Awesome Machine Learning Courses

The following is a list of free or paid online courses on machine learning, statistics, data-mining, etc.

Machine-Learning / Data Mining

• Artificial Intelligence (Columbia University) – free
• Machine Learning (Columbia University) – free
• Machine Learning (Stanford University) – free
• Neural Networks for Machine Learning (University of Toronto) – free. Also available on YouTube as a playlist. #This course is no longer available on Coursera.
• Deep Learning Specialization (by Andrew Ng, deeplearning.ai) – Courses: I Neural Networks and Deep Learning; II Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; III Structuring Machine Learning Projects; IV Convolutional Neural Networks; V Sequence Models; Paid for grading/certification, financial aid available, free to audit
• Deep Learning Nano Degree on Udacity – $
• Intro to Deep Learning (MIT)
• Stanford’s CS20 Tensorflow for Deep Learning Research
• fast.ai – deep learning MOOC
• Machine Learning Specialization (University of Washington) – Courses: Machine Learning Foundations: A Case Study Approach, Machine Learning: Regression, Machine Learning: Classification, Machine Learning: Clustering & Retrieval, Machine Learning: Recommender Systems & Dimensionality Reduction,Machine Learning Capstone: An Intelligent Application with Deep Learning; free
• Machine Learning Course (2014-15 session) (by Nando de Freitas, University of Oxford) – Lecture slides and video recordings.
• Learning from Data (by Yaser S. Abu-Mostafa, Caltech) – Lecture videos available
• Intro to Machine Learning – free
• Probabilistic Graphical Models (by Prof. Daphne Koller, Stanford) Coursera Specialization
• Reinforcement Learning Course (by David Silver, DeepMind) – YouTube playlist and lecture slides.
• Keras in Motion $
• Stanford’s CS231n: CNNs for Visual Recognition – Spring 2017 iteration, instructors (Fei-Fei Li, Justin Johnson, Serena Yeung), or Winter 2016 edition instructors (Fei-Fei Li, Andrej Karpathy, Justin Johnson). Course website has supporting material.
• University of California, Berkeley’s CS294: Deep Reinforcement Learning – Fall 2017 edition. Course website has lecture slides and other related material.
• Machine Learning (Georgia Tech) on Udacity – free
• Reinforcement Learning (Georgia Tech) on Udacity – free
• Machine Learning for Trading – free
• Mining of Massive Datasets (YouTube playlist) – Course website has info about accompanying book, free chapters, and Stanford’s MOOC
• Machine Learning Crash Course (Google) – free
• Machine Learning Mini Bootcamp Course (LambdaSchool) – free and $
• Microsoft Professional Program for Artificial Intelligence – free
• Open Machine Learning Course with articles on Medium
• Machine Learning A-Z (Udemy) – Hands-On Python & R In Data Science
• Deep Learning Crash Course – $
• Reinforcement Learning in Motion – $
• Udemy A-Z Machine learning course – $
• Statistics and Probability-Khan Academy – free
• Math and Architectures of Deep Learning – $
• Deep Learning with Python, Second Edition – $
• Transfer Learning for Natural Language Processing – $
• Grokking Artificial Intelligence Algorithms – $
• Learn ML from experts at Google – free
• Kaggle courses on ML,AI and DS(certificate) – free
• Ml with python(Cognitive classes) – free
• Intro to Data science(Cognitive classes) – free
• Machine Learning for Business – $
• Transfer Learning for Natural Language Processing – $
• In-depth introduction to machine learning in 15 hours of expert videos (by Prof. Trevor Hastie, Prof. Rob Tibshirani, Stanford) – free
• Data Scientist in Python (Dataquest) – free and $
• AI Expert Roadmap – Roadmap to becoming an Artificial Intelligence Expert – free
• Semi-Supervised Deep Learning with GANs for Melanoma Detection – $
• Interpretable AI – $
• Deploying a Deep Learning Model on Web and Mobile Applications Using TensorFlow – $ Hands-on project