This course can also be taken for academic credit as ECEA 5318, part of CU Boulder’s Master of Science in Electrical Engineering degree. The final course emphasizes hands-on building of an application using real-time machine vision and multiple real-time services to synchronize the internal state of Linux with an external clock via observation. Compare actual performance to theoretical and analysis to determine scheduling jitter and to mitigate any accumulation of latency. The verification of the final project will include comparison of system timestamp logs with a large set of images which can be encoded into a video. The final report will be peer reviewed and the captured frames and video uploaded for scripted assessment. Course Learning Outcomes: ● Outcome 1: Decompose a problem and set of basic real-time requirements into software modules and Linux POSIX real-time threads ● Outcome 2: Analyze services in terms of C (execution time), T (request period), and D (deadlines for completion) to establish feasibility and margin for meeting requirements ● Outcome 3: Design and construct a solution for a native Linux system equipped with a webcam to verify and demonstrate system synchronization using machine vision processing

Learners will create a roadmap to achieve their own personal goals related to the digital manufacturing and design (DM&D) profession, which will help them leverage relevant opportunities. The culminating project provides a tangible element to include in their professional portfolios that showcases their knowledge of Industry 4.0. This project is part of the Digital Manufacturing and Design Technology specialization that explores the many facets of manufacturing’s “Fourth Revolution,” aka Industry 4.0. To learn more about the specialization and its courses, please watch the overview video by copying and pasting the following link into your web browser: https://youtu.be/wETK1O9c-CA

Exploring concepts of Optics using Wolfram notebook

This class provides a series of Python programming exercises intended to explore the use of numerical modeling in the Earth system and climate sciences. The scientific background for these models is presented in a companion class, Global Warming I: The Science and Modeling of Climate Change. This class assumes that you are new to Python programming (and this is indeed a great way to learn Python!), but that you will be able to pick up an elementary knowledge of Python syntax from another class or from on-line tutorials.

This course can also be taken for academic credit as ECEA 5610, part of CU Boulder’s Master of Science in Electrical Engineering degree. 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 build on them more advanced topics. At the end of this course learners will be able to: 1. demonstrate full grasp of basic concepts in quantum mechanics including wave-particle duality, operators and wavefunctions, and evolution of quantum states, 2. achieve mastery of the mathematical apparatus needed for quantum mechanics and 3. attain foundational knowledge required to learn more advanced quantum mechanics and applications.

This course offers you advanced knowledge within the field of photovoltaic system technology. We'll learn about the solar resource and how photovoltaic energy conversion is used to produce electric power. From this fundamental starting point we'll cover the design and fabrication of different solar cell and module technologies, the various photovoltaic system components, how to design a photovoltaic plant and carry out energy yield simulations, essentials in energy economics, O&M and reliability assessment, as well as the role of photovoltaic energy in sustainable energy systems. This course is unique in that it takes you from the nanoscale physics of a solar cell to the modelling of a utility scale solar farm. The course is made up of 9 sections with an estimated workload of 2-3 hours each. The academic level is targeted at master students at technical universities and engineers from the energy industry. Passing this course offers you a great basis for a career in the field of photovoltaics.

Are you motivated by the idea that social justice can be served by the energy transition, but are not sure how to make this happen? Do you want to grow your ability to recognize - and do something about - injustice in the energy space? Are you a sustainability or environmental professional eager to help design just energy systems? Do you wonder how to help advance equity in your community’s energy decisions? This course is for you! Energy is the lifeblood of the modern way of life. Yet not everyone has equal access to its benefits, and the environmental and social costs of producing, transporting, and using it are not evenly distributed. In this course you will explore the idea and practice of energy justice: what does it look like? Why are societies struggling to achieve it? What do we mean by sociotechnical energy systems, and how can we make them more equitable? The purposes of this course are (1) to introduce individuals and organizations to the concept of energy justice and where it comes from, and (2) to help them build a toolkit to identify and leverage opportunities to increase fairness and equity in energy-related decisions and actions. After completing this course, learners should be better equipped to recognize and confront energy injustice in their personal and professional lives, and to help envision and foster energy justice in society. Course Learning Objectives At the end of this course, students will be able to: • Define energy justice and explain its relationship to environmental justice, climate justice, and energy democracy • Define structural inequity and describe the impact of historical racism on today's energy systems • Describe the social complexity of energy systems as well as their major physical elements • Identify and explain key energy justice principles and frameworks • Distinguish between multiple forms of injustice in energy systems and analyze potential remedies • Discuss energy injustice and structural inequality with fluency • Identify and assess energy injustices in personal, professional and civic contexts • Design strategies to integrate energy justice into professional work and civic life • Advocate for energy justice as an essential element of energy transitions and climate change mitigation • Envision more just energy futures

"Excel/VBA for Creative Problem Solving, Part 1" is aimed at learners who are seeking to augment, expand, optimize, and increase the efficiency of their Excel spreadsheet skills by tapping into the powerful programming, automation, and customization capabilities available with Visual Basic for Applications (VBA). This course is the first part of a three-part series and Specialization that focuses on the application of computing techniques in Excel/VBA to solve problems. In this course (Part 1), you will: 1) create macros to automate procedures in Excel; 2) define your own user-defined functions; 3) create basic subroutines to interface with the user; 4) learn the basic programming structures in VBA; and 5) automate Excel’s Goal Seek and Solver tools and use numerical techniques to create “live solutions” to solve targeting and optimization problems. New to computer programming? The extremely intuitive and visual nature of VBA lends itself nicely to teaching and learning - what a fun way to learn to code! No prior knowledge in programming nor advanced math skills are necessary yet seasoned programmers will pick up new and creative spreadsheet problem solving strategies. After you have learned the basics of VBA, each module will introduce foundational and broad problems inspired by situations that you might encounter in the real world. To pass each module, you'll need to pass a mastery quiz and complete a problem solving assignment. This course is unique in that the weekly assignments are completed in-application (i.e., on your own computer in Excel), providing you with valuable hands-on training.

This course can also be taken for academic credit as ECEA 5709, part of CU Boulder’s Master of Science in Electrical Engineering degree. This is Course #5 in the Modeling and Control of Power Electronics Specialization. The course 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. We strongly recommend students complete the CU Boulder Power Electronics Specialization as well as Courses #1 (Averaged-Switch Modeling and Simulation) and #4 (Current-Mode Control) before enrolling in this course (the course numbers provided below are for students in the CU Boulder's MS-EE program): ● Introduction to Power Electronics (ECEA 5700) ● Converter Circuits (ECEA 5701) ● Converter Control (ECEA 5702) ● Averaged-Switch Modeling and Simulation (ECEA 5705) ● Current-Mode Control (ECEA 5708) After completing this course, you will be able to: ● Understand the operating principles of low-harmonic, high power factor rectifier and inverters ● Model and design current shaping and voltage control loops in power factor correction (PFC) rectifiers ● Model and design control loops in single-phase dc-to-ac inverters ● Design photovoltaic power systems tied to the single-phase ac power grid ● Use computer-aided tools and simulations to verify the design of rectifiers and inverters

This course can also be taken for academic credit as ECEA 5632, part of CU Boulder’s Master of Science in Electrical Engineering degree. 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. At the end of this course learners will be able to: 1. Understand and analyze metal-oxide-semiconductor (MOS) device 2. Understand and analyze MOS field effect transistor (MOSFET) 3. Understand and analyze bipolar junction transistor (BJT)