Summary thread for Coursera classes

Maybe it would be worth to have a single summary thread for Coursera (and also other source like Udacity etc.) material. At some future point when the courses are on-line and enough people seen them we could work out a "LW curiculum". Here is my subjective list of particularly intersting courses for LW audience:

A Beginner's Guide to Irrational Behavior
Artificial Intelligence Planning
Automata
Basic Behavioral Neurology
Computer Science 101
Clinical Problem Solving
Critical Thinking in Global Challenges
Data Analysis
Fantasy and Science Fiction: The Human Mind, Our Modern World
Game Theory
Human-Computer Interaction
Introduction to Genetics and Evolution
Introduction to Genome Science
Introduction to Mathematical Thinking
Machine Learning
Microeconomics Principles
Model Thinking
Nanotechnology: The Basics
Networked Life
Networks: Friends, Money, and Bytes
Neural Networks for Machine Learning
Neuroethics
Principles of Economics for Scientists
Probabilistic Graphical Models
Quantum Mechanics and Quantum Computation
Rationing and Allocating Scarce Medical Resources
Statistics One
Think Again: How to Reason and Argue

Please note I haven't picked any programming/algorithm courses - there seem to be quite a lot of nice ones. Subscribe here. Plain text list (111 courses):

A Beginner's Guide to Irrational Behavior
A History of the World since 1300
Aboriginal Worldviews and Education
Algorithms, Part I
Algorithms, Part II
Algorithms: Design and Analysis, Part 1
Algorithms: Design and Analysis, Part 2
An Introduction to Interactive Programming in Python
An Introduction to Operations Management
An Introduction to the U.S. Food System: Perspectives from Public Health
Analytic Combinatorics, Part I
Analytic Combinatorics, Part II
Analytical Chemistry
Artificial Intelligence Planning
Astrobiology and the Search for Extraterrestrial Life
Automata
Basic Behavioral Neurology
Bioelectricity: A Quantitative Approach
Calculus: Single Variable
Cardiac Arrest, Hypothermia, and Resuscitation Science
Chemistry: Concept Development and Application
Clinical Problem Solving
Community Change in Public Health
Compilers
Computational Investing, Part I
Computational Photography
Computer Architecture
Computer Science 101
Computer Vision: From 3D Reconstruction to Visual Recognition
Computer Vision: The Fundamentals
Computing for Data Analysis
Contraception: Choices, Culture and Consequences
Control of Mobile Robots
Creative, Serious and Playful Science of Android Apps
Critical Thinking in Global Challenges
Cryptography
Cryptography II
Data Analysis
Design: Creation of Artifacts in Society
Digital Signal Processing
Drugs and the Brain
E-learning and Digital Cultures
Energy 101
Equine Nutrition
Fantasy and Science Fiction: The Human Mind, Our Modern World
Functional Programming Principles in Scala
Fundamentals of Electrical Engineering
Fundamentals of Online Education: Planning and Application
Fundamentals of Pharmacology
Galaxies and Cosmology
Game Theory
Gamification
Greek and Roman Mythology
Grow to Greatness: Smart Growth for Private Businesses, Part I
Health Policy and the Affordable Care Act
Health for All Through Primary Care
Healthcare Innovation and Entrepreneurship
Heterogeneous Parallel Programming
How Things Work 1
Human-Computer Interaction
Information Security and Risk Management in Context
Intermediate Organic Chemistry - Part 1
Intermediate Organic Chemistry - Part 2
Internet History, Technology, and Security
Introduction to Astronomy
Introduction to Finance
Introduction to Genetics and Evolution
Introduction to Genome Science
Introduction to Logic
Introduction to Mathematical Thinking
Introduction to Philosophy
Introduction to Sociology
Introduction to Sustainability
Introduction à la Programmation Objet (in French)
Introductory Human Physiology
Introductory Organic Chemistry - Part 1
Introductory Organic Chemistry - Part 2
Know Thyself
Learn to Program: Crafting Quality Code
Learn to Program: The Fundamentals
Listening to World Music
Machine Learning
Mathematical Biostatistics Bootcamp
Medical Neuroscience
Microeconomics Principles
Model Thinking
Modern & Contemporary American Poetry
Nanotechnology: The Basics
Natural Language Processing
Networked Life
Networks: Friends, Money, and Bytes
Neural Networks for Machine Learning
Neuroethics
Nutrition for Health Promotion and Disease Prevention
Planet Earth
Principles of Economics for Scientists
Principles of Obesity Economics
Probabilistic Graphical Models
Quantum Mechanics and Quantum Computation
Rationing and Allocating Scarce Medical Resources
Scientific Computing
Securing Digital Democracy
Social Network Analysis
Software Engineering for SaaS
Statistics One
The Modern World: Global History since 1760
The Social Context of Mental Health and Illness
Think Again: How to Reason and Argue
VLSI CAD: Logic to Layout
Vaccine Trials: Methods and Best Practices
Vaccines

[-]novalis12y80

Skip "Computer Vision: The Fundamentals", at least until it is seriously reworked. The videos were poorly edited, and the material was poorly paced.

I really liked Andrew Ng's machine learning course, and, on Udacity, Sebastian Thrun's AI course (although a few sections of it were unnecessary for me personally).

[-]mej1012y20

I also liked Andrew Ng's machine learning course. It is a great introduction to the ideas and techniques of the field.

I have since started diving into a more serious treatment of the topic by studying Pattern Recognition and Machine Learning by Bishop, and I will say that the knowledge from the course has definitely helped, but its main benefit was in getting me interested in the topic.

[-]Maelin12y30

I tried the Coursera Cryptography class earlier this year. The pace was quite brisk and the material was somewhat demanding - I'd recommend at least first year university mathematics. It was fairly well presented and quite interesting, and it showed a degree of polish better than Sebastian Thrun's / Peter Norvig's original AI class last year.

I had to drop out after about three weeks because I couldn't handle it along with my actual uni course, but I'm thinking of starting it again soon.

[-]mapnoterritory12y30

I'm doing now Model Thinking. It's rather slowly paced and very superficial (but also quite broad - this is fine with me, I wanted to get some overview of modeling in social sciences). I watch it on top speed while doing dishes or some other work and that way it is okay, but for sure not enough meat for "deep studying".