As a serial MOOCist I cannot single out any one so here is a list per domain.
Data Science
Introduction to Probability - The Science of Uncertainty,math oriented MIT/EDX
Difficulty:5/5 Videos:5/5 Material and exercises:5/5 Usefulness: 5/5
Learning from Data, math oriented formerly Caltech/EDX now on caltech, check the exercises and you will see the difference in quality with Andrew Ng:
Difficulty:4/5 Videos:4:5 Material and exercises:5:5 Usefulness:3/5
The Analytics Edge - Bertsimas MIT/EDX.You will learn practical stuff in R includes a kaggle competition.
Difficulty:3/5 Videos:4/5 Material and exercises:6/5 Usefulness:6/5
Computational Probability and Inference MIT/EDX Computational probabilty using python.
Difficulty:2/5 Videos:3/5 Material and exercises:6/5 Usefulness:5/5
Basic Modeling for Discrete Optimization: Uses an easy to learn language called minizinc which has multiple backends and is useful for those types of problems. VERY pleasant to watch videos.
Difficulty:2/5 Videos:4/5 Material and exercises:3/5 Usefulness:5/5
Deep learning: deeplearning.ai coursera and fast.ai for more practical stuff.
Non data science:
I have not done the exercises on these just watched them:
Learning how to learn: Life changing I wish it existed many years ago.
Influencing People: Puts things into perspective. Makes you ponder about morality
Roman Architecture: Includes the "why" it is like the old "who moved my cheese" book, but in roman architecture edition.
Explaining European Paintings, 1400 to 1800: What it says on the tin.
Economics of money and Banking: In all tuthe courses I have listed the professors are very good. But this guy.... Makes a difficult subject so approachable and watching the news becomes as painful as watching a train full of passengers going to broken bridge
I am sure I have forgotten others
MOOCs have changed my life, financially and in other ways. I thank all the people involved.
I was a mech eng manager in industrial automation. Did the MOOCs, chose a domain, started a phd in ML and AI by showing my MOOC results, got picked during the 3rd year from one of the big consulting companies, now running a series of international projects. Banking(IT only), AI, CompVision and Analytics.
Data Science
Introduction to Probability - The Science of Uncertainty,math oriented MIT/EDX Difficulty:5/5 Videos:5/5 Material and exercises:5/5 Usefulness: 5/5
Learning from Data, math oriented formerly Caltech/EDX now on caltech, check the exercises and you will see the difference in quality with Andrew Ng: Difficulty:4/5 Videos:4:5 Material and exercises:5:5 Usefulness:3/5
The Analytics Edge - Bertsimas MIT/EDX.You will learn practical stuff in R includes a kaggle competition. Difficulty:3/5 Videos:4/5 Material and exercises:6/5 Usefulness:6/5
Computational Probability and Inference MIT/EDX Computational probabilty using python. Difficulty:2/5 Videos:3/5 Material and exercises:6/5 Usefulness:5/5
Basic Modeling for Discrete Optimization: Uses an easy to learn language called minizinc which has multiple backends and is useful for those types of problems. VERY pleasant to watch videos. Difficulty:2/5 Videos:4/5 Material and exercises:3/5 Usefulness:5/5
Deep learning: deeplearning.ai coursera and fast.ai for more practical stuff.
Non data science:
I have not done the exercises on these just watched them:
Learning how to learn: Life changing I wish it existed many years ago.
Influencing People: Puts things into perspective. Makes you ponder about morality
Roman Architecture: Includes the "why" it is like the old "who moved my cheese" book, but in roman architecture edition.
Explaining European Paintings, 1400 to 1800: What it says on the tin.
Economics of money and Banking: In all tuthe courses I have listed the professors are very good. But this guy.... Makes a difficult subject so approachable and watching the news becomes as painful as watching a train full of passengers going to broken bridge
I am sure I have forgotten others
MOOCs have changed my life, financially and in other ways. I thank all the people involved.