Created by:   University of Pennsylvania

  • Kostas Daniilidis

    Taught by:    Kostas Daniilidis, Professor of Computer and Information Science

    School of Engineering and Applied Science

  • Jianbo Shi

    Taught by:    Jianbo Shi, Professor of Computer and Information Science

    School of Engineering and Applied Science

Basic InfoCourse 4 of 6 in the Robotics Specialization.
LevelIntermediate
Commitment4 weeks of study, 3-5 hours/week
Language
English
How To PassPass all graded assignments to complete the course.
User Ratings
4.3 stars
Average User Rating 4.3See what learners said
Course 4 of Specialization
Syllabus

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How It Works
Coursework
Coursework

Each course is like an interactive textbook, featuring pre-recorded videos, quizzes and projects.

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Connect with thousands of other learners and debate ideas, discuss course material, and get help mastering concepts.

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Certificates

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Creators
University of Pennsylvania
The University of Pennsylvania (commonly referred to as Penn) is a private university, located in Philadelphia, Pennsylvania, United States. A member of the Ivy League, Penn is the fourth-oldest institution of higher education in the United States, and considers itself to be the first university in the United States with both undergraduate and graduate studies.
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Ratings and Reviews
Rated 4.3 out of 5 of 179 ratings

Unclear explaination

Interesting material, presented well, very on-top and supportive TAs. I wish the second assignment had been the first assignment (the current first assignment is very basic and can be scrapped), so that the 4th assignment could be about implementing bundle adjustment.

This course is excellent: lots of things covered in depth, learning curve is high, detailed explanations with lots of examples; If you want to ramp up quickly on Structure for Motion or Visual Odometry, Visual SLAM, this is highly recommended. But be prepared to put some real effort in this demanding course. Overall one of the best MOOC I took. Programming assignments and especially the last one are *very* interesting. It's great to have such courses that are available for everybody. Pre-requisites are linear algebra (eigenvalues, eigenvectors, Jacobian, Hessian ...) and familiarity with matlab (but people familiar with numpy should easily ramp up). For people not familiar with matlab there are also some very nice matlab tutorials in the resources. Highly recommended.

very good, I love this course, I learned many knowledge from it