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This course may also be credited toward ECEA 5705 in the CU Boulder Electrical Engineering Master of Science program. It is Course 1 in the Power Electronics Modeling and Control sequence. The course provides practical modeling and control of pulse-width modulated power converters using time- and frequency-domain analysis and simulation tools. A design-oriented analysis technique known as the Middlebrook Feedback Theorem is introduced and applied to the analysis and design of voltage regulators and other feedback circuits. Additionally, it is shown how circuit averaging and average switch modeling techniques result in average converter models suitable for manual analysis, computer analysis, and converter simulation. Upon completion of this course, the student will be able to practice designing high-performance switching power converter control loops using analytical and simulation techniques. We strongly recommend that students complete the CU Boulder Power Electronics Specialization before enrolling in this course (course numbers listed are for CU Boulder MS-EE students): ● Introduction to Power Electronics (ECEA 5700) ● Converter Circuits (ECEA 5701) ● Converter Control (ECEA 5702) After completing this course, you will be able to: ● Explain the operation and modeling of switching power converters ● Model open-loop transfer functions and frequency responses ● Design closed-loop adjustable switching power converters ● Verify the operation of switching power converters through simulation ● Understand the principles of the feedback theorem ● Apply the feedback theorem to practical design examples ● Derive average switch models and average power converter circuit models ● Apply average switch modeling techniques to analysis, design and modeling of power converters

Why would hundreds of scientists from around the world deliberately freeze a ship in Arctic sea ice for a year, bravely enduring sub-zero temperatures and months of polar darkness? It might sound like the plot of a fictional adventure film, but from September 2019 to October 2020, the Arctic research expedition MOSAiC (Multidisciplinary drifting Observatory for the Study of Arctic Climate) did just that. In this course, you will hear directly from MOSAiC scientists and Arctic experts about why this expedition is so important to advancing our understanding of the Arctic and global climate systems, and what types of data they will collect during MOSAiC on the ice, under the sea, and in the air. The course begins with an examination of the geography, climate, and history of Arctic exploration, and then introduces students to the major components of the Arctic system: the atmosphere, ocean, sea ice, and ecosystems. You will also learn how the data collected during MOSAiC will be used to improve climate model predictions. Finally, we will conclude the course by exploring the challenges facing the new Arctic, including how Arctic Indigenous Peoples have different influences on the changing Arctic environment.

"Everyday Excel, Part 1" is designed for anyone looking to learn Excel from scratch. No prior experience with Excel is required. While this course is designed for beginner Excel users, experienced users will undoubtedly gain new skills and tools. This course is the first in a three-part series and specialization that focuses on teaching beginner to very advanced Excel techniques and tools. In this course (Part 1), you will: 1) learn to navigate the Excel environment effectively; 2) edit and format Excel worksheets; 3) apply basic and advanced Excel functions (including financial, logical, and text functions); 4) learn to manage data sets (filter, remove duplicates, combine data, sort data, and validate data); and 5) learn to effectively visualize data using scatter plots, bar charts, and pie charts. New to Excel? That's totally okay! This course is designed to be fun, thought-provoking, and intended for a general audience. No prior programming knowledge or deep mathematical skills are required. The course consists of 5 weeks (modules). To complete each module, you will need to pass a test of your understanding of the material and complete a problem-solving assignment. What makes this course unique is that the weekly assignments are completed in application mode (i.e. on your own computer in Excel), which provides you with valuable practical training.

"Everyday Excel, Part 2" is a continuation of the popular course "Everyday Excel, Part 1". Building on the concepts learned in the first course, you will continue to expand your knowledge of Excel applications. This course is designed for intermediate users, but even advanced users will gain new skills and tools for working in Excel. By the end of this course, you will have the skills and tools necessary to work on the project "Everyday Excel, Part 3 (Projects)". This course is the second part of a three-part series and specialization that focuses on teaching beginner to very advanced techniques and tools in Excel. In this course (Part 2), you will: 1) Master advanced data management techniques; 2) Learn to perform financial calculations in Excel; 3) Use advanced Excel tools (Data Tables, Goal Seek, and Solver) to perform and solve what-if analysis problems; 4) Learn to create mathematical models of predictive regression using the Regression tool in Excel. This course is intended to be engaging and thought-provoking. I hope that at least a few times during the course you will say to yourself, "Wow, I never thought of that before!" Given the wide range of experience and abilities of the learners, the course aims to appeal to a broad audience. The course consists of 5 weeks (modules). To complete each module, you will need to pass a knowledge test and a problem-solving assignment. What makes this course unique is that the weekly assignments are completed in application mode (i.e. on your own computer in Excel), which provides you with valuable practical training.

