Position yourself for a leadership and management role in the dynamic engineering and technology sectors! Learn at your own pace and power your future with this fully online Master of Engineering in Engineering Management (ME-EM) from an RI Research University.Learn more about Engineering Management Program on Coursera. opens in new window
Tuition prices may vary depending on program.
CSCA 5414 Dynamic Programming, Greedy AlgorithmsSpecialization: Foundations of Data Structures and AlgorithmsInstructor: Sriram Sankaranarayanan, Ph.D., Co-Associate Chair for Undergraduate Education, Professor of Computer Science
See Coursera and syllabus opens in new window for detailed description, including any required materials.
This course covers basic algorithm design techniques such as divide and conquer, dynamic programming, and greedy algorithms. It concludes with a brief introduction to intractability (NP-completeness) and using linear/integer programming solvers for solving optimization problems. Cross listed with DTSA 5503.
CSCA 5424 Approximation Algorithms and Linear ProgrammingSpecialization: Graduate AlgorithmsInstructor: Sriram Sankaranarayanan, Ph.D., Co-Associate Chair for Undergraduate Education, Professor of Computer Science
Covers ideas surrounding approximation algorithms including a rigorous mathematical analysis of the approximation guarantees provided by these algorithms. Teaches the use of linear/integer programming formulations for common algorithmic problems and the relation between integer optimization problems and their linear programming relaxations. Introduces key mathematical concepts needed to analyze these algorithms and explores the application of algorithmic concepts to real-world problems.
CSCA 5454 Advanced Data Structures, RSA and Quantum AlgorithmsSpecialization: Foundations of Data Structures and AlgorithmsInstructor: Sriram Sankaranarayanan, Ph.D., Co-Associate Chair for Undergraduate Education, Professor of Computer Science
See Coursera opens in new window and syllabus opens in new window for detailed description, including any required materials.
CSCA 5008 Fundamentals of Software Architecture for Big DataSpecialization: Software Architecture for Big DataInstructor: Mike Barinek, Lecturer & Tyson Gern, Delivery Lead at VMware Tanzu Labs
The course is intended for individuals looking to understand the basics of software engineering as they relate to building large software systems that leverage big data. Learners will be introduced to software engineering concepts necessary to build and scale large, data intensive, distributed systems. Starting with software engineering best practices and loosely coupled, highly cohesive data microservices, the course takes learners through the evolution of a distributed system over time. Cross listed with DTSA 5507.
CSCA 5018 Software Architecture Patterns for Big DataSpecialization: Software Architecture for Big DataInstructor: Mike Barinek, Lecturer & Tyson Gern, Delivery Lead at VMware Tanzu Labs
The course is intended for individuals looking to understand the architecture patterns necessary to take large software systems that leverage big data to production. Learners will transform big data prototypes into high quality tested production software. After measuring the performance characteristics of distributed systems, learners will identify trouble areas and implement scalable solutions to improve performance. Upon completion of the course learners will know how to scale production datastores to perform under load, designing load tests to ensure applications meet performance requirements. Cross listed with DTSA 5508.
CSCA 5028 Applications of Software Architecture for Big DataSpecialization: Software Architecture for Big DataInstructor: Mike Barinek, Lecturer & Tyson Gern, Delivery Lead at VMware Tanzu Labs
The course is intended for individuals who want to build a production-quality software system that leverages big data. Learners will apply the basics of software engineering and architecture to create a production-ready distributed system that handles big data. Learners will build and scale a large, data intensive, distributed system, composed of loosely coupled, highly cohesive data microservices. Cross listed with DTSA 55714.
CSCA 5622 Introduction to Machine Learning - Supervised LearningSpecialization: Machine Learning: Theory and Hands-on Practice with PythonInstructor: Geena Kim, Instructor
This course introduces various supervised ML algorithms and prediction tasks applied to different data. Specific topics include linear and logistic regression, KNN, Decision trees, ensemble methods such as Random Forest and Boosting, and kernel methods such as SVM. Cross listed with DTSA 5509.
CSCA 5632 Unsupervised Algorithms in Machine LearningSpecialization: Machine Learning: Theory and Hands-on Practice with PythonInstructor: Geena Kim, Instructor
In this course, we will learn selected unsupervised learning methods for dimensionality reduction, clustering, finding latent features, and application cases such as recommender systems with hands-on examples of product recommendation algorithms. Cross listed with DTSA 5510.
CSCA 5642 Introduction to Deep LearningSpecialization: Machine Learning: Theory and Hands-on Practice with PythonInstructor: Geena Kim, Instructor
Course will cover the basics of deep learning, such as multilayer perceptron, convolutional neural network, recurrent neural network, how to build and train neural network models, optimization methods, and application examples Cross listed with DTSA 5511.
CSCA 5214 Computing, Ethics, and Society FoundationsSpecialization: Computing, Ethics, and SocietyInstructor: Bobby Schnabel, Professor, Department External Chair
Computing systems and technologies fundamentally impact the lives of most people in the world, including how we communicate, get information, socialize, and receive healthcare. This course is the first of a three course sequence that examines ethical issues in the design and implementation of computing systems and technologies, and reflects upon the broad implication of computing on our society. It covers ethical theories, privacy, security, social media, and misinformation.
CSCA 5224 Ethical Issues in AI and Professional EthicsSpecialization: Computing, Ethics, and SocietyInstructor: Bobby Schnabel, Professor, Department External Chair
Computing systems and technologies fundamentally impact the lives of most people in the world, including how we communicate, get information, socialize, and receive healthcare. This course is the second of a three course sequence that examines ethical issues in the design and implementation of computing systems and technologies, and reflects upon the broad implication of computing on our society. It covers algorithmic bias in machine learning methods, professional ethics, and issues in the tech workplace.
CSCA 5234 Ethical Issues in Computing ApplicationsSpecialization: Computing, Ethics, and SocietyInstructor: Bobby Schnabel, Professor, Department External Chair
Computing systems and technologies fundamentally impact the lives of most people in the world, including how we communicate, get information, socialize, and receive healthcare. This course is the third of a three course sequence that examines ethical issues in the design and implementation of computing systems and technologies, and reflects upon the broad implication of computing on our society. It covers medical applications, uses of robotics, autonomous vehicles, and the future of work.
CSCA 5502 Data Mining PipelineSpecialization: Data Mining Foundations and PracticeInstructor: Qin (Christine) Lv, Ph.D., Professor of Computer Science
This course introduces the key steps involved in the data mining pipeline, including data understanding, data preprocessing, data warehouse, data modeling, interpretation and evaluation, and real-world applications. Cross listed with DTSA 5504.
CSCA 5512 Data Mining MethodsSpecialization: Data Mining Foundations and PracticeInstructor: Qin (Christine) Lv, Ph.D., Professor of Computer Science
This course covers core techniques used in data mining, including frequent pattern analysis, classification, clustering, outlier detection, as well as time-series mining and graph mining. Cross listed with DTSA 5505.
CSCA 5522 Data Mining ProjectSpecialization: Data Mining Foundations and PracticeInstructor: Qin (Christine) Lv, Ph.D., Professor of Computer Science
This course offers step-by-step guidance and hands-on experience of designing and implementing a real-world data mining project, including problem formulation, literature survey, proposed work, evaluation, discussion and future work.. Cross listed with DTSA 5506
CSCA 5112 Introduction to Generative AISpecialization: Generative AIInstructor: Tom Yeh, Ph.D., Associate Professor of Computer Science
In this course, students will learn about several topics related to Generative AI, including deep learning and machine learning algorithms that enable machines to generate text, images, and music. Additionally, they will also learn about the diffusion model and transformer model, which are important techniques used in Generative AI. The course will guide students on how to apply these techniques to design and build their own generative models and apply those models to new problems.
CSCA 5222 Introduction to Computer VisionSpecialization: Introduction to Computer VisionInstructor: Tom Yeh, Ph.D., Associate Professor of Computer Science
This course guides students through the essential algorithms and methods to help computers 'see' and interpret visual data. Students learn the core concepts and techniques that have been traditionally used to analyze images. Then, students learn modern deep learning methods, such as neural networks and specific models designed for image recognition, can be used to perform more complex tasks like object detection and image segmentation. Additionally, students will learn the creation and impact of AI-generated images and videos, exploring the ethical considerations of such technology.
CSCA 5433 When to Regulate? The Digital Divide and Net NeutralitySpecialization: Internet Policy: Principles and ProblemsInstructor: David Reed, Ph.D., Scholar in Residence
This is the first out of three courses exploring Internet Policy: Principles and Problems, which is part of CU Boulder’s Masters of Science in Data Science program on Coursera. This course builds an interdisciplinary policy framework to critique and develop regulatory approaches to real-world problems on the Internet. Learners then use the framework to develop a definition of broadband to improve the Digital Divide and to evaluate net neutrality regulations. Cross listed with DTSA 5736.
CSCA 5063 Network Systems FoundationSpecialization: Network Systems: Principles and Practice (Linux and Cloud Networking)Instructor: Eric Keller, Associate Professor
In this course, students will learn the most important principles in network systems. This will center on the layered design of networks, and cover the link layer (Ethernet), network layer (IP), transport layer (TCP, UDP), and application layer (HTTP, gRPC). With those as a foundation, student will learn about network security problems and how some current solutions work at different layers.Same as ECEA 5370.
CSCA 5073 Linux NetworkingSpecialization: Network Systems: Principles and Practice (Linux and Cloud Networking)Instructor: Eric Keller, Associate Professor
In this course students will learn how networking is designed and used in the Linux operating system. This will be learned in the context of networking principles and the application to real modern uses – building network operating systems (that power network appliances) and using Linux to support connectivity in modern containerized and virtualized applications (such as a Kubernetes network plugin). Same as ECEA 5371.
CSCA 5083 Cloud NetworkingSpecialization: Network Systems: Principles and Practice (Linux and Cloud Networking)Instructor: Eric Keller, Associate Professor
In this class, students will learn about the networking abstractions and services for building applications in the cloud, and the technology underlying cloud networking. Students will be able to architect complex applications in the cloud. In understanding how the cloud providers created their networks, students will be in a better position to troubleshoot applications and analyze different possible ways of architecting applications, and even help design the next generation of networking for cloud providers.Same as ECEA 5372.
CSCA 5834 Modeling of Autonomous SystemsSpecialization: Foundations of Autonomous SystemsInstructor: Dr. Majid Zamani, Associate Professor, Co-Associate Chair for Graduate Education
This course will explain the core structure in any autonomous system which includes sensors, actuators, and potentially communication networks. Then, it will cover different formal modeling frameworks used for autonomous systems including state-space representations (difference or differential equations), timed automata, hybrid automata, and in general transition systems. It will describe solutions and behaviors of systems and different interconnections between systems.
CSCA 5844 Requirement Specifications for Autonomous SystemsSpecialization: Foundations of Autonomous SystemsInstructor: Dr. Majid Zamani, Associate Professor, Co-Associate Chair for Graduate Education
This course will discuss different ways of formally modeling requirements of interest for autonomous systems. Examples of such requirements include stability, invariance, reachability, regular languages, omega-regular languages, and linear temporal logic properties. In addition, it will introduce non-deterministic finite and büchi automata for recognizing, respectively, regular languages and omega-regular languages.
CSCA 5854 Verification and Synthesis of Autonomous SystemsSpecialization: Foundations of Autonomous SystemsInstructor: Dr. Majid Zamani, Associate Professor, Co-Associate Chair for Graduate Education
This course will provide different techniques on the verification of autonomous systems against stability, regular, or omega-regular properties. Such techniques include Lyapunov theories, reachability analysis, barrier certificates, and model checking. Finally, it will introduce several techniques on designing controllers enforcing properties of interest over the original autonomous systems.
CSCA 5428 Object-Oriented Analysis and Design: Foundations and ConceptsSpecialization: Object-Oriented Analysis & DesignInstructor: Bruce Montgomery, Senior Instructor, Faculty Director for Professional Master's Program
An applied analysis and design class that addresses the use of object-oriented techniques. Topics include domain modeling, use cases, architectural design and modeling notations. Students apply techniques in analysis and design projects. Focus is on key object-oriented elements and concepts.
CSCA 5438 Object-Oriented Analysis and Design: Patterns and PrinciplesSpecialization: Object-Oriented Analysis & DesignInstructor: Bruce Montgomery, Senior Instructor, Faculty Director for Professional Master's Program
An applied analysis and design class that addresses the use of object-oriented techniques. Topics include domain modeling, use cases, architectural design and modeling notations. Students apply techniques in analysis and design projects. Focus is on key object-oriented design patterns and principles.
CSCA 5448 Object-Oriented Analysis and Design: Practice and ArchitectureSpecialization: Object-Oriented Analysis & DesignInstructor: Bruce Montgomery, Senior Instructor, Faculty Director for Professional Master's Program
An applied analysis and design class that addresses the use of object-oriented techniques. Topics include domain modeling, use cases, architectural design and modeling notations. Students apply techniques in analysis and design projects. Focus is on key object-oriented practices and architectural design.
CSCA 5303 Attacking the NetworkSpecialization: Security and Ethical HackingInstructor: Ahmed Hamza, PhD., Associate Teaching Professor
This course explains the science and art behind offensive security techniques used in penetration testing of networks and systems. A review of networking concepts is given. Students will utilize low-level programming through network interfaces, in executing a variety of network attacks, while learning to use essential auxiliary tooling. An introduction to cryptography for pentesters is provided.
CSCA 5842 Deep Learning for Natural Language ProcessingSpecialization: Natural Language Processing
Deep learning has revolutionized the field of natural language processing and led to many state-of-the-art results. This course introduces students to neural network models and training algorithms frequently used in natural language processing. At the end of this course, learners will be able to explain and implement feedforward networks, recurrent neural networks, convolutional neural networks, and transformers. They will also have an understanding of transfer learning, the paradigm behind popular models such as BERT and GPT-3.
