This is an advanced graduate course on quantum computation and quantum information, for which prior knowledge of quantum mechanics is required. Topics include quantum computation, advanced quantum error correction codes, fault tolerance, quantum algorithms beyond factoring, properties of quantum entanglement, and quantum protocols and communication complexity.
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Massachusetts Institute of Technology is in Tier 1: world-leading universities and India's top institutes of our institution ranking (98/100). OpenCourseWare is the gold standard for free university material.
Instructor: Dennis Freeman, Kendra Pugh This course provides an integrated introduction to electrical engineering and computer science, including modern software engineering, linear systems analysis, electronic circuits, and decision-making. The lecture videos provide an overview of each topic, whi…
Instructor: Russell Tedrake See the complete course at: http://ocw.mit.edu/6-832s09 Robots today move far too conservatively, using control systems that attempt to maintain full control authority at all times. Humans and animals move much more aggressively by routinely executing motions which invol…
Harvard University · edX
Learn fundamental principles of architecture — as an academic subject or a professional career — by studying some of history’s most important buildings.
Instructor: David Perreault View the complete course: https://ocw.mit.edu/courses/6-622-power-electronics-spring-2023 YouTube Playlist: https://www.youtube.com/playlist?list=PLUl4u3cNGP62UTc77mJoubhDELSC8lfR0 6.622 covers modeling, analysis, design, control, and application of circuits for energy c…
In this webinar Professor Bill Burnett gives you a taste of what will be taught during the Innovation Masters Series course being held this June 19 -21, 2013 and December 11 - 13, 2013 at Stanford University. Explore Stanford Online's Innovation and Design Thinking courses and programs: https://onl…
Harvard University · edX
Learn to program in TensorFlow Lite for microcontrollers so that you can write the code, and deploy your model to your very own tiny microcontroller. Before you know it, you’ll be implementing an entire TinyML application.