This course can also be taken for academic credit as ECEA 5707, part of CU Boulder’s Master of Science in Electrical Engineering degree. This is Course #3 in the Modeling and Control of Power Electronics course sequence. After completion of this course, you will gain an understanding of issues related to electromagnetic interference (EMI) and electromagnetic compatibility (EMC), the need for input filters and the effects input filters may have on converter responses. You will be able to 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. We strongly recommend students complete the CU Boulder Power Electronics specialization as well as Courses #1 (Averaged-Switch Modeling and Simulation) and #2 (Techniques of Design-Oriented Analysis) 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) ● Techniques of Design-Oriented Analysis (ECEA 5706) After completing this course, you will be able to: ● Understand conducted electromagnetic interference (EMI) and the need for input filter ● Understand input filter design principles based on attenuation requirements and impedance interactions. ● Design properly damped single-stage input filters. ● Design properly damped multi-stage input filters. ● Use computer-aided tools and simulations to verify input filter design

This course may also be credited toward ECEA 5708 in the CU Boulder Electrical Engineering Master of Science program. It is Course 4 in the Power Electronics Modeling and Control sequence. This course focuses on current mode control techniques that are very common in switching power applications. The practical advantages of peak current mode control are discussed, including built-in overcurrent protection, simpler and more robust dynamic response, and the ability to provide current sharing in paralleled converter modules. For peak current mode controlled converters, slope compensation and high frequency effects are discussed in detail. Upon completion of this course, you will be able to understand, analyze, model, and design high performance current mode controllers for DC/DC converters, including peak current mode controllers and average current mode controllers. We strongly recommend that students complete the CU Boulder Power Electronics Specialization as well as Course #1 (Modeling and Simulating Averaged Switches) before enrolling in this course (course numbers below are for CU Boulder MS-EE students): ● Introduction to Power Electronics (ECEA 5700) ● Converter Circuits (ECEA 5701) ● Converter Control (ECEA 5702) ● Modeling and Simulating Averaged Switches (ECEA 5705) After completing this course, you will be able to: ● Understand the principles of operation and benefits of current mode control for DC-DC converters ● Model and design DC-DC converters with peak current mode control ● Model and design DC-DC converters with average current mode control ● Use computer tools and simulation to validate DC-DC converters with current mode control

This course will introduce you to all aspects of development of Soft Processors and Intellectual Property (IP) in FPGA design. You will learn the extent of Soft Processor types and capabilities, how to make your own Soft Processor in and FPGA, including how to design the hardware and the software for a Soft Processor. You will learn how to add IP blocks and custom instructions to your Soft Processor. After the Soft Processor is made, you learn how to verify the design using simulation and an internal logic analyzer. Once complete you will know how to create and use Soft Processors and IP, a very useful skill. This course consists of 4 modules, approximately 1 per week for 4 weeks. Each module will include an hour or two of video lectures, reading assignments, discussion prompts, and an end of module assessment.

This course will give you hands-on FPGA design experience that uses all the concepts and skills you have developed up to now. You will need to purchase a DE10-Lite development kit. You will setup and test the MAX10 DE10-Lite board using the FPGA design tool Quartus Prime and the System Builder. You will: Design and test a Binary Coded Decimal Adder. Design and test a PWM Circuit, with verification by simulation. Design and test an ADC circuit, using Quartus Prime built-in tools to verify your circuit design. Create hardware for the NIOS II soft processor, including many interfaces, using Qsys (Platform Designer). Instantiate this design into a top-level DE10-Lite HDL file. Compile your completed hardware using Quartus Prime. Enhance and test a working design, using most aspects of the Quartus Prime Design Flow and the NIOS II Software Build Tools (SBT) for Eclipse. Create software for the NIOS II soft processor, including many interfaces, using Qsys (Platform Designer) and the SBT. Compile your completed software using the SBT. Use Quartus Prime to program both the FPGA hardware configuration and software code in you DE10-Lite development kit. Record all your observations in a lab notebook pdf. Submit your project files and lab notebook for grading. This course consists of 4 modules, approximately 1 per week for 4 weeks. Each module will include an hour or less of video lectures, plus reading assignments, discussion prompts, and project assignment that involves creating hardware and/or software in the FPGA.