CSCA 5832 Fundamentals of Natural Language ProcessingSpecialization: Natural Language Processing
The field of natural language processing aims at getting computers to perform useful and interesting tasks with human language. This course introduces students to the fundamental problems in NLP, the fundamental techniques that are used to solve those problems and lays the foundation for understanding state-of-art methods. At the end of the course, students will be able to implement and analyze text classifiers, sequence labelers, discrete probabilistic models, and vector-based approaches to word meaning.
CSCA 5313 Attacking Unix & WindowsSpecialization: Security and Ethical HackingInstructor: Ahmed Hamza, PhD., Associate Teaching Professor
This course in the sequence examines attacks on computer systems, with particular attention to Unix Security Model and Windows for memory corruption and binary exploitation. Students can expect to learn about, and apply offensive techniques against, Unix in general. We will demonstrate lateral movement and privilege escalation attacks, as well as buffer overflow and other memory exploitation primitives. Course assessments are through quizzes, hands-on exercises and an exam.
EMEA 5021 Product Cost and Investment Cash Flow AnalysisSpecialization: Finance for Technical ManagersInstructor: Michael Readey, Professor of Engineering Practice
See Coursera for detailed description, including any required materials.
This first course in the finance sequence discusses costs and business practices to establish the cost of a product. The concept of time value of money (TVM) is developed to determine the present and future values of a series of cash flows. TVM principles are then applied to personal finances and retirement planning. This is a practical course that uses spreadsheets extensively to better prepare students in engineering and science for a career in industry.
EMEA 5022 Project Valuation and the Capital Budgeting ProcessSpecialization: Finance for Technical ManagersInstructor: Michael Readey, Professor of Engineering Practice
This second course in the finance sequence describes the economic viability of an engineering project through application of net present value, internal rate of return, and payback period analysis. The impacts of depreciation, taxes, inflation and foreign exchange are then addressed. The capital budgeting process is discussed, showing how companies make decisions to optimize their investment portfolio. Risk is mitigated through application of quantitative techniques such as scenario analysis, sensitivity analysis and real options analysis.
EMEA 5023 Financial Forecasting and ReportingSpecialization: Finance for Technical ManagersInstructor: Michael Readey, Professor of Engineering Practice
This third and final course in the finance sequence discusses how public projects are evaluated using cost-benefit analysis. Students then learn how interest rates and prices for stocks and bonds are determined. Techniques are presented on how to create departmental budgets for engineering cost centers and pro forma statements for profit centers. Students then work with corporate financial statements to assess a company’s financial health, including recent measures of environmental, social and corporate governance (ESG).
EMEA 5031 Project Management: Foundations and InitiationSpecialization: Project ManagementInstructor: Christy Bozic, Professor of Engineering Practice
The goal of this introductory course in a series of three is to provide students the foundational knowledge of how engineering projects are managed and initiated. Engineering project managers are responsible for project scope, stakeholder management, effective communication, and team leadership. In this course you will develop introductory skills needed to manage traditional engineering projects, along with tools needed to engage stakeholders and build diverse teams.
EMEA 5032 Project Planning and ExecutionSpecialization: Project ManagementInstructor: Christy Bozic, Professor of Engineering Practice
The goal of this second course in a series of three is to provide students with skills necessary to plan and execute traditional engineering projects. Project managers must plan and manage complex projects constrained by time and budget. As part of this course, you will determine project schedules, budgets, and risk assessments. At the end of this course, you will be able to identify and explain various quality tools and methods used in project management.
EMEA 5033 Agile Project ManagementSpecialization: Project ManagementInstructor: Christy Bozic, Professor of Engineering Practice
The goal of this third course in a series of three examines the philosophy and process of managing projects using Agile project management. Students in this course will learn the Agile philosophy and process including the Scrum framework, sprints, and user stories. Upon completion of this course, you will be able to distinguish between traditional and agile project management methodologies and understand the benefits of delivering value early in an engineering project.
EMEA 5051 Leading Oneself with Self-KnowledgeSpecialization: Principles of Leadership: Leading OneselfInstructor: Ron Duren,Teaching Assistant Professor
Before we can lead others well, we must first learn to lead ourselves well. Knowing thyself is the starting point on this journey. In this course, you will come to understand the importance of three forms of awareness, craft a personal identity, gain understanding of how you work best, learn to be strategic with your time and energy and manage cognitive biases and understand your worldview.
EMEA 5052 Leading Oneself with Purpose and MeaningSpecialization:Principles of Leadership: Leading OneselfInstructor: Ron Duren,Teaching Assistant Professor
Before we can lead others well, we must first learn to lead ourselves well. Knowing your why is an important part of this journey. In this course, you will identify your core purpose and recognize meaning in your life, explore the power of spirituality and embracing our mortality, create a lasting impact by serving a greater good, describe your character and practice personal excellence.
EMEA 5053 Leading Oneself with Personal ExcellenceSpecialization: Principles of Leadership: Leading OneselfInstructor: Ron Duren,Teaching Assistant Professor
Before we can lead others well, we must first learn to lead ourselves well. Knowing personal excellence is the culmination of this journey. In this course, you will describe how and why to set goals and create action plans, increase your focus and reduce distraction, harness motivation and flow state for performance, build self-efficacy and agency, and redefine your relationship with stress, anxiety, fear and adversity.
EMEA 5016 Communication as a Technical LeaderSpecialization: Technical CommunicationInstructor: Daniel Moorer, Professor of Engineering Practice
An engineering leader spends a majority of their day interacting with others. Indeed, studies repeatedly point to the impact communication skills have on the ability of managerial leaders to succeed or fail. Too often, individuals move into managerial leadership roles without an awareness of the need to improve in this area. This course focuses on interpersonal skills such as listening, counseling, non-verbals, mentoring, coaching, building trust, and providing feedback.
EMEA 5017 Technical Managerial Written SkillsSpecialization: Technical CommunicationInstructor: Daniel Moorer, Professor of Engineering Practice
Writing effective documents to influence teams and decision-makers is one of the essential elements of successful management. Additionally, in all of its forms, writing remains one of the primary vehicles by which a leader exercises leadership. Just like the other forms of communication, it must be coherent, complete, make a clear argument, and include appropriate decorum. This course focuses on these attributes as applied in all forms of modern written communication.
EMEA 5018 Speaking to a Technical GroupSpecialization: Technical CommunicationInstructor: Daniel Moorer, Professor of Engineering Practice
Great speakers focus on voice, nonverbals, eye contact, body language, and storytelling to captivate their audiences. Moreover, as a leader, it is possible to communicate in such a manner and in such a tone of voice so as to inspire in others nothing but an intense desire to excel, making this form, potentially, the most powerful leadership-communication skill of all. This course focuses on the fundamentals of excellent oral communication.
EMEA 5054 Leadership Style and Building a High Performance TeamSpecialization: Principles of Leadership: Leading Technical OrganizationsInstructor: Kathy Tobey, Professor of Engineering Practice
Leadership of complex technical organizations is being challenged by the rapid pace of technology development, innovation and the new flexible workplace where employees working from anywhere demand to be engaged, motivated and recognized. This first Leading Technical Organizations course explores leadership style, value creation, how a leader multiplies their abilities by building high performance teams, leading through others and that one's executive presence is essential to be a leader of leaders.
EMEA 5055 Accountability and Employee EngagementSpecialization: Principles of Leadership: Leading Technical OrganizationsInstructor: Kathy Tobey, Professor of Engineering Practice
Being a successful leader in a complex technical organization requires being ultimately accountable for your team’s performance and meeting commitments to all your stakeholders. This second Leading Technical Organizations course explores how organizational leaders use different decision-making processes for different situations and that they are ultimately accountable for all results. You’ll also look into how a company’s culture drives strategy, risk and meeting stakeholder commitments.
EMEA 5056 Value Creation and Building Enduring RelationshipsSpecialization: Principles of Leadership: Leading Technical OrganizationsInstructor: Kathy Tobey, Professor of Engineering Practice
The most effective leaders in complex technical organizations are successful leading the performance of large-scale technical endeavors. These leaders have generally established a network of professional relationships, supporting them throughout their career. This third Leading Technical Organizations course explores techniques for building enduring relationships that have a multiplicative impact on business success. The course provides insight into how authentic leadership yields employee engagement that is critical to strategizing, planning and performing large scale technical endeavors.
EMEA 5057 Your World and What Shapes ItSpecialization: Global Perspectives of Diversity, Equity, and Inclusion in the WorkplaceInstructor: Jessica Leeker, Professor of Engineering Practice
Advancing equity, diversity, and inclusion (DEI) requires a process of examination, self-reflection, and action. In this course, students will examine their identity and background and reflect on how it has shaped their thoughts, activities, and relationships with others. The student will also explore the historical narratives and power dynamics that have shaped their environment. Discussions surrounding course topics will be approached through a global lens.
EMEA 5058 Their World and How You Define ItSpecialization: Global Perspectives of Diversity, Equity, and Inclusion in the WorkplaceInstructor: Jessica Leeker, Professor of Engineering Practice
As future leaders in workplace DEI initiatives, it is essential to develop an awareness of the experiences faced by others and cultural empathy. In this course, students will listen to and reflect on the voices of women, black, LGBTQ+, and neurodiverse experiences. Through listening, students will learn to look inward and confront their own ignorance, biases, or stereotypes.
EMEA 5059 Our World and How to Accept ItSpecialization: Global Perspectives of Diversity, Equity, and Inclusion in the WorkplaceInstructor: Jessica Leeker, Professor of Engineering Practice
In this course, students will learn the history of DEI in the workplace and how DEI initiatives can be successfully implemented in a global environment. The course will provide students with a toolkit to make lasting changes for themself and their interactions with others.
EMEA 5091 Getting Started with Technology StartupsSpecialization: Technology EntrepreneurshipInstructor: John Thomas, Scholar in Residence
This course will introduce the contemporary practice of entrepreneurship for engineers. Students will identify their driving purpose for creating a new startup and explore the fundamental tools and practice of entrepreneurship. They will develop the knowledge and skills for thinking and acting like an entrepreneur and gain insight about how to recognize new opportunities. The tools, resources, and methods introduced can be used to generate new product and service ideas that address real customer needs.
EMEA 5092 Creating a Technology Startup CompanySpecialization: Technology EntrepreneurshipInstructor: John Thomas, Scholar in Residence
This course will examine the core elements that make up the inner and outer workings of a startup company. Students will learn how to define, research, and segment markets and use that knowledge to develop viable business and revenue models. The models will be used to construct pro forma financial statements suitable for potential investors. Students will gain the knowledge and skills to build networks and teams and create a lean business plan of operations.
EMEA 5093 Forming, Funding, and Launching a Technology Startup CompanySpecialization: Technology EntrepreneurshipInstructor: John Thomas, Scholar in Residence
This course explores the key steps and processes involved with forming, funding, and launching a startup company. Students will learn about funding options and how to interpret investor needs and requirements. They will gain the knowledge and skills needed for creating and presenting viable business plans to potential investors. Students will explore topics related to company formation, legal issues relevant to startups, and map the key steps to launching, growing, and exiting a startup company.
EMEA 5006 Defining, Describing and Visualizing DataSpecialization: The Data Driven ManagerInstructor: Wendy Martin, Teaching Associate Professor
As leaders in your chosen field, you need to not only know how to ask the right questions but also answer them using data-based methods. Through this class, you'll be able to get to the bottom of what you really want to know, describe the associated data related to that question and visualize the information from that data to understand and explain the results.
EMEA 5007 Data Acquisition, Risk and EstimationSpecialization: The Data Driven ManagerInstructor: Wendy Martin, Teaching Associate Professor
Engineering and Business professionals often have access to many sources of data. The best way to ensure your data is both valid and reliable is to plan for it ahead of time. Through this class, you'll be able to plan for accurate and precise data generation, then use that data for the purpose of estimation and risk reduction related to capital investments.
EMEA 5008 Data Driven Decision MakingSpecialization: The Data Driven ManagerInstructor: Wendy Martin, Teaching Associate Professor
Once we’ve generated data, we need to answer the research question by performing an appropriate statistical analysis. Engineers and Business Professionals need to know which test or tests to use. Through this class, you'll be able to plan for accurate and precise data generation, then use that data for the purpose of estimation and risk reduction related to capital investments.
EMEA 5061 A Technical Leader's Qualities and EffectivenessSpecialization: Principles of Leadership: Leading Technical TeamsInstructor: Daniel Moorer, Professor of Engineering Practice
This course describes the traits of Great Leaders who combine fierce resolve with personal humility. Indeed, they might be described more as “plow horses” as opposed to “show horses”. They see themselves as servants to the team and to the organization. They “hold the line” when faced with tough decisions and “do what must be done” when the time comes. Their leadership is based on solid ethical principles and they act with quiet, calm determination.
EMEA 5062 Challenges of Leading Individuals in the Tech IndustrySpecialization: Principles of Leadership: Leading Technical TeamsInstructor: Daniel Moorer, Professor of Engineering Practice
Great Leaders lead by example. They protect their team members, empower them, and help them to improve and grow while the team members, in turn, help the organization improve and grow. Working together with the team, they envision what the organization could be and inspire others to help execute the strategy that will take them there. Many times, they see their team members as more of a family than simply as business acquaintances.
EMEA 5063 Challenges of Leading Technical TeamsSpecialization: Principles of Leadership: Leading Technical TeamsInstructor: Daniel Moorer, Professor of Engineering Practice
Great Leaders’ ambition is for the organization and team first, and for themselves a distant second. They help develop and “spin-off” other great leaders and help set up their successors for success. They seek truth about their organization, seeing it from the outside-in as well as from the inside-out. Most importantly, they focus on establishing processes that allow the organization to operate smoothly and efficiently.
