- https://www.coursera.org/specializations/mathematics-machine-learning (Free to Audit)
- https://www.khanacademy.org/math/linear-algebra
- https://www.khanacademy.org/math/differential-calculus
- https://www.khanacademy.org/math/statistics-probability
- https://www.udacity.com/course/statistics--st095
- https://www.coursera.org/specializations/python? (Free to Audit)
- https://www.udemy.com/course/complete-python-bootcamp/ (Paid but worth buying)
- https://www.datacamp.com/ (Free subscription available through github student developer pack)
- https://www.youtube.com/playlist?list=PLQVvvaa0QuDeAams7fkdcwOGBpGdHpXln
- Python for Data Analysis (not free worth buying)
- Data Analysis with Python IBM (Free to Audit)
- Python for Research by HarvardX (Free to Audit)
- Python for Data Analysis (By Creater of Pandas Library)
- Python Data Science HandBook
- Machine Learning Coursera
- Deep Learning Specilzation (Free to Audit)
- CS 224 Natural Language Processing by Stanford
- CS 231 Conv Neural Networks
- CS 232 Digital Image Processing
- CS 234 Reinforcment Learning
- TensorFlow in Practice (By deeplearning.ai free to audit)
- Advanced Machine Learning with TensorFlow on Google Cloud Platform Specialization (Free to Audit)
- Complete Guide to Tensorflow for deeplearning (Worth Buying)
- Intro to Deep Learning with PyTorch
- PyTorch DataCamp (free via Github Student Pack)
- PyTorch for DeepLearning BootCamp (Worth buying)
- Grokking Deep Learning (well explained concepts with good figures)
- Make your own Neural Network (A book by an author which most people do not know but trust me this is one of the best book on Neural Networks)