Search result for Course of electrical engineering Online Courses & Certifications
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Battery State-of-Health (SOH) Estimation
by Gregory Plett- 4.8
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Approx. 23 hours to complete
This course can also be taken for academic credit as ECEA 5733, part of CU Boulder’s Master of Science in Electrical Engineering degree. By the end of the course, you will be able to: 7: Summary of "Total-least-squares battery-cell capacity estimation"; what next? 7: Summary of "Simplified total-least-squares battery-cell capacity estimates"; what next?...
Electrodynamics: Electric and Magnetic Fields
by Seungbum Hong- 4.8
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Approx. 12 hours to complete
This course is a continuation of Electrodynamics: An Introduction and Electrodynamics: Analysis of Electric Fields. Furthermore, this course uniquely provides the link between the knowledge of electrodynamics and its practical applications to research in materials science, information technology, electrical engineering, chemistry, chemical engineering, energy storage, energy harvesting, and other materials related fields....
Signals and Systems, Part 2
by Vikram Gadre- 0.0
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10 Weeks
Ideas introduced in this course will be useful in understanding further electrical engineering courses which deal with control systems, communication systems, power systems, digital signal processing, statistical signal analysis and digital message transmission. The concepts taught in this course are also useful to students of other disciplines like mechanical, chemical, aerospace and other branches of engineering and science....
$49
Convex Optimization
by Stephen Boyd , Henryk Blasinski- 0.0
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8 Weeks
This course concentrates on recognizing and solving convex optimization problems that arise in applications. This course should benefit anyone who uses or will use scientific computing or optimization in engineering or related work (e. , summa cum laude, in Mathematics and Computer Science from the University of Pennsylvania and an M....
Convex Optimization
by Stephen Boyd , Henryk Blasinski- 0.0
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8 Weeks
This course concentrates on recognizing and solving convex optimization problems that arise in applications. This course should benefit anyone who uses or will use scientific computing or optimization in engineering or related work (e. , summa cum laude, in Mathematics and Computer Science from the University of Pennsylvania and an M....
Introduction to Electrical and Electronic Engineering - 電気電子工学入門 -
by Akira Chiba , Akira Matsuzawa , Shinsuke Miyajima , Ayaka Saito- 0.0
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4 Weeks
Learn fundamental knowledge about electrical and electronic engineering from Tokyo Tech instructors and engineers working in Japanese industry. This course introduces fundamental topics in electrical and electronic engineering including a broad range of examples. By taking this course, you will gain knowledge about general aspects of electrical and electronic engineering from Tokyo Tech instructors and engineers working in Japanese industry....
$50
Hardware Description Languages for FPGA Design
by Timothy Scherr , Benjamin Spriggs- 4.3
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Approx. 36 hours to complete
This course can also be taken for academic credit as ECEA 5361, part of CU Boulder’s Master of Science in Electrical Engineering degree. Simple first examples are presented, then language rules and syntax, followed by more complex examples, and then finally use of test bench simulations to verify correctness of the designs....
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Discrete Time Signals and Systems
by Richard G. Baraniuk- 0.0
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8 Weeks
Students will find out in this rigorous mathematical introduction to the engineering field of signal processing: the study of signals and systems that extract information from the world around us. This course is an excerpt from an advanced undergraduate class at Rice University taught to all electrical and computer engineering majors....
$249
Applied Data Science for Data Analysts
by Kevin Coyle , Mark Roepke , Emma Freeman- 4.2
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Approx. 16 hours to complete
NOTE: This is the third and final course in the Data Science with Databricks for Data Analysts Coursera specialization. Course Introduction and Prerequisites Identifying the Number of Clusters Identifying the Number of Clusters Demo Feature Engineering and Selection Introduction to Feature Engineering A Review of Feature Importance A Review of Model Generalization...
State Estimation and Localization for Self-Driving Cars
by Jonathan Kelly , Steven Waslander- 4.7
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Approx. 27 hours to complete
Welcome to State Estimation and Localization for Self-Driving Cars, the second course in University of Toronto’s Self-Driving Cars Specialization. We recommend you take the first course in the Specialization prior to taking this course. This is an advanced course, intended for learners with a background in mechanical engineering, computer and electrical engineering, or robotics....
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