EMEA 5034 The Need for Systems EngineeringSpecialization: Introduction to Systems EngineeringInstructor: William Van Atten, Lecturer
Systems engineering is an interdisciplinary approach to designing, realizing, and managing complex systems. In this course, you will be introduced to principles of systems engineering and its importance to the development of complex systems. You will learn to identify and define systems, manage their complexity, and describe their life cycle. The course uses real-world engineering examples to address how the systems engineering approach can address challenges.
EMEA 5035 Applying Systems Engineering to the Design ProcessSpecialization: Introduction to Systems EngineeringInstructor: William Van Atten, Lecturer
In this course, you will learn what a systems engineer does. Following the conceptual foundations from The Need for Systems Engineering, you will perform requirements analysis and functional analysis on engineering programs. You will learn how to perform a trade study using a methodical, quantitative approach that is universal in application. This course also covers preparing design reviews, focusing on coordinating the inputs of multiple engineering disciplines into a cohesive description of the design approach.
EMEA 5036 Systems Engineering and Program ManagementSpecialization: Introduction to Systems EngineeringInstructor: William Van Atten, Lecturer
This course teaches the learner how to apply Systems Engineering to the overall management of a complex program. This includes tailoring the systems engineering process to the specific needs of a particular program. The risk management process is described, including how to identify risks and develop a mitigation strategy. The key management tools are described along with how the scope of a program is defined and managed according to the terms of the contract.
EMEA 5064 The Neuroscience of Personal ExcellenceSpecialization: Neuroscience of Personal ExcellenceInstructor: Ron Duren, Teaching Assistant Professor
This course examines leadership techniques through the lens of social cognitive neuroscience and psychology. Utilizing the latest research, we develop a leadership practice based on the foundation of neuroscience. Topics include neuroplasticity, regulating arousal, personal performance, flow state, decision-making and learning. This course focuses on personal excellence to lead oneself.
EMEA 5065 The Neuroscience of Leading High-Performance TeamsSpecialization: Neuroscience of Personal ExcellenceInstructor: Ron Duren, Teaching Assistant Professor
This course examines leadership techniques through the lens of social cognitive neuroscience and psychology. Utilizing the latest research, we develop a leadership practice based on the foundation of neuroscience. Topics include motivation, storytelling, improv, collaboration, psychological safety, influence, and coaching. This course focuses on leading high-performance teams.
EMEA 5066 The Neuroscience of Leading Transformational OrganizationsSpecialization: Neuroscience of Personal ExcellenceInstructor: Ron Duren, Teaching Assistant Professor
This course examines leadership techniques through the lens of social cognitive neuroscience and psychology. Utilizing the latest research, we develop a leadership practice based on the foundation of neuroscience. Topics include innovation, creativity, facilitating change, gender and diversity, mental toughness, and explore the neuroscience of business. This course focuses on leading transformational organizations.
EMEA 5081 A Theoretical Origin of Ethics in Business and Tech IndustrySpecialization: Ethical Decision-Making in the Tech IndustryInstructor: Dr. Daniel Moorer, Professor of Engineering Practice
In the pursuit of a clear understanding of business ethics, one may begin by considering our evolved eusocial behavior. Is the source of morality fundamentally biological in nature? If so, does that help to provide us with an explanation for the unresolvable tension between selfishness and altruism? Indeed, may we use this theory to help, then, explain the human condition and the drivers of ethics in business and industry?
EMEA 5082 Avoiding Ethical Pitfalls in the Tech IndustrySpecialization: Ethical Decision-Making in the Tech IndustryInstructor: Dr. Daniel Moorer, Professor of Engineering Practice
Most executives who commit crimes make those decisions on the basis of intuition and gut feeling. The weaknesses associated with this type of decision-making are exacerbated by an environment where leaders are increasingly distanced from the consequences of their decisions and the individuals they impact. This course is a look at the ethical dark side of the modern business world.
EMEA 5083 Ethical Decision Making for Success in the Tech IndustrySpecialization: Ethical Decision-Making in the Tech IndustryInstructor: Dr. Daniel Moorer, Professor of Engineering Practice
Good ethics is absolutely essential to effective business practice. That is, how each employee works and the standards they uphold while working affects both personal and company reputations. Indirectly, they also affect politics, society at large, and even the national reputation. This course focuses on various techniques that help one avoid an incorrect ethical path in business and industry and, instead, make ethically correct decisions.
EMEA 5401 Strategic Product DevelopmentSpecialization: Product DevelopmentInstructor: Dr. Michael Readey, EMP Associate Faculty Director, W. Edwards Deming Professor of Management
This first course in the product development specialization discusses how companies create new products that customers want while achieving their financial objectives. We begin by defining the product strategies necessary to ensure a company’s long-term growth. We then explore the different product development processes used by high-tech businesses today, such as Stage-Gate and Lean/Agile techniques. We conclude illustrating the tools to build the high-performance teams that take the development process from concept through product launch.
EMEA 5402 Managing the New Product Development ProcessSpecialization: Product DevelopmentInstructor: Dr. Michael Readey, EMP Associate Faculty Director, W. Edwards Deming Professor of Management
This second course in the product development specialization goes into the product development process in detail. With the opportunity defined, we begin with ideation techniques such as Design Thinking to create new product concepts. We then define the tools to create product specifications that meet customer requirements, and then conceptualize different ways of meeting those requirements. With finally explore prototyping and the techniques used to down-select to a concept that is then carried through launch.
EMEA 5403 Product Innovation ManagementSpecialization: Product DevelopmentInstructor: Dr. Michael Readey, EMP Associate Faculty Director, W. Edwards Deming Professor of Management
This third course in the product development specialization discusses a product’s life cycle with the strategies to ensure long-term success. We begin with an overview of digital product development and how it differs from physical products. Students are then introduced to product roadmaps and forecasting techniques, and apply these in creating a compelling financial business case. We conclude with how sustainability impacts product development today and how to design innovative products for a circular economy.
EMEA 5231 Resilience and Leadership: Concepts, Definitions, and FrameworksSpecialization: Resilience Engineering and Leadership in CrisisInstructor: Dr. Thomas John, Scholar In Residence, Lockheed Martin Engineering Management Program
This course is part 1 of 3 that comprise the specialization 'Resilience Engineering and Leadership in Crisis'. The course introduces the common terms, definitions, and concepts that characterize resilient systems. Frameworks for resilience engineering and leadership in crisis are applied to complex systems and the built environment. Learners will explore a holistic approach to critical infrastructure resilience and apply a threat assessment protocol to a project scenario.
EMEA 5232 Resilience and Leadership: Tools, Methods, and ApplicationsSpecialization: Resilience Engineering and Leadership in CrisisInstructor: Dr. Thomas John, Scholar In Residence, Lockheed Martin Engineering Management Program
This course is Part 2 of 3 comprising the specialization 'Resilience Engineering and Leadership in Crisis.' The course offers tools and methods for applying the concepts from Part 1 to various applications and disaster scenarios. Systems thinking, crisis management lifecycle, and organizational strategy are presented to help cultivate and strengthen crisis leadership and communication skills. Learners will assess the resilience of a complex system and create a crisis management plan.
EMEA 5233 Resilience and Leadership: Design, Development, and Integration Specialization: Resilience Engineering and Leadership in CrisisInstructor: Dr. Thomas John, Scholar In Residence, Lockheed Martin Engineering Management Program
This course is part 3 of 3 that comprise the specialization ‘Resilience Engineering and Leadership in Crisis’. The course emphasizes the importance of practices like organizational learning and adaptive change management amid uncertainty. Resilience engineering principles and strategies are combined with critical leadership knowledge and skills essential to navigating unanticipated catastrophic disruptions. Learners will integrate selective assignments from Parts 1, 2, & 3 to construct a comprehensive resilience report of a complex project scenario.
EMEA 5216 Sustainability and the Circular EconomySpecialization: Applied Sustainability for Technical ManagersInstructor: Dr. Michael Readey, EMP Associate Faculty Director, W. Edwards Deming Professor of Management, Scholar In Residence
This first course in the Applied Sustainability specialization discusses the need to shift from today’s linear economy to a circular one. The course begins with the sustainability imperative and introduces the Anthropocene. It then shifts to solutions, detailing the rapid transition to renewable energy, electric vehicles, and the design of more environmentally responsible buildings. The course closes with an overview of the circular economy, and how it is integrated into these solutions.
EMEA 5217 Applied Sustainability EngineeringSpecialization: Applied Sustainability for Technical ManagersInstructor: Dr. Michael Readey, EMP Associate Faculty Director, W. Edwards Deming Professor of Management, Scholar In Residence
This second course in the Applied Sustainability specialization discusses the techniques used by engineers and scientists to develop and assess the environmental impact of products and processes. It discusses carbon and water footprints and how they are determined. Topics then address the different approaches to environmental analysis, including life cycle assessment, energy and material flow analysis, and eco-audits. The course concludes definitions of what constitutes circular product and packaging design.
EMEA 5218 Leading the Circular BusinessSpecialization: Applied Sustainability for Technical ManagersInstructor: Dr. Michael Readey, EMP Associate Faculty Director, W. Edwards Deming Professor of Management, Scholar In Residence
This final course in the Applied Sustainability specialization discusses the business case for circularity. Topics include design of production and operations and ensuring circularity throughout the supply chain. The course then examines the marketing of circular products and what distinguishes true marketing from greenwashing. Finance is impacted by circularity and is addressed through Triple Bottom Line accounting. Finally, the course concludes with how individuals can become agents of change in the organizations where they work.
EMEA 5226 Sustainable and Resilient Operations ManagementSpecialization: Sustainable and Resilient Operations and Supply ChainsInstructor: Christy Bozic, Professor of Engineering Practice
Operations management is the use of company resources to create value or meet a market need. Increasingly, customers are demanding more attention be paid to the environmental impacts of the goods and services they buy. In this course, students will learn concepts and practices companies employ to manage business processes that meet the needs of shareholders and employees while reducing negative impacts on the pollution and waste.
EMEA 5227 Developing and Managing Sustainable Supply ChainsSpecialization: Sustainable and Resilient Operations and Supply ChainsInstructor: Christy Bozic, Professor of Engineering Practice
Customers are becoming more aware of the environmental and social impacts of where and how the products they purchase are produced and delivered. Many are demanding organizations act in environmentally responsible ways. In this course, you will learn to build a more sustainable and socially responsible supply chain while meeting business expectations.
EMEA 5228 Impacts of Sustainable Operations and Supply ChainsSpecialization: Sustainable and Resilient Operations and Supply ChainsInstructor: Christy Bozic, Professor of Engineering Practice
See Syllabus for detailed description, including any required materials.
Innovative organizations need leaders and managers who understand the complex nature of corporate social responsibility, sustainability, and resilience. In this course, students will learn strategies to become good corporate citizens while still creating value for stakeholders. You will learn methods to measure environmental and social impacts of sustainable operations and supply chains.
EMEA 5222 Product Design for the Circular EconomySpecialization: Sustainable and Circular Product DevelopmentInstructor: Michael Readey, Professor of Engineering Practice
This first course in the Sustainable and Circular Product Development specialization provides the tools necessary to implement Circular Economy (CE) principles. Methodologies include Cradle-to-Cradle, Design for “R”, where R refers to Reuse, Repair, Remanufacturing, and Recycling. Organic materials enable the biological cycle as a component to CE. Products are often packaged, and a circular product needs to also have circular packaging. Finally, the course highlights ways designers can select the appropriate materials to achieve their circularity objectives.
EMEA 5223 Packaging Design for the Circular EconomySpecialization: Sustainable and Circular Product DevelopmentInstructor: Michael Readey, Professor of Engineering Practice
The Circular Economy is about zero waste, where products are disassembled into their constituent components, either to be recycled or composted. While considerable attention has been on the product itself, a product can only be sustainable or circular if the packaging it comes in is also sustainable and circular. This course provides an overview of packaging today, and how it is evolving to become more sustainable. Topics include packaging systems, functionality, materials, and recycling strategies.
EMEA 5224 Circular Product Design Frameworks and CertificationsSpecialization: Sustainable and Circular Product DevelopmentInstructor: Michael Readey, Professor of Engineering Practice
This final course in the Sustainable and Circular Product Development specialization provides the tools necessary to take a circular product design to the next step, including frameworks such as Cradle-to-Cradle, Biomimicry, ISO 14000 and several EU Directives. Products can be certified if they meet certain criteria, and the course covers the major certifications available today. Finally, the course shows how companies report their progress using methods prescribed by ISO standards or the Global Reporting Initiative (GRI).
EMEA 5241 The Circular EconomySpecialization: Transformative Leadership in the Circular EconomyInstructor: Christy Bozic, Professor of Engineering Management
This course defines the Circular Economy and how it differs from the linear economy. It then highlights the need to move toward a Circular Economy, and how such a transition could take place. This also requires customers going from being “consumers” to “users”, which impacts product design, and therefore challenges existing financial business models. The course concludes with several case studies highlighting companies successfully adopting Circular design practices.
DTSA 5501 Algorithms for Searching, Sorting, and IndexingSpecialization: Foundations of Data Structures and AlgorithmsInstructor: Sriram Sankaranarayanan, Ph.D., Co-Associate Chair for Undergraduate Education, Professor of Computer Science
This course covers basics of algorithm design and analysis, as well as algorithms for sorting arrays, data structures such as priority queues, hash functions, and applications such as Bloom filters.
