Courses & TutorialsProgramming
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