The following is a list of free or paid online courses on machine learning, statistics, data-mining, etc.
- 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
- Amazon's MLU-Explain - Visual, Interactive Explanations of Core Machine Learning Concepts
- 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
- Complete Data Science and ML Course - $