DTSA 5502 Trees and Graphs: BasicsSpecialization: Foundations of Data Structures and AlgorithmsInstructor: Sriram Sankaranarayanan, Ph.D., Co-Associate Chair for Undergraduate Education, Professor of Computer Science
Basic algorithms on tree data structures, binary search trees, self-balancing trees, graph data structures and basic traversal algorithms on graphs. This course also covers advanced topics such as kd-trees for spatial data and algorithms for spatial data.
DTSA 5503 Dynamic Programming, Greedy AlgorithmsSpecialization: Foundations of Data Structures and AlgorithmsInstructor: Sriram Sankaranarayanan, Ph.D., Co-Associate Chair for Undergraduate Education, Professor of Computer Science
This course covers basic algorithm design techniques such as divide and conquer, dynamic programming, and greedy algorithms. It concludes with a brief introduction to intractability (NP-completeness) and using linear/integer programming solvers for solving optimization problems. Cross listed with CSCA 5414.
DTSA 5001 Probability Theory: Foundation for Data ScienceSpecialization: Data Science Foundations: Statistical InferenceInstructor: Anne Dougherty, Ph.D., Senior Instructor, Associate Department Chair in Applied Mathematics
Probability Theory covers the foundations of probability and its relationship to statistics and data science. Calculate a probability, independent and dependent outcomes, and conditional events. Understand discrete and continuous random variables and see how this fits with data collection. Learn Gaussian (normal) random variables and the Central Limit Theorem and understand it’s fundamental importance for statistics and data science.
DTSA 5002 Statistical Inference for Estimation in Data ScienceSpecialization: Data Science Foundations: Statistical InferenceInstructor: Jem Corcoran, Ph.D., Associate Professor in Applied Mathematics
Introduction to statistical inference, sampling distributions, and confidence intervals. Learn how to define and construct good estimators, method of moments estimation, maximum likelihood estimation, and methods of constructing confidence intervals that will extend to more general settings.
DTSA 5003 Statistical Inference and Hypothesis Testing in Data Science ApplicationsSpecialization: Data Science Foundations: Statistical InferenceInstructor: Jem Corcoran, Ph.D., Associate Professor in Applied Mathematics
This course will focus on theory and implementation of hypothesis testing, especially as it relates to applications in data science. Students will learn to use hypothesis tests to make informed decisions from data. Special attention will be given to the general logic of hypothesis testing, error and error rates, power, simulation, and the correct computation and interpretation of p-values. Attention will also be given to the misuse of testing concepts, especially p-values, and the ethical implications of such misuse.
DTSA 5301 Data Science as a FieldSpecialization: Vital Skills for Data ScienceInstructor: Jane Wall, Ph.D., Instructor of Data Science
This course provides a general introduction to the field of Data Science. It is designed for aspiring data scientists, content experts who work with data scientists, or anyone interested in learning about what Data Science is and what it’s used for. Weekly topics include the past, present, and future of the field; the academic disciplines that both practice and make use of Data Science; collaboration between data scientists and content experts; and the practice of Data Science in the professional world. This course is part of CU Boulder’s Master’s of Science in Data Science and was collaboratively designed by both academics and industry professionals to provide learners with an insider’s perspective on this exciting, evolving, and increasingly vital discipline.
DTSA 5302 Cybersecurity for Data ScienceSpecialization: Vital Skills for Data ScienceInstructor: Al Pisano, Ph.D., Instructor, Computer Science
Cybersecurity for Data Science covers distinctions between confidentiality, integrity, and availability; introduces learners to relevant cybersecurity tools and techniques including cryptographic tools, software resources, and policies that will be essential to data science. Explore key tools and techniques for authentication and access control so producers, curators, and users of data can help ensure the security and privacy of the data.
DTSA 5303 Ethical Issues in Data ScienceSpecialization: Vital Skills for Data ScienceInstructor: Bobby Schnabel, Ph.D., Department External Chair, Professor of Computer Science
This course examines ethical issues related to data science, with the objective of making data science professionals aware of and sensitive to ethical considerations that may arise in their careers. It focuses on ethical frameworks, data science applications that lead to ethical considerations, current media and scholarly articles, and the perspectives and experiences of fellow students and computing professionals.
DTSA 5304 Fundamentals of Data VisualizationSpecialization: Vital Skills for Data ScienceInstructor: Dr. Danielle Albers Szafir, Assistant Professor of Computer Science & Atlas Institute
Data is everywhere. Charts, graphs, and other types of information visualizations help people to make sense of this data. This course explores the design, development, and evaluation of such information visualizations. By combining aspects of design, computer graphics, HCI, and data science, you will gain hands-on experience with creating visualizations, using exploratory tools, and architecting data narratives. Topics include user-centered design, web-based visualization, data cognition and perception, and design evaluation.
DTSA 5504 Data Mining PipelineSpecialization: Data Mining Foundations and PracticeInstructor: Qin (Christine) Lv, Ph.D., Professor of Computer Science
This course introduces the key steps involved in the data mining pipeline, including data understanding, data preprocessing, data warehouse, data modeling, interpretation and evaluation, and real-world applications. Cross listed with CSCA 5502.
DTSA 5505 Data Mining MethodsSpecialization: Data Mining Foundations and PracticeInstructor: Qin (Christine) Lv, Ph.D., Professor of Computer Science
This course covers core techniques used in data mining, including frequent pattern analysis, classification, clustering, outlier detection, as well as time-series mining and graph mining. Cross listed with CSCA 5512.
DTSA 5506 Data Mining ProjectSpecialization: Data Mining Foundations and PracticeInstructor: Qin (Christine) Lv, Ph.D., Professor of Computer Science
This course offers step-by-step guidance and hands-on experience of designing and implementing a real-world data mining project, including problem formulation, literature survey, proposed work, evaluation, discussion and future work. Cross listed with CSCA 5522.
DTSA 5011 Modern Regression Analysis in RSpecialization: Statistical Modeling for Data Science ApplicationsInstructor: Brian Zaharatos, Ph.D., Director, Professional Master's Degree in Applied Mathematics, Interim Faculty Director of Data Science
Modern Regression Analysis in R provides foundational statistical modeling tools for data science. Introduction to methods, theory, and applications of linear statistical models, covering the topics of parameter estimation, residual diagnostics, goodness of fit, and various strategies for variable selection and model comparison. Attention will also be given to the misuse of statistical models and ethical implications of such misuse.
DTSA 5012 ANOVA and Experimental DesignSpecialization: Statistical Modeling for Data Science ApplicationsInstructor: Brian Zaharatos, Ph.D., Director, Professional Master's Degree in Applied Mathematics, Interim Faculty Director of Data Science
Introduction to the analysis of variance (ANOVA), analysis of covariance (ANCOVA), and experimental design. ANOVA and ANCOVA, presented as a type of linear regression model, provide mathematical basis for designing experiments for data science applications. Emphasis placed on important design-related concepts, such as randomization, blocking, factorial design, and causality. Attention will also be given to ethical issues raised in experimentation.
DTSA 5013 Generalized Linear Models and Nonparametric RegressionSpecialization: Statistical Modeling for Data Science ApplicationsInstructor: Brian Zaharatos, Ph.D., Director, Professional Master's Degree in Applied Mathematics, Interim Faculty Director of Data Science
Generalized Linear Models and Nonparametric Regression teaches generalized linear models (GLMs), which provide an introduction to classification (through logistic regression); nonparametric modeling, including kernel estimators, smoothing splines; and semi-parametric generalized additive models (GAMs). Emphasis will be placed on a firm conceptual understanding of these tools. Attention will also be given to ethical issues raised by using complicated statistical models.
DTSA 5509 Introduction to Machine Learning - Supervised LearningSpecialization: Machine Learning: Theory and Hands-on Practice with PythonInstructor: Geena Kim, Instructor
In this course, we will cover the basics of deep learning, such as multilayer perceptron, convolutional neural network, recurrent neural network, how to build and train neural network models, optimization methods, and application examples. Cross listed with CSCA 5622.
DTSA 5510 Unsupervised Algorithms in Machine LearningSpecialization: Machine Learning: Theory and Hands-on Practice with PythonInstructor: Geena Kim, Instructor
In this course, we will learn selected unsupervised learning methods for dimensionality reduction, clustering, finding latent features, and application cases such as recommender systems with hands-on examples of product recommendation algorithms. Cross listed with CSCA 5632.
DTSA 5511 Introduction to Deep LearningSpecialization: Machine Learning: Theory and Hands-on Practice with PythonInstructor: Geena Kim, Instructor
In this course, we will cover the basics of deep learning, such as multilayer perceptron, convolutional neural network, recurrent neural network, how to build and train neural network models, optimization methods, and application examples. Cross listed with CSCA 5642.
DTSA 5733 Relational Database DesignSpecialization: Databases for Data ScientistsInstructor: Di Wu, Data Science
This course will prepare students with the tools needed to design a Relational Database System.
DTSA 5734 The Structured Query Language (SQL)Specialization: Databases for Data ScientistsInstructor: Alan Paradise, Computer Science
In this course students will thoroughly learn the Structured Query Language. Study includes all ANSI standard SQL commands and syntax. Lectures are supplemented with thorough hands-on lab assignments and exercises.
DTSA 5735 Advanced Topics and Future Trends in Database TechnologiesSpecialization: Databases for Data ScientistsInstructor: Di Wu; Alan Paradise, Data Science
The course will have an overview of future trends in databases, including non-relational databases (NoSQL) and Big Data.
DTSA 5701 Introduction to High Performance and Parallel ComputingSpecialization: High Performance and Parallel ComputingInstructor: Thomas Hauser, Ph.D., Associate Professor Adjoint Computer Science & Shelley Knuth, Ph.D., Director of Research Computing
This course introduces the fundamentals of high-performance and parallel computing, and the software skills necessary for work in parallel software environments. These skills include big-data analysis, machine learning, parallel programming, and optimization. It covers the basics of linux environments and bash scripting all the way to high throughput computing and parallelizing code.
DTSA 5704 Managing, Describing, and Analyzing DataSpecialization: Data Science Methods for Quality ImprovementInstructor: Wendy Martin, Instructor, W. Edwards Deming Professor of Management
In this course, you will learn the basics of understanding the data you have and why correctly classifying data is the first step to making correct decisions. You will describe data both graphically and numerically using descriptive statistics and R software. You will learn four probability distributions commonly used in the analysis of data. You will analyze data sets using the appropriate probability distribution. Finally, you will learn the basics of sampling error, sampling distributions, and errors in decision-making.
DTSA 5705 Stability and Capability in Quality ImprovementSpecialization: Data Science Methods for Quality ImprovementInstructor: Wendy Martin, Instructor, W. Edwards Deming Professor of Management
In this course, you will learn to analyze data in terms of process stability and statistical control and why having a stable process is imperative prior to performing statistical hypothesis testing. You will create statistical process control charts for both continuous and discrete data using R software. You will analyze data sets for statistical control using control rules based on probability. Additionally, you will learn how to assess a process with respect to how capable it is of meeting specifications, either internal or external, and make decisions about process improvement.
DTSA 5706 Measurement System AnalysisSpecialization: Data Science Methods for Quality ImprovementInstructor: Wendy Martin, Instructor, W. Edwards Deming Professor of Management
In this course, you will learn to analyze measurement systems for process stability and statistical control and why having a stable measurement process is imperative prior to performing any statistical analysis. You will analyze continuous measurement systems and statistically characterize both accuracy and precision using R software. You will perform measurement systems analysis for potential, short term and long term statistical control and capability.
DTSA 5707 Deep Learning Applications for Computer VisionSpecialization: Deep Learning Applications for Computer VisionInstructor: Ioana Fleming, Ph.D., Co-Associate Chair for Undergraduate Education
In this course, you’ll be learning about Computer Vision as a field of study and research. First we’ll be exploring several Computer Vision tasks and suggested approaches, from the classic Computer Vision perspective. Then we’ll introduce Deep Learning methods and apply them to some of the same problems. We will analyze the results and discuss advantages and drawbacks of both types of methods. Examples of Computer Vision tasks where Deep Learning can be applied include: image classification, image classification with localization, object detection, object segmentation, facial recognition, and activity or pose estimation. Cross listed with CSCA 5812.
DTSA 5842 Effective Communication: Writing, Design and PresentationSpecialization: Effective CommunicationInstructor: William Kuskin, Ph.D., Professor
This course teaches students how to present themselves effectively through writing, design, and presentation. Students will focus on how to write well-organized, clear business documents; to design elegant presentation slides, reports, and posters; and to present and speak with confidence and power. More broadly, the course charts a journey toward each student’s best professional self. This course is a prerequisite for the Effective Communication Capstone.
DTSA 5843 Effective Communication Capstone ProjectSpecialization: Effective CommunicationInstructor: William Kuskin, Ph.D., Professor
In this course students will create a portfolio of work that demonstrates their mastery of writing, design, and presentation skills. The portfolio includes three elements—a memo, a slide deck, and deliver presentation—integrated around a single topic. The capstone allows learners to engage meaningfully in their world by choosing a project relevant to their job. Effective Communication: Writing, Design, and Presentation is a prerequisite for this course.
DTSA 5507 Fundamentals of Software Architecture for Big DataSpecialization: Software Architecture for Big DataInstructor: Tyson Gern, Delivery Lead at VMware Tanzu Labs
The course is intended for individuals looking to understand the basics of software engineering as they relate to building large software systems that leverage big data. They will be introduced to software engineering concepts necessary to build and scale large, data intensive, distributed systems. Starting with software engineering best practices and loosely coupled, highly cohesive data microservices, the course takes you through the evolution of a distributed system over time. Cross listed with CSCA 5008.
