Information Theory

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6/10 stars
based on  3 reviews
Provided by:
Cost FREE
Start Date On demand

Course Details

Cost

FREE

Upcoming Schedule

  • On demand

Course Provider

Coursera online courses
Coursera's online classes are designed to help students achieve mastery over course material. Some of the best professors in the world - like neurobiology professor and author Peggy Mason from the University of Chicago, and computer science professor and Folding@Home director Vijay Pande - will supplement your knowledge through video lectures. They will also provide challenging assessments, interactive exercises during each lesson, and the opportunity to use a mobile app to keep up with yo...
Coursera's online classes are designed to help students achieve mastery over course material. Some of the best professors in the world - like neurobiology professor and author Peggy Mason from the University of Chicago, and computer science professor and Folding@Home director Vijay Pande - will supplement your knowledge through video lectures. They will also provide challenging assessments, interactive exercises during each lesson, and the opportunity to use a mobile app to keep up with your coursework. Coursera also partners with the US State Department to create “learning hubs” around the world. Students can get internet access, take courses, and participate in weekly in-person study groups to make learning even more collaborative. Begin your journey into the mysteries of the human brain by taking courses in neuroscience. Learn how to navigate the data infrastructures that multinational corporations use when you discover the world of data analysis. Follow one of Coursera’s “Skill Tracks”. Or try any one of its more than 560 available courses to help you achieve your academic and professional goals.

Provider Subject Specialization
Humanities
Sciences & Technology
4733 reviews

Course Description

This course is an introduction to information theory, which emphasizes fundamental concepts as well as analytical techniques. Specific topics include: Information Measures, The I-Measure, Zero-Error Data Compression, Weak Typicality, Strong Typicality, Discrete Memoryless Channels, etc.
Information Theory course image
Reviews 6/10 stars
3 Reviews for Information Theory

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Rankings are based on a provider's overall CourseTalk score, which takes into account both average rating and number of ratings. Stars round to the nearest half.

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Richard Taylor profile image
Richard Taylor profile image
2/10 starsDropped
  • 29 reviews
  • 28 completed
5 years, 2 months ago
A very difficult course with some major problems. The first problem and the reason I dropped is that what you learn in the lectures is not enough to do the homework assignments, and that's totally frustrating. I believe easier exercises with nicer examples that can be done based on what is learned in the lectures would fix this course. The second problem is the boring way the lectures are given without any interesting examples or motivation, just a readout of formulas and theorems without any story between them. Formula 2.3, then 2.4 then theorem 2.5 etc etc. I would have loved this to be a nice class but it fails. Badly.
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Equanimous Creativity profile image
Equanimous Creativity profile image
5/10 starsCompleted
  • 33 reviews
  • 32 completed
5 years, 7 months ago
I took Information Theory because it is super important when working data science and AI. Unfortunately this course focus entirely on coding theory but I still learned something I can use in AI. I don't understand why this is the only MOOC I can find in Information Theory. The course itself is not a good MOOC. The lecture videos is just the proves from the book read out. All the homework is made as peer assignment instead of quizzes. Which means that you get feedback on your homework 2 weeks after you made it. In conclusion a super important subject but a very poor MOOC implementation.
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Student profile image
Student profile image

Student

8/10 starsCompleted
5 years, 6 months ago
This was a really difficult course. Required a huge commitment of time and attention, and in most cases, the lectures had to be complemented by self- study, both from the recommended textbook as well as from other, more basic texts. The professor was mathematically sound, but did not do enough to motivate the subject. I think most students who took the course dropped out. What I liked was that the course covered a great deal of information in a mathematically very rigorous way. Even if I had dropped out halfway, I would have learned more from the course than from a typical undergrad course in Information Theory. Finishing the course was a huge achievement for me.
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Rankings are based on a provider's overall CourseTalk score, which takes into account both average rating and number of ratings. Stars round to the nearest half.