This course can also be taken for academic credit as ECEA 5703, part of CU Boulder’s Master of Science in Electrical Engineering degree. This course covers the analysis and design of magnetic components, including inductors and transformers, used in power electronic converters. The course starts with an introduction to physical principles behind inductors and transformers, including the concepts of inductance, core material saturation, airgap and energy storage in inductors, reluctance and magnetic circuit modeling, transformer equivalent circuits, magnetizing and leakage inductance. Multi-winding transformer models are also developed, including inductance matrix representation, for series and parallel structures. Modeling of losses in magnetic components covers core and winding losses, including skin and proximity effects. Finally, a complete procedure is developed for design optimization of inductors in switched-mode power converters. After completing this course, you will: - Understand the fundamentals of magnetic components, including inductors and transformers - Be able to analyze and model losses in magnetic components, and understand design trade-offs - Know how to design and optimize inductors and transformers for switched-mode power converters This course assumes prior completion of courses 1 and 2: Introduction to Power Electronics, and Converter Circuits.

This course explores how animals and humans are situated within the web of structures and connections known as ‘society’. Module 1 looks at some of the key symbolic roles that animals play in society, exploring the practice of ‘thinking with animals’. We explore how people create different meanings of animals and the consequences of these meanings for both animals and people. You will gain first-hand experience by analysing how animals are represented in the media. Modules 2 and 3 explore human-animal relationships, including those that involve suffering as well as those that bring benefit. While many people refer to their pets as friends or family members, Module 2 looks more deeply at what constitutes friendship and family membership when it comes to other animal species. Module 3 looks at the dark side of these relationships, with a particular focus on animal cruelty and its links to domestic violence. Module 4 looks at people’s encounters with these animals outside the home and farm. How people understand and treat species that are commonly considered "wild" shapes attitudes toward these animals and their moral status.

This course can also be credited toward ECEA 5347, part of CU Boulder's Electrical Engineering graduate program. Rapid Prototyping is the second of three courses in the Embedded Interface Design (EID) specialization, an online version of the EID course taught on campus in the Embedded Systems Engineering graduate program. This course focuses on rapid prototyping of devices and systems and the associated methods, practices, and principles to help ensure that your embedded interface designs meet the needs and desires of users. The course includes an introduction to rapid prototyping, prototyping device and system user interfaces, device prototyping, and device design considerations and perspectives. Course content ranges from general design best practices to embedded device-specific topics covering the different types and specifics of user interfaces, but all are presented to support embedded device development. The course includes hands-on projects that allow you to try out some standard software development techniques to prototype graphical user interfaces for devices using Qt and HTML. This course may be credited toward ECEA 5347, part of CU Boulder's Master of Science in Electrical Engineering program.

This course introduces the fundamentals of high-performance and parallel computing. It is targeted to scientists, engineers, scholars, really everyone seeking to develop the software skills necessary for work in parallel software environments. These skills include big-data analysis, machine learning, parallel programming, and optimization. We will cover the basics of Linux environments and bash scripting all the way to high throughput computing and parallelizing code. We recommend you are familiar with either Fortran 90, C++, or Python to complete some of the programming assignments. After completing this course, you will be familiar with: The components of a high-performance distributed computing system Types of parallel programming models and the situations in which they might be used High-throughput computing Shared memory parallelism Distributed memory parallelism Navigating a typical Linux-based HPC environment Assessing and analyzing application scalability including weak and strong scaling Quantifying the processing, data, and cost requirements for a computational project or workflow This course can be taken for academic credit as part of CU Boulder's Master of Science in Data Science (MS-DS) degree offered on the Coursera platform. The MS-DS is an interdisciplinary degree that brings together faculty from CU Boulder's departments of Applied Mathematics, Computer Science, Information Science, and others. With performance-based admissions and no application process, the MS-DS is ideal for individuals with a broad range of undergraduate education and/or professional experience in computer science, information science, mathematics, and statistics. Learn more about the MS-DS program at https://www.coursera.org/degrees/master-of-science-data-science-boulder.