DTSA 5508 Software Architecture Patterns for Big DataSpecialization: Software Architecture for Big DataInstructor: Tyson Gern, Delivery Lead at VMware Tanzu Labs
The course is intended for individuals looking to understand the architecture patterns necessary to take large software systems that leverage big data to production. They will transform big data prototypes into high quality tested production software. After measuring the performance characteristics of distributed systems, you will identify trouble areas and implement scalable solutions to improve performance. Upon completion of the course you will know how to scale production datastores to perform under load, designing load tests to ensure applications meet performance requirements. Cross listed with CSCA 5018.
DTSA 5714 Applications of Software Architecture for Big DataSpecialization: Software Architecture for Big DataInstructor: Tyson Gern, Delivery Lead at VMware Tanzu Labs
Intended for individuals who want to build a production-quality software system that leverages big data. Students will apply the basics of software engineering and architecture to create a production-ready distributed system that handles big data. Students will build and scale a large, data intensive, distributed system, composed of loosely coupled, highly cohesive data microservices. Cross listed with CSCA 5028.
DTSA 5020 Regression and ClassificationSpecialization: Statistical Learning for Data ScienceInstructor: James Bird, Instructor, Data Science
Consists of the foundational framework & application of simple and multiple linear regression and classification methods.
DTSA 5021 Resampling, Selection, and SplinesSpecialization: Statistical Learning for Data ScienceInstructor: Osita Onyejekwe, Assistant Teaching Professor, Data Science
Consists of the foundational framework & application of cross-validation, bootstrapping, dimensionality reduction, ridge regression, lasso, GAMs and splines.
DTSA 5022 Trees, SVM, and Unsupervised LearningSpecialization: Statistical Learning for Data ScienceInstructor: Osita Onyejekwe, Assistant Teaching Professor, Data Science
Consists of the foundational framework & application of tree-based methods, support vector machines, and unsupervised learning.
DTSA 5798 Supervised Text Classification for Marketing AnalyticsSpecialization: Text Marketing AnalyticsInstructor: Chris Vargo, Associate Professor | MSBA CMCI Director | Editor - The Agenda Setting Journal
Marketing data often requires categorization, or labeling. In today’s age, marketing data can also be very big, or larger than what humans can reasonably tackle. In this course students will learn how to use supervised deep learning to train algorithms to tackle text classification tasks. Students will walk through a conceptual overview of supervised machine learning, and dive into real-world datasets through instructor-led tutorials in Python. The course will conclude with a major project.
DTSA 5799 Unsupervised Text Classification for Marketing AnalyticsSpecialization: Text Marketing AnalyticsInstructor: Chris Vargo, Associate Professor | MSBA CMCI Director | Editor - The Agenda Setting Journal
Marketing data is often so big that humans cannot read or analyze a representative sample of it to understand what insights might lie within. In this course students will learn how to use unsupervised deep learning to train algorithms to extract topics and insights from text data. Students will walk through a conceptual overview of unsupervised machine learning, and dive into real-world datasets through instructor-led tutorials in Python. The course will conclude with a major project.
DTSA 5800 Network Analysis for Marketing AnalyticsSpecialization: Text Marketing AnalyticsInstructor: Chris Vargo, Associate Professor | MSBA CMCI Director | Editor - The Agenda Setting Journal
Network analysis is a long-standing methodology used to understand the relationships between words and actors in the broader networks in which they exist. This course will cover network analysis at it pertains to marketing data, specifically text datasets and social networks. Students will walk through a conceptual overview of network analysis, and dive into real-world datasets through instructor-led tutorials in Python. The course will conclude with a major project.
DTSA 5747 Fundamentals of Natural Language ProcessingSpecialization: Natural Language ProcessingInstructor: James Martin, Ph.D., Professor in Computer Science
DTSA 5748 Deep Learning for Natural Language ProcessingSpecialization: Natural Language ProcessingInstructor: James Martin; Katharina Kann
DTSA 5736 When to Regulate? The Digital Divide and Net NeutralitySpecialization: Internet PolicyInstructor: David Reed, Scholar in Residence
This course builds an interdisciplinary policy framework to critique and develop regulatory approaches to real-world problems on the Internet. Learners then use the framework to develop a definition of broadband to improve the Digital Divide and to evaluate net neutrality regulations. Cross listed with CSCA 5433.
CSCA 5312 Basic Robotic Behaviors and OdometrySpecialization: Introduction to Robotics with WebotsInstructor: Nikolaus Correll, Ph.D., Professor of Computer Science
Introduction to autonomous mobile robots, including forward kinematics (“odometry”), basic sensors and actuator, and simple reactive behavior. The course is centered around two laboratory exercises in the realistic, physics-based simulator “Webots” in which students will experiment with simple reactive behaviors for collision avoidance and line following, state machines, and basic forward kinematics of non-holonomic systems. An overarching objective of this course is to understand the role of the physical system on algorithm design and its role as source of uncertainty that makes robots non-deterministic.
CSCA 5332 Robotic Mapping and Trajectory GenerationSpecialization: Introduction to Robotics with WebotsInstructor: Nikolaus Correll, Ph.D., Professor of Computer Science
Building upon the course “Basic Robotic Behaviors and Odometry”, students will learn how to perform basic inverse kinematics of (non-)holonomic systems using a feedback control approach and how to process multi-dimensional sensor signals such as laser range scanners to create discrete representations of the environment (mapping). Also in this course, the overarching focus is mechanisms and sensors as sources of uncertainty and techniques to model and control for them.
CSCA 5342 Robotic Path Planning and Task ExecutionSpecialization: Introduction to Robotics with WebotsInstructor: Nikolaus Correll, Ph.D., Professor of Computer Science
Building upon the courses “Basic Robotic Behaviors and Odometry” and “Robotic Mapping and Trajectory Generation”, students will learn how implement high-level reasoning for generating trajectories (path planning) and sequencing tasks under uncertainty of sensing and actuation. As a first cap stone in the robotics specialization, this course will also lead toward the implementation of a complex mobile manipulation system, combining behaviors, sensing, control and planning developed in previous modules.
CSCA 5702 Fundamentals of Data VisualizationSpecialization: Fundamentals of Data VisualizationInstructor: Danielle Szafir, Ph.D., Assistant Professor of Computer Science
Fundamentals of Visualization explores the design, development, and evaluation of information visualizations. Combine aspects of design, computer graphics, HCI, and data science, to gain hands-on experience with creating visualizations, using exploratory tools, and architecting data narratives. Topics include user-centered design, web-based visualization, data cognition and perception, and design evaluation. Cross listed with DTSA 5304.
DTSA 5740 Global Climate Change Policies and AnalysisSpecialization: Modeling and Predicting Climate AnomaliesInstructor: Osita Onyejekwe, Assistant Teaching Professor
This course explores and critically analyzes historical and contemporary climate policies (e.g. Kyoto Protocol and the Paris Agreement). Political issues pertaining to energy sources, such as nuclear energy, will be reviewed. The course will focus on understanding key climate principles and terms surrounding policy development, specifically for low-income or developing countries/communities. This course also introduces the Python programming language.
DTSA 5741 Modeling Climate Anomalies with Multivariate RegressionSpecialization: Modeling and Predicting Climate AnomaliesInstructor: Osita Onyejekwe, Assistant Teaching Professor
This course introduces the use of statistical analysis in Python programming to study and model climate data, specifically with the Tidyverse package. Topics include data visualization, predictive model development, simple linear regression, multivariate linear regression, multivariate linear regression with interaction, and logistic regression. Strong emphasis will be placed on gathering and analyzing climate data with the Python programming language.
DTSA 5742 Predicting Extreme Climate Behavior with Machine LearningSpecialization: Modeling and Predicting Climate AnomaliesInstructor: Osita Onyejekwe, Assistant Teaching Professor
This course reviews current global climate policies with the goal of gathering data and applying machine learning algorithms to predict extreme climate behaviors, specifically in developing countries. Topics include simple linear regression, multivariate linear regression, time-series analysis, and numerical weather prediction. The use of Monte Carlo simulations to forecast extreme weather events will be analyzed. Strong emphasis will be placed on application in the Python programming language.
DTSA 5726 Introduction to Bayesian Statistics for Data Science ApplicationsSpecialization: Bayesian Statistics for Data ScienceInstructor: Brian Zaharatos, Ph.D., Interim Faculty Director of Data Science, Director of Professional Master's Degree in Applied Mathematics
This course introduces the theoretical, philosophical, and mathematical foundations of Bayesian Statistical inference. Students will learn to apply this foundational knowledge to real-world data science problems. Topics include the use and interpretations of probability theory in Bayesian inference; Bayes’ theorem for statistical parameters; conjugate, improper, and objective priors distributions; data science applications of Bayesian inference; and ethical implications of Bayesian statistics.
ECEA 5605 Light Emitting Diodes and Semiconductor LasersSpecialization: 1st course in Active Optical DevicesInstructor: Juliet Gopinath, Ph.D., Associate Professor
Syllabus for Light Emitting Diodes and Semiconductor Lasers Opens in new window
You will learn about semiconductor light-emitting diodes (LEDs) and lasers, and the important rules for their analysis, planning, design, and implementation. You will also apply your knowledge through challenging homework problem sets to cement your understanding of the material and prepare you to apply in your career.
ECEA 5606 Nanophotonics and DetectorsSpecialization: 2nd course in Active Optical DevicesInstructor: Juliet Gopinath, Ph.D., Associate Professor
Syllabus for Nanophotonics and Detectors opens in new window
This course dives into nanophotonic light-emitting devices and optical detectors, including metal semiconductors, metal-semiconductor insulators, and pn junctions. We will also cover photoconductors, avalanche photodiodes, and photomultiplier tubes. Weekly homework problem sets will challenge you to apply the principles of analysis and design we cover in preparation for real-world problems.
ECEA 5607 DisplaysSpecialization: 3rd course in Active Optical DevicesInstructor: Juliet Gopinath, Ph.D., Associate Professor
Syllabus for Displays Opens in new window
The course will dive deep into electronic display devices, including liquid crystals, electroluminescent, plasma, organic light-emitting diodes, and electrowetting based displays. You'll learn about various design principles, affordances, and liabilities, and also a variety of applications in the real world of professional optics.
ECEA 5730 Introduction to Battery Management SystemsSpecialization: 1st course in Algorithms for Battery Management SystemsInstructor: Gregory Plett, Ph.D., Professor
Syllabus for Introduction to Battery Management Systems opens in new window
This course will provide you with a firm foundation in lithium-ion cell terminology and function and in battery-management-system requirements as needed by the remainder of the specialization.
ECEA 5731 Equivalent Circuit Cell Model SimulationSpecialization: 2nd course in Algorithms for Battery Management SystemsInstructor: Gregory Plett, Ph.D., Professor
Syllabus for Equivalent Circuit Cell Model Simulation opens in new window
In this course, you will learn the purpose of each component in an equivalent-circuit model of a lithium-ion battery cell, how to determine their parameter values from lab-test data, and how to use them to simulate cell behaviors under different load profiles.
ECEA 5732 Battery State-of-Charge (SOC) EstimationSpecialization: 3rd course in Algorithms for Battery Management SystemsInstructor: Gregory Plett, Ph.D., Professor
Syllabus for Battery State-of-Charge (SOC) Estimation opens in new window
In this course, you will learn how to implement different state-of-charge estimation methods and to evaluate their relative merits
ECEA 5733 Battery State-of-Health (SOH) EstimationSpecialization: 4th course in Algorithms for Battery Management SystemsInstructor: Gregory Plett, Ph.D., Professor
Syllabus for Battery State-of-Health (SOH) Estimation opens in new window
In this course, you will learn how to implement different state-of-health estimation methods and to evaluate their relative merits.
ECEA 5734 Battery Pack Balancing and Power EstimationSpecialization: 5th course in Algorithms for Battery Management SystemsInstructor: Gregory Plett, Ph.D., Professor
Syllabus for Battery Pack Balancing and Power Estimation opens in new window
In this course, you will learn how to design balancing systems and to compute remaining energy and available power for a battery pack.
ECEA 5385 Industrial IoT Markets and SecuritySpecialization: 1st course in Developing Industrial Internet of ThingsInstructor: David Sluiter, BSEE, Lecturer
Syllabus for Industrial IoT Markets and Security Opens in new window
This course goes beyond the hype of consumer IoT to emphasize a much greater space for potential embedded system applications and growth: The Industrial Internet of Things (IIoT), also known as Industry 4.0. Part of the Industrial Internet of Things MasterTrack® Certificate.
ECEA 5386 Project Planning and Machine LearningSpecialization: 2nd course in Developing Industrial Internet of ThingsInstructor: David Sluiter, BSEE, Lecturer
Syllabus for Project Planning and Machine Learning Opens in new window
Part 2 of the Developing Industrial Internet of Things specialization. You will learn how to staff, plan and execute a project, calibrate sensors, file system operation, and an introduction to big data and machine learning algorithms. Part of the Industrial Internet of Things MasterTrack® Certificate.
ECEA 5387 Modeling and Debugging Embedded SystemsSpecialization: 3rd course in Developing Industrial Internet of ThingsInstructor: David Sluiter, BSEE, Lecturer
Syllabus for Modeling and Debugging Embedded Systems Opens in new window
Part 3 of the Developing Industrial Internet of Things specialization. You will learn about modeling cyber-physical systems, the Automotive and Transportation market segment, and what can be learned from studying engineering failures. Part of the Industrial Internet of Things MasterTrack® Certificate.
ECEA 5346 User Experience Design for Embedded SystemsSpecialization: 1st course in Embedded Interface DesignInstructor: Bruce Montgomery, Ph.D., Senior Instructor
Syllabus for User Experience Interface Design for Embedded Systems Opens in new window
ECEA 5347 Rapid Prototyping of Embedded Interface DesignsSpecialization: 2nd course in Embedded Interface Design Instructor: Bruce Montgomery, Ph.D., Senior Instructor
Syllabus for Rapid Prototyping of Embedded Interface Designs Opens in new window
This is the second of three courses in the Embedded Interface Design (EID) specialization. This course is an introduction to rapid prototyping concepts, platforms, software, and design perspectives that can be applied to embedded devices and systems. The class looks at key considerations for rapid prototyping, product realization, and wireless designs. It then looks at tools and methods for embedded user interfaces for prototypes and products.
