Machine Learning Courses

Numpy and Pandas

• Udacity's Intro to Data Analysis
• Deep Learning Prerequisites: The Numpy Stack in Python
• Lynda.com
• Youtube.com
• Stanford CS 231n tutorial

Linear Algebra

• Gilbert Strang MIT Course
• Coding the Matrix
• fast.ai computational linear algrebra

Calculus/Optimization

• Convex Optimization
• Essence of Calculus
• Deterministic Optimization
• Multivariate Calculus on Khan Academy or MIT OCW

Statistics

• Stanford: Probability and Statistics (Big Picture of Statistics)
• MIT: Statistics for Application (Renamed Fundamentals of Statistics in 2017)
  • The book for this class is All of Statistics which is supposed to help Computer Scientists quickly learn statistics
• Think Stats and Think Bayes actually look really good!

Probability

• Harvard's Stats 110
• Probabalistic Graphical Models Specialization

Data Science

• Havard's CS109: Data Science

Data Visualization

• D3.js
• Matplotlib on YouTube

Data Mining

• Mining Massive Data Sets

Machine Learning

• CS229: Machine Learning
• Caltech Learning From Data
• Stanford: Statistical Learning
• Advanced Machine Learning Specialization
• GA Tech: Reinforcement Learning
• fast.ai machine learning course
• kaggle learn courses

Deep Learning

• CS230: Deep Learning
• CS231n: Convolutional Neural Networks for Visual Recognition
• CS224n: Natural Language Processing with Deep Learning
• fast.ai two 7-week courses
• Nerual Networks for Machine Learning
• UC Berkeley CS 294 Deep Reinforcement Learning

Artificial Intelligence

• CS221: Artificial Intelligence: Principles and Techniques

Big Data

• Mining Massive Data Sets

• Coursera Specialization

• Practical learning resources include dataquest.io, datacamp.com, machinelearningmastery.com, fast.ai, think stats, think bayes, kaggle learn and more.

Additional topics that could be added are cloud computing, more big data courses, and algorithm courses