Information Theory
Introductory Level
- Khan Academy, Brit Cruise Informtion Theory
- Seth Lloyd (Complexity Explorer/YouTube) Introduction to Information Theory
Advanced
- Thomas Cover (Stanford | YouTube) Information Theory
- Raymond Yeung (Chinese University of Hong Kong | Coursera) Information Theory (May require account to see 3 or more archived versions)
- David MacKay (University of Cambridge) Information Theory, Inference, and Learning Algorithms
- Andrew Eckford (York University | YouTube) Coding and Information Theory
- S.N. Merchant (IIT Bombay | NPTEL :: Electronics & Communication Engineering) Introduction to Information Theory and Coding
Fortunately, most are pretty reasonable, though vary in their coverage of topics. The introductory lectures don’t require as much mathematics and can probably be understood by those at the high school level with just a small amount of basic probability theory and an understanding of the logarithm.
The top three in the advanced section (they generally presume a prior undergraduate level class in probability theory and some amount of mathematical sophistication) are from professors who’ve written some of the most commonly used college textbooks on the subject. If I recall a first edition of the Yeung text was available via download through his course interface. MacKay’s text is available for free download from his site as well.
Quantum Information
- Quantum Mechanics and Quantum Computation (aka Quantum Information I); Umesh V. Vazirani of UC Berkeley for edX | Berkeley
- Quantum Information II; Isaac Chuang of MIT for edX | MIT (Fall 2016)
Complexity
- Introduction to Dynamical Systems and Chaos; David Feldman of College of the Atlantic for Complexity Explorer (Summer 2016)