Development of embedded device prototypes also includes a review of platforms, operating systems, and other tools. The class closes with a review of various design perspectives for connected embedded devices and systems, including wearables and voice user interfaces. Includes practical programming exercises using key tools such as Qt, HTML, and Python. Part of the Industrial Internet of Things MasterTrack® Certificate.
ECEA 5348 M2M and IoT Interface Design and ProtocolsSpecialization: 3rd course in Embedded Interface DesignInstructor: Bruce Montgomery, Ph.D., Senior Instructor
Syllabus for M2M and IoT Interface Design and Protocols Opens in new window
This course is focused on connecting devices to each other and to the cloud to create prototypes and actual systems that flow data from devices to consumers. The class includes an introduction to M2M (Machine-to-Machine) and IoT (Internet of Things) concepts, using the cloud to develop IoT systems (specifically AWS (Amazon Web Services) and its IoT framework), a review of common communications protocols at every level of connected devices, and other IoT design concerns such as security, message queuing approaches, and the use and design of APIs and microservices.The content ranges from general design best practices to specifics for select tools and methods, but all are presented to support developing embedded devices in IoT applications. The class includes practical projects that let you try some of standard methods in software development of prototype graphical user interfaces for devices using AWS, Python, and optionally Node.JS. Part of the Industrial Internet of Things MasterTrack® Certificate.
ECEA 5340 Sensor and Sensor Circuit DesignSpecialization: 1st course in Embedding Sensors and MotorsInstructors: Jay Mendelson, MSME, Lecturer & James Zweighaft, MSME
Syllabus for Sensor and Sensor Circuit Design Opens in new window
You will need to buy the following components to do the two course projects based on the videos in this module. Note that if you have already purchased the PSOC 5LP PROTOTYPING KIT, you do not need to buy it again. These parts may be purchased off the Digikey web site, www. Digikey.com. Or, you may obtain the specs from the site, and purchase them elsewhere. These are the part numbers typed out, so you can copy and paste them into the Digikey web site. You will need one of each part. 428-3390-ND NHD-0216BZ-RN-YBW-ND 570-1229-ND
Additional parts needed: Wire, Breadboard, ESM Electronic Parts List_FLAT BOM.xlsx, nScope oscilloscope, Note: If the oscilloscope is still not available on Amazon, fill out the nScope request form to buy them now. Part of the Industrial Internet of Things MasterTrack® Certificate.
ECEA 5341 Motors and Motor Control CircuitsSpecialization: 2nd course in Embedding Sensors and MotorsInstructors: Jay Mendelson, MSME, Lecturer & James Zweighaft, MSME
Syllabus for Motor and Motor Control Circuits Opens in new window
This is our second course in our specialization on Embedding Sensor and Motors. To get the most out of this course, you should first take our first course entitled Sensors and Sensor Circuits. Our first course gives you a tutorial on how to use the hardware and software development kit we have chosen for the lab exercises. This second course assumes that you already know how to use the kit.
You will need to buy the following components to do the two course projects based on the videos in this module. Note that if you have already purchased the PSOC 5LP PROTOTYPING KIT, you do not need to buy it again. These parts may be purchased off the Digikey web site, www. Digikey.com. Or, you may obtain the specs from the site, and purchase them elsewhere. These are the part numbers for the above table, the lab on Motor Voltage and Current Measurement. You can copy and paste them into the search engine on the Digikey web site. You need one of each except for the AA batteries (N107-ND), which you would need 3. 428-3390-ND P14355-ND FQU13N10LTU-ND N107-ND 1N5393-E3/54GICT-ND RNF14FTD1K00CT-ND P0.62W-1BK-ND These are the part numbers for the above table, so you can copy and paste them into the search engine on the Digikey web site. You will need one of each. 428-3390-ND 987-1188-ND Part of the Industrial Internet of Things MasterTrack® Certificate.
ECEA 5342 Pressure, Force, Motion, and Humidity SensorsSpecialization: 3rd course in Embedding Sensors and MotorsInstructors: Jay Mendelson, MSME, Lecturer & James Zweighaft, MSME
Syllabus for Pressure, Force, Motion, and Humidity Sensors Opens in new window
In this course you will build the circuit from Video 7 (Lab Exercise on strain gauges), Module 2 (Force and Strain Sensors and Touch Screens), and use it to make screen shots of the timing of the switch. If you haven't already wired up the system and written all the software per the instructions of Video 7, please do so now.
You will need to buy the following components to complete this assignment. Note that if you have already purchased the PSOC 5LP PROTOTYPING KIT, you do not need to buy it again. These parts may be purchased off the Digikey web site, www. Digikey.com Or, you may obtain the specs from the site, and purchase them elsewhere. These are the part numbers for the below table, the lab on strain gauges. You can copy and paste them into the search engine on the Digikey website. You need one of each except for the AA batteries (N107-ND), which you would need 3. 428-3390-ND (PSOC 5LP PROTOTYPING KIT) CF14JT22K0CT-ND CF14JT100KCT-ND Part of the Industrial Internet of Things MasterTrack® Certificate.
ECEA 5343 Sensor Manufacturing and Process ControlSpecialization: 4th course in Embedding Sensors and Motors (Pathway)Instructors: Jay Mendelson, MSME, Lecturer & James Zweighaft, MSME
Syllabus for Sensor Manufacturing and Process Control Opens in new window
This is our fourth course in our specialization on Embedding Sensor and Motors. To get the most out of this course, you should first take our first course entitled "Sensors and Sensor Circuits", our second course entitled "Motor and Motor Control Circuits", and our third course entitled "Pressure, Force, Motion, and Humidity Sensors".
ECEA 5360 Introduction to FPGA Design for Embedded SystemsSpecialization:1st course in FPGA Design for Embedded SystemsInstructor: Timothy Scherr, MSEE, Senior Instructor
Syllabus for Introduction to FPGA Design for Embedded Systems opens in new window
This course will give you the foundation for FPGA design in Embedded Systems. You will learn what an FPGA is and how this technology was developed, how to select the best FPGA architecture for a given application, how to use state of the art software tools for FPGA development and solve critical digital design problems using FPGAs. If you are thinking of a career in Electronics Design or looking at a career change, this is a great course to enhance your career opportunities.
Hardware Requirements
You must have access to computer resources to run the development tools, a PC running either Windows 7, 8, or 10 or a recent Linux OS which must be RHEL 6.5 or CentOS Linux 6.5 or later. Either Linux OS could be run as a virtual machine under Windows 8 or 10. Whatever the OS, the computer must have at least 8 GB of RAM. Most new laptops will have this, older ones may be upgraded. A target FPGA development board, while helpful, is NOT required for this course.
Please click on Syllabus for more hardware requirements and suggested development kits.
ECEA 5361 Hardware Description Languages for FPGA DesignSpecialization: 2nd course in FPGA Design for Embedded Systems (Pathway)Instructors: Timothy Scherr, MSEE, Senior Instructor & Benjamin Spriggs, MBA, MSEE, Lecturer
Syllabus for Hardware Description Languages for FPGA Design Opens in new window
This course will give you the foundation for using Hardware Description Languages, specifically VHDL and Verilog for Logic Design. You will learn the history of both VHDL and Verilog and how to use them for design entry and verification with FPGAs and ASICs. You will use current HDL software tools for FPGA development, and practice with several programming examples that will give you proficiency with the languages. If you are thinking of a career in Electronics Design or looking at a career change, this is a great course to enhance your career opportunities. You must have access to computer resources to run the development tools, a PC running either Windows 7, 8, or 10 or a recent Linux OS which must be RHEL 6.5 or CentOS Linux 6.5 or later. Either Linux OS could be run as a virtual machine under Windows 8 or 10. Whatever the OS, the computer must have at least 8 GB of RAM. Most new laptops will have this, older ones may be upgraded. The DE10-lite will be used as target board in this course.” Please click on Syllabus for more hardware requirements and suggested development kits.
ECEA 5362 FPGA Softcore Processors and IP AcquisitionSpecialization: 3rd course in FPGA Design for Embedded Systems (Pathway)Instructors: Timothy Scherr, MSEE, Senior Instructor & Benjamin Spriggs, MBA, MSEE, Lecturer
Syllabus for FPGA Softcore Processors and IP Acquisition Opens in new window
The objective of this course is to learn how to develop, program, and use Softcore Processors with associated IP integration. To accomplish this, the Nios II Softcore Processor from Intel Altera is developed as an example design. The development flow is explained including both hardware and software development. Hardware is designed using the Qsys system design tool. Software is developed using an Eclipse-based IDE and Board Support Package Editor. One advantage of Softcore Processors is the ability to add a custom instruction, and this is demonstrated building it in hardware and using it in software. The range of IP available for various FPGA vendors is presented, along with the use of simulation to verify the designs. You must have access to computer resources to run the development tools, a PC running either Windows 7, 8, or 10 or a recent Linux OS which must be RHEL 6.5 or CentOS Linux 6.5 or later. Either Linux OS could be run as a virtual machine under Windows 8 or 10. Whatever the OS, the computer must have at least 8 GB of RAM. Most new laptops will have this, older ones may be upgraded. The DE10-lite will be used as target board in this course. Please click on Syllabus for more hardware requirements and suggested development kits.
ECEA 5363 Building FPGA ProjectsSpecialization: 4th course in FPGA Design for Embedded Systems (Pathway)Instructor: Timothy Scherr, MSEE, Senior Instructor
Syllabus for Building FPGA Projects Opens in new window
The objective of this course is provide a platform to get hands-on experience designing FPGA circuits and systems. To this end the DE10-Lite from TerAsic featuring the Intel Altera MAX10 FPGA is employed. The student will use this development kit to do a series of projects culminating in the construction of hardware and software for a System on a Chip (SoC) with the Nios II Soft Processor. All the prior lessons in this series of courses will be reinforced by the experience of building and testing real systems in the FPGA. DE10-Lite Evaluation Board using the MAX 10 by Terasic Inc. You must have access to computer resources to run the development tools, a PC running either Windows 7, 8, or 10 or a recent Linux OS which must be RHEL 6.5 or CentOS Linux 6.5 or later. Either Linux OS could be run as a virtual machine under Windows 8 or 10. Whatever the OS, the computer must have at least 8 GB of RAM. Most new laptops will have this, older ones may be upgraded
ECEA 5705 Averaged Switch Modeling and SimulationSpecialization: 1st course in the Modeling and Control of Power ElectronicsInstructor: Dragan Maksimovic, Ph.D., Professor
Syllabus for Averaged Switch Modeling and Simulation opens in new window
The course is focused on practical design-oriented modeling and control of pulse-width modulated switched mode power converters using analytical and simulation tools in time and frequency domains. A design-oriented analysis technique known as the Middlebrook's feedback theorem is introduced and applied to analysis and design of voltage regulators and other feedback circuits. Furthermore, it is shown how circuit averaging and averaged-switch modeling techniques lead to converter averaged models suitable for hand analysis, computer-aided analysis, and simulations of converters. After completion of this course, the student will be able to practice design of high-performance control loops around switched-mode power converters using analytical and simulation techniques. Assignments include section quizzes, open-ended design problem, and a final exam. The course is a prerequisite for Courses #2-#5 in the Modeling and Control of Power Electronics specialization.
ECEA 5706 Techniques of Design-Oriented AnalysisSpecialization: 2nd course in the Modeling and Control of Power ElectronicsInstructor: Dragan Maksimovic, Ph.D., Professor
Syllabus for Techniques of Design-Oriented Analysis opens in new window
After completion of this course, you will gain advanced analytical skills that will enable you to quickly gain insights into converter models and translate these insights into converter designs.
ECEA 5707 Input Filter DesignSpecialization: 3rd course in the Modeling and Control of Power ElectronicsInstructor: Dragan Maksimovic, Ph.D., Professor
Syllabus for Input Filter Design opens in new window
Gain an understanding of issues related to electromagnetic interference (EMI) and electromagnetic compatibility (EMC). Understand the need for input filters and the effects input filters may have on converter responses. Design properly damped single and multi-section filters to meet the conducted EMI attenuation requirements without compromising frequency responses or stability of closed-loop controlled power converters.
ECEA 5708 Current Mode ControlSpecialization: 4th course in the Modeling and Control of Power ElectronicsInstructor: Dragan Maksimovic, Ph.D., Professor
Syllabus for Current Mode Control Opens in new window
The course is focused on current-mode control techniques, which are very frequently applied in practical realizations of switched-mode. Upon completion of the course, you will be able to understand, analyze, model, and design current-mode controllers for dc-dc power converters, including peak current-mode controllers and average current-mode controllers.
ECEA 5709 Modeling and Control of Single-Phase Rectifiers and InvertersSpecialization: 5th course in the Modeling and Control of Power ElectronicsInstructor: Dragan Maksimovic, Ph.D., Professor
Syllabus for Modeling and Control of Single-Phase Rectifiers and Inverters Opens in new window
The course consists of three weeks of materials and is focused on modeling and control of grid-tied power electronics. Upon completion of the course, you will be able to understand, analyze, model, and design low-harmonic rectifiers and inverters interfacing dc loads or dc power sources, such as photovoltaic arrays, to the single-phase ac power grid.
ECEA 5600 First Order Optical System DesignSpecialization: 1st course in Optical EngineeringInstructor: Robert McLeod, Ph.D., Professor
Syllabus for First Order Optical System Design Opens in new window
Optical instruments are how we see the world, from corrective eyewear to medical endoscopes to cell phone cameras to orbiting telescopes. When you finish this course, you will be able to design to first order such optical systems with simple mathematical and graphical techniques, develop the foundation needed to begin all optical design as well as the intuition needed to quickly address the feasibility of complicated designs during brainstorming meetings, and enter these designs into an industry-standard design tool, OpticStudio by Zemax, to analyze and improve performance with powerful automatic optimization methods.
ECEA 5601 Optical Efficiency and ResolutionSpecialization: 2nd course in Optical EngineeringInstructors: Robert McLeod, Ph.D., Professor
Syllabus for Optical Efficiency and Resolution Opens in new window
Optical instruments are how we see the world, from corrective eyewear to medical endoscopes to cell phone cameras to orbiting telescopes. This course will teach you how to design such optical systems with simple mathematical and graphical techniques. The first order optical system design covered in the previous course is useful for the initial design of an optical imaging system but does not predict the energy and resolution of the system. This course discusses the propagation of intensity for Gaussian beams and incoherent sources. It also introduces the mathematical background required to design an optical system with the required field of view and resolution. You will also learn how to analyze these characteristics of your optical system using an industry-standard design tool, OpticStudio by Zemax.
ECEA 5602 Design of High-Performance Optical SystemsSpecialization: 3rd course in Optical EngineeringInstructors: Robert McLeod, Ph.D., Professor
Syllabus for Design of High-Performance Optical Systems opens in new window
Optical instruments are how we see the world, from corrective eyewear to medical endoscopes to cell phone cameras to orbiting telescopes. This course extends what you have learned about first-order, paraxial system design and optical resolution and efficiency with the introduction to real lenses and their imperfections. We begin with a description of how different wavelengths propagate through systems, then move on to aberrations that appear with high angle, non-paraxial systems and how to correct for those problems. The course wraps up with a discussion of optical components beyond lenses and an excellent example of a high-performance optical system – the human eye. The mathematical tools required for analysis of high-performance systems are complicated enough that this course will rely more heavily on OpticStudio by Zemax. This will allow students to analyze systems that are too complicated for the simple analysis thus far introduced in this set of courses.
ECEA 5700 Introduction to Power ElectronicsSpecialization: 1st course in Power ElectronicsInstructor: Robert Erickson, Ph.D., Professor
Syllabus for Introduction to Power Electronics opens in new window
This course introduces the basic concepts of switched-mode converter circuits for controlling and converting electrical power with high efficiency. Principles of converter circuit analysis are introduced and are developed for finding the steady-state voltages, current, and efficiency of power converters. Assignments include simulation of a dc-dc converter, analysis of an inverting dc-dc converter, and modeling and efficiency analysis of an electric vehicle system and of a USB power regulator. Prior knowledge needed: A basic understanding of electrical circuit analysis, introduction to Circuits and Electronics (Basic Electronics), Linear Circuits, Microelectronics and Circuits as Systems. Part of the Power Electronics MasterTrack® Certificate.
ECEA 5701 Converter CircuitsSpecialization: 2nd course in Power ElectronicsInstructor: Robert Erickson, Ph.D., Professor
Syllabus for Converter Circuits Opens in new window
This course introduces more advanced concepts of switched-mode converter circuits. Realization of the power semiconductors in inverters or in converters having bidirectional power flow is explained. Power diodes, power MOSFETs, and IGBTs are explained, along with the origins of their switching times. Equivalent circuit models are refined to include the effects of switching loss. The discontinuous conduction mode is described and analyzed. A number of well-known converter circuit topologies are explored, including those with transformer isolation. The homework assignments include a boost converter and an H-bridge inverter used in a grid-interfaced solar inverter system, as well as transformer-isolated forward and flyback converters. Part of the Power Electronics MasterTrack® Certificate.
Completion of the first course Introduction to Power Electronics is the assumed prerequisite for this course.
ECEA 5702 Converter ControlSpecialization: 3rd course in Power ElectronicsInstructor: Robert Erickson, Ph.D., Professor
Syllabus for Converter Control Opens in new window
This course teaches how to design a feedback system to control a switching converter. The equivalent circuit models derived in the previous courses are extended to model small-signal ac variations. These models are then solved, to find the important transfer functions of the converter and its regulator system. Finally, the feedback loop is modeled, analyzed, and designed to meet requirements such as output regulation, bandwidth and transient response, and rejection of disturbances. Part of the Power Electronics MasterTrack® Certificate.
This course assumes prior completion of courses Introduction to Power Electronics and Converter Circuits.
ECEA 5703 Magnetics Design for Power ConvertersSpecialization: 4th course in Power ElectronicsInstructor: Robert Erickson, Ph.D., Professor
Syllabus for Magnetics Design for Power Converters opens in new window
This course covers the analysis and design of magnetic components, including inductors and transformers, used in power electronic converters. This course assumes prior completion of ECEA 5700: Introduction to Power Electronics and ECEA 5701: Converter Circuits.
Prior knowledge needed: Able to understand functioning of different Power electronics converters n both DCM and CCM, able to solve and understand complex mathematical equations, have a good understanding of RMS, average quantities and Dutyratio, and familiarity with Maxwell’s equations. Part of the Power Electronics MasterTrack® Certificate.
ECEA 5715 Capstone Design Project in Power ElectronicsSpecialization: Power Electronics CapstoneInstructors: Robert Erickson, Ph.D., Professor & Dragan Maksimovic, Ph.D., Professor
Syllabus for Capstone Design Project in Power Electronics opens in new window
This course assumes the student has prerequisite knowledge in the specialization on power electronics (ECEA 5700, 5701, 5702, and 5703) and the specialization on modeling and control of power electronics (ECEA 5705, 5706, 5707, 5708, and 5709).
ECEA 5315 Concepts and PracticesSpecialization: 1st course in Real-time Embedded SystemsInstructor: Sam Siewert, Ph.D., Associate Professor Adjunct
Syllabus for Concepts and Practices opens in new window
In this course, students will design and build a microprocessor-based embedded system application using a real-time operating system or RT POSIX extensions with Embedded Linux. The course focus is on the process as well as fundamentals of integrating microprocessor-based embedded system elements for digital command and control of typical embedded hardware systems.
ECEA 5316 Theory and AnalysisSpecialization: 2nd course in Real-time Embedded SystemsInstructor: Sam Siewert, Ph.D., Associate Professor Adjunct
Syllabus for Theory and Analysis opens in new window
This course provides an in-depth and full mathematical derivation and review of models for scheduling policies and feasibility determination by hand and with rate monotonic tools along with comparison to actual performance for real-time scheduled threads running on a native Linux system.
ECEA 5317 Mission-Critical Software ApplicationsSpecialization: 3rd course in Real-time Embedded SystemsInstructor: Sam Siewert, Ph.D., Associate Professor Adjunct
Syllabus for Mission-Critical Software Applications opens in new window
Upon completion of this course, the learner will know the difference between systems you can bet your life on (mission critical) and those which provide predictable response and quality of service (reliable). This will be achieved not only by study of design methods and patterns for mission critical systems, but also through implementation of soft real-time systems and comparison to hard real-time.
ECEA 5318 Real-time Embedded Systems ProjectSpecialization: 4th course in Real-time Embedded SystemsInstructor: Sam Siewert, Ph.D., Associate Professor Adjunct
Syllabus for Real-time Embedded Systems Project opens in new window
In this course, students will design and build a microprocessor-based embedded system project managing real-time constraints while analyzing the system in-order to meet them. Students are expected to do a project capturing the images from a camera connected to raspberry pi at 1 Hz and 10 Hz frequency while storing them in the memory. Various problems encountered while designing the system and its proper documentation is expected from the students.
ECEA 5630 Semiconductor PhysicsSpecialization: 1st course in Semiconductor DevicesInstructors: Wounjhang Park, Ph.D., Professor
Syllabus for Semiconductor Physics opens in new window
This course introduces basic concepts of the quantum theory of solids and presents the theory describing the carrier behaviors in semiconductors. The course balances fundamental physics with application to semiconductors and other electronic devices. Prior knowledge needed: Introductory physics including electromagnetics and modern physics and Introductory calculus and ordinary differential equations
ECEA 5631 Diode: pn Junction and Metal Semiconductor ContactSpecialization: 2nd course in Semiconductor DevicesInstructors: Wounjhang Park, Ph.D., Professor
Syllabus for Diode: pn Junction and Metal Semiconductor Contact opens in new window
This course presents in-depth discussion and analysis of pn junction and metal-semiconductor contacts including equilibrium behavior, current and capacitance responses under bias, breakdown, non-rectifying behavior, and surface effect. You'll work through sophisticated analysis and application to electronic devices.
ECEA 5632 Transistor: Field Effect and Bipolar JunctionSpecialization: 3rd course in Semiconductor DevicesInstructors: Wounjhang Park, Ph.D., Professor
Syllabus for Transistor: Field Effect and Bipolar Junction opens in new window
This course presents in-depth discussion and analysis of metal-oxide-semiconductor field effect transistors (MOSFETs) and bipolar junction transistors (BJTs) including the equilibrium characteristics, modes of operation, switching and current amplifying behaviors.
ECEA 5716 Open-Loop Photovoltaic Power Electronics LaboratorySpecialization: 1st course in the Photovoltaic Power ElectronicsInstructors: Robert Erickson, Ph.D., Professor
Syllabus for Open-Loop Photovoltaic Power Electronics Laboratory opens in new window
This course requires purchase of a parts kit in order to complete assignments. The kit will be used from the first experiment in the 2nd week of class and throughout the course and the following 2 courses of the specialization. Please allow adequate time to receive the kit. It is highly suggested that you receive the parts kit by the end of the first week of the session. This is a 100% distance course in which students design, construct, and demonstrate an actual hardware stand-alone solar power system at home or other distance location.
ECEA 5717 Closed-Loop Photovoltaic Power Electronics LaboratorySpecialization: 2nd course in the Photovoltaic Power Electronics Instructors: Robert Erickson, Ph.D., Professor
Syllabus for Closed-Loop Photovoltaic Power Electronics Laboratory opens in new window
This course requires purchase of a parts kit in order to complete assignments. Please allow adequate time to receive the kit. It is highly suggested that you receive the parts kit by the end of the first week of the session. This is a 100% distance course in which students design, construct, and demonstrate a stand-alone solar power system at home.
ECEA 5718 Photovoltaic Power Electronics Battery Management LaboratorySpecialization: 3rd course in the Photovoltaic Power Electronics Instructors: Robert Erickson, Ph.D., Professor
Syllabus for Photovoltaic Power Electronics Battery Management Laboratory opens in new window
Design, construct, and demonstrate a battery management system in which the power electronics system developed in the earlier courses is adapted to control charging of the storage battery. The project includes maximum power point tracking (MPPT) to provide bulk charging at the maximum rate, and charge taper and float modes to improve battery health. Note: The parts kit and test equipment kit for this course are the same as in the prerequisite open-loop (ECEA 5716) and closed-loop (ECEA 5717) power electronics lab courses, so no further purchases are required.
ECEA 5610 Foundations of Quantum MechanicsSpecialization: 1st course in the Quantum Mechanics for EngineersInstructors: Wounjhang Park, Ph.D., Professor
Syllabus for Foundations of Quantum Mechanics opens in new window
This course covers the fundamental concepts and topics of quantum mechanics which include basic concepts, 1D potential problems, time evolution of quantum states, and essential linear algebra. It provides undergraduate level foundational knowledge and builds on them to explore more advanced topics.
ECEA 5611 Theory of Angular MomentumSpecialization: 2nd course in the Quantum Mechanics for EngineersInstructors: Wounjhang Park, Ph.D., Professor
Syllabus for Theory of Angular Momentum opens in new window
This course introduces the quantum mechanical concept of angular momentum operator and its relationship with rotation operator. It then presents the angular momentum operators, their eigenvalues and eigenfunctions. Finally, it covers the theory of angular momentum addition.
ECEA 5612 Approximation MethodsSpecialization: 3rd course in the Quantum Mechanics for EngineersInstructors: Wounjhang Park, Ph.D., Professor
Syllabus for Approximation Methods opens in new window
This course teaches commonly used approximation methods in quantum mechanics. They include time-independent perturbation theory, time-dependent perturbation theory, tight binding method, variational method and the use of finite basis set. In each case, a specific example is given to clearly show how the method works.
ECEA 5721 Introduction to Power SwitchesSpecialization: 1st course in the Power Semiconductor DevicesInstructors: Bart Van Zeghbroeck, Ph.D., Professor
Syllabus for Introduction to Power Switches opens in new window
Power Semiconductor devices that are commonly used in power electronic circuits. Starting with the circuit models of these devices, we will identify the requirements leading to low loss circuits and learn how these can be simulated and analyzed in basic switching circuits. Recommended Prerequisite: Students are expected to have an undergraduate-level active circuit knowledge and some experience with LTSPICE. Students who have not used LTSPICE before, should expect to spend more than the estimated time needed to complete the simulation-based assignments.
ECEA 5722 High-Voltage p-n and Schottky DiodesSpecialization: 2nd course in the Power Semiconductor DevicesInstructors: Bart Van Zeghbroeck, Ph.D., Professor
Syllabus for High-Voltage p-n and Schottky Diodes opens in new window
ECEA 5305 Linux System Programming and Introduction to BuildrootSpecialization: 1st course in the Advanced Embedded Linux DevelopmentInstructors: Dan Walkes
Syllabus for Linux System Programming and Introduction to Buildroot opens in new window
Provides an overview of System Programming for the Linux operating system, or software which is interfacing directly with the Linux Kernel and C library. The basic components of a Linux Embedded System, including kernel and root filesystem details are discussed. The Buildroot build system is introduced, which students use to build their own custom Embedded Linux system through programming assignments. Recommended Prerequisites: Knowledge of C Programming and embedded computer architecture and working knowledge of Linux command line operations, shell programming, Git, and makefiles.
ECEA 5306 Linux Kernel Programming and Introduction to YoctoSpecialization: 2nd course in the Advanced Embedded Linux DevelopmentInstructors: Dan Walkes
Syllabus for Linux Kernel Programming and Introduction to Yocto opens in new window
Provides an overview of Linux Kernel Programming. The basics of Linux Kernel development and device driver development are included. Building on content covered in the previous module, the Yocto Project is also introduced as a second Embedded Linux device build system. Students develop a custom character device driver and deploy on a Yocto or Buildroot based qemu emulated Embedded System. Recommended Prerequisites: Knowledge of C Programming and embedded computer architecture and working knowledge of Linux command line operations, shell programming, Git, and makefiles.
ECEA 5307 Embedded Systems Topics and ProjectSpecialization: 3rd course in the Advanced Embedded Linux DevelopmentInstructors: Dan Walkes
Syllabus for Embedded Systems Topics and Project opens in new window
Building on concepts of previous courses in the series to implement a project based on a hardware platform which supports Embedded Linux, students pick a final project hardware platform and a final project topic. The project will use either Buildroot or Yocto to build a hardware image. Final project implementation will be organized in sprints based on Agile development methodology.
ECEA 5349 Electric Vehicle SensorsSpecialization: 1st course in Sensors for a Carbon Free WorldInstructor: Jay Mendelson, MSME, Lecturer
Syllabus for Electric Vehicle Sensors Opens in new window
“Electric Vehicle Sensors” starts with a discussion on how electric vehicles work differently from gasoline or diesel fuel powered vehicles and the major types of electric vehicles. It then moves to the unique components of full electric and hybrid electric vehicles, and how in-vehicle and outside battery charging systems work. We reference all the sensors that are used for in-vehicle and outside unique components. Then we do a deep dive into how each of these sensors work.
ECEA 5350 Wind Turbine SensorsSpecialization: 2nd course in Sensors for a Carbon Free WorldInstructor: Jay Mendelson, MSME, Lecturer
Syllabus for Wind Turbine Sensors Opens in new window
"Wind Turbine Sensors" starts with a discussion on how wind turbines generate electricity for the grid. It then moves to the major components of a wind turbine and how the generator transfers power to the grid. We reference all the sensors that are used in wind turbines. Then we perform detailed calculations on power efficiency, kinetic energy, DC power generation, and DC to AC conversion. Last, we do a deep dive into how each sensor in a wind turbine works.
ECEA 5351 Solar Power SensorsSpecialization: 3rd course in Sensors for a Carbon Free WorldInstructor: Jay Mendelson, MSME, Lecturer
Syllabus for Solar Power Sensors Opens in new window
“Solar Power Sensors” starts with a discussion on the photovoltaic process for generating electricity for the grid. It then moves to the types of solar cells: monocrystalline vs. polycrystalline, thin film, perovskite. We the move to the major components of a solar cell, how electricity is transferred to the grid, and how solar power grids are constructed. We reference all the sensors that are used in solar cells. Then we perform detailed calculations on solar irradiance, shading and efficiency. Last, we do a deep dive into how each sensor in a solar cell works.
ECEA 5800 Control Systems Analysis: Modeling of Feedback SystemsSpecialization: 1st course in Control Systems AnalysisInstructor: Lucy Pao, Professor, Palmer Endowed Chair in Electrical, Computer & Energy Engineering
Syllabus for Modeling of Feedback Systems Opens in new window
Covers differential equation derivation to model systems, solving these equations through Laplace transforms to determine transfer functions for simple mechanical, electrical, and electromechanical systems. We will analyze 1st and 2nd-order system dynamic responses, and explore approximating higher-order systems with 1st to 3rd-order systems. Also covered, Bounded-Input Bounded-Output (BIBO) stability, plus designing and evaluating proportional, integral, and derivative controllers.
ECEA 5934 Engineering Genetic Circuits: DesignSpecialization: 1st course in Engineering Genetic CircuitsInstructor: 1. Chris Myers, Department Chair, Professor, Palmer Leadership Chair in Electrical, Computer & Energy Engineering 2. Lukas Buecherl
Syllabus for Engineering Genetic Circuits: Design Opens in new window
Gives an introduction to the biology and biochemistry necessary to understand genetic circuits. It starts by providing an engineering viewpoint on genetic circuit design and a review of cells and their structure. The second module introduces genetic parts and the importance of standards followed by a discussion of genetic devices used within circuit design. The last two modules cover experimental techniques and construction methods and principles applied during the design process.
ECEA 5935 Engineering Genetic Circuits: Modeling and AnalysisSpecialization: 2nd course in Engineering Genetic CircuitsInstructor: 1. Chris Myers, Department Chair, Professor, Palmer Leadership Chair in Electrical, Computer & Energy Engineering 2. Lukas Buecherl
Syllabus for Engineering Genetic Circuits: Modeling and Analysis Opens in new window
Covers mathematical models and analysis methods used to describe genetic circuits in the field of synthetic biology. The first module introduces modeling methods and standards for modeling. The following three modules cover different methods for the simulation of models to predict a genetic circuit's behavior in silico. Methods covered include ordinary differential equation analysis and stochastic analysis. The course ends with an introduction to genetic circuit technology mapping, the process of assigning physical biological parts to implement the functional design specification.
ECEA 5936 Engineering Genetic Circuits: Abstraction MethodsSpecialization: 3rd course in Engineering Genetic CircuitsInstructor: 1. Chris Myers, Department Chair, Professor, Palmer Leadership Chair in Electrical, Computer & Energy Engineering 2. Lukas Buecherl
Syllabus for Engineering Genetic Circuits: Abstraction Methods Opens in new window
Given the substantial computational requirements for simulation of even modest size genetic circuits, model abstraction is essential. To reduce the cost of simulation, this course first describes methods to simplify the original reaction-based model by applying several reaction-based abstractions. Second, this course introduces state-based (logical) abstraction methods and analysis techniques that have commonly been applied to electronic circuits.
EMEA 5094 Market Research & Analysis for Tech IndustriesSpecialization: Marketing Strategy for Engineers and TechnologistsInstructor: John Svoboda, Teaching Assistant Professor
This first course in the Digital Marketing Specialization begins with customer behavior, both consumer and business-to-business. We learn to design and execute means of gathering information on markets and customers, market research. We then analyze that data using various tools and approaches. Throughout, our guiding scenario of a technology or engineering startup with a novel product or service is both exciting and a realistic representation of staff, financial and time resources.
EMEA 5095 Digital Media & Strategic Planning in Technology MarketsSpecialization: Marketing Strategy for Engineers and TechnologistsInstructor: John Svoboda, Teaching Assistant Professor
In this second Digital Marketing Specialization course we develop strategic analysis and planning skills, applying the tools of industry to turn market research into actionable items. Next, we will investigate the most effective media channels available, focused on the more efficient and dynamic digital marketing channels. Throughout, our guiding scenario of a technology or engineering startup with a novel product or service is both exciting and a realistic representation of staff, financial and time resources.
EMEA 5096 Building and Pitching Marketing Campaigns in Tech IndustriesSpecialization: Marketing Strategy for Engineers and TechnologistsInstructor: John Svoboda, Teaching Assistant Professor
In this third Digital Marketing Specialization course we bring together all our skills to build a marketing plan for a real-world startup company of our choosing. We develop and apply industry decision metrics and critical lenses while building a comprehensive plan, both written and a video pitch, addressing executive decision-makers. Now our guiding scenario of a technology startup with a novel product comes to fruition with a complete strategic program for a firm operating in a dynamic engineering industry.
ECEA 5370 Network Systems FoundationsSpecialization: Network Systems: Principles and Practice (Linux and Cloud Networking)Instructor: Eric Keller, Associate Professor
Syllabus for Network Systems Foundations Opens in new window
ECEA 5371 Network Principles in Practice: Linux Networking Specialization: Network Systems: Principles and Practice (Linux and Cloud Networking)Instructor: Eric Keller, Associate Professor
Syllabus for Network Principles in Practice: Linux Networking Opens in new window
ECEA 5372 Network Principles in Practice: Cloud Networking Specialization: Network Systems: Principles and Practice (Linux and Cloud Networking)Instructor: Eric Keller, Associate Professor
Syllabus for Network Principles in Practice: Cloud Networking Opens in new window
ECEA 5900 Introduction to Modeling for Formal Verification Specialization: Fundamentals of Model CheckingInstructor: Hao Zhang, Assistant Professor
Syllabus for Introduction to Modeling for Formal Verification Opens in new window
ECEA 5901 Temporal Logic Model Checking Specialization: Fundamentals of Model CheckingInstructor: Hao Zhang, Assistant Professor
Syllabus for Temporal Logic Model Checking Opens in new window
ECEA 5850 Kalman-Filter Boot Camp and State-Estimation ApplicationSpecialization: 1st course in Applied Kalman FilteringInstructor: Gregory Plett, Professor, Electrical, Computer & Energy Engineering
Syllabus for Kalman-Filter Boot Camp and State-Estimation Application Opens in new window
Introduces the Kalman filter as a method that can solve problems related to estimating the hidden internal state of a dynamic system. Develops the background theoretical topics in state-space models and stochastic systems. Presents the steps of the linear Kalman filter and shows how to implement these steps in Octave code and how to evaluate the filter’s output.
ECEA 5851 Kalman Filter Deep Dive and Target-Tracking ApplicationSpecialization: 2nd course in Applied Kalman FilteringInstructor: Gregory Plett, Professor, Electrical, Computer & Energy Engineering
Syllabus for Kalman Filter Deep Dive and Target-Tracking Application Opens in new window
Derives the steps of the linear Kalman filter to give understanding regarding how to adjust the method to applications that violate the standard assumptions. Applies this understanding to enhancing the robustness of the filter and to extend to applications including prediction and smoothing. Shows how to implement a target-tracking application in Octave code using an interacting multiple-model Kalman filter.
ECEA 5852 Nonlinear Kalman Filters, Parameter-Estimation ApplicationSpecialization: 3rd course in Applied Kalman FilteringInstructor: Gregory Plett, Professor, Electrical, Computer & Energy Engineering
Syllabus for Nonlinear Kalman Filters, Parameter-Estimation Application Opens in new window
Derives the steps of the extended Kalman filter and the sigma-point Kalman filter for estimating the state of nonlinear dynamic systems. Shows how to implement these filters in Octave code and compare their results. Introduces adaptive methods to tune Kalman-filter noise-uncertainty covariances online. Shows how to estimate the parameters of a state-space model using nonlinear Kalman filters.
ECEA 5853 Particle Filters and Navigation ApplicationSpecialization: 4th course in Applied Kalman FilteringInstructor: Gregory Plett, Professor, Electrical, Computer & Energy Engineering
Syllabus for Particle Filters and Navigation Application Opens in new window
Develops the particle filter for solving strongly nonlinear state-estimation problems. Introduces Monte-Carlo integration and the importance density. Derives the sequential importance sampling method to estimate the posterior probability density function of a system’s state. Illustrates the degeneracy problem for this method and shows how to solve it via resampling. Shows how to implement a robust particle-filter in Octave code.
Course Session
See ME-EM Calendar opens in new window and Information for Current Students opens in new window
Enrollment for the session beginning June 30 opens on June 16, 2025.
Instructions to set up your CU Boulder IdentiKey and email address will be sent to your personal email. You will then use your Colorado.edu email address to link to your Coursera account. Your Colorado.edu email will be used for important University of Colorado Boulder communications so be sure to check it often.
As an institution who is a member of the National Council for State Authorization Reciprocity Agreements (NC-SARA), part of our membership duties is to report the number of students we have located in each state enrolled in out-of-state learning placements (e.g. internships, field experiences, practica, etc.) and online courses. None of your personally identifiable information is tied to this data. You can read more about NC-SARA here: https://www.nc-sara.org/about opens in new window
We ask this for federal reporting purposes to the U.S. Department of Education.
Your SSN is required for select business processes, including federal and state reporting, issuing tuition statements for tax purposes and verifying your Selective Service registration, among other things. Personally identifiable information is secured and accessed only by school officials with a legitimate educational interest who have completed student data privacy training, per university policy and federal law.
Pay with U.S. Dollars (USD)
We have partnered with NelNet Campus Commerce to accept payment in US Dollars. NelNet offers two payment options:
Option 1: eCheck – U.S. checking or savings account (no fee) ECheck is a direct bank transfer from a traditional checking or savings account in the United States. There are no fees associated with this payment method.
Option 2: Credit or debit card (2.85% fee)– AMEX, Discover, Mastercard, Visa Pay with a credit or debit card in US dollars. We accept American Express, Discover, Mastercard or Visa. Nelnet Campus Commerce charges a nonrefundable 2.85% service fee for each transaction using this payment method. Learn more about payment methods on the Bursar's Office website at Degrees on Coursera payment methods.
Pay with another currency
International wire transfer or international credit card – Pay with your local currency from outside the U.S. (fees vary by country)
We have partnered with Flywire to accept payments in local currencies from outside the United States. Pay securely in your or your employer’s country's currency, using local payment methods. See how it works and learn about Flywire's Best Price Guarantee on the Bursar's Office website at Degrees on Coursera payment methods.
Important! Paying with Flywire is a multi-step process. You will be enrolled in the course once you have completed all payment steps. Assignment and exam dates will not be adjusted for delays in payment and enrollment. This session ends on June 27, 2025. Before proceeding, ensure you have enough time to complete all coursework and schedule exams. Otherwise, please consider enrolling in the next session.
