ML Learning Road Map

This is my planned learning roadmap of online courses covering topics I’m interested in exploring related to ML.

My goal is to complete most of these by my 25th birthday on July 4, 2020.

Update 7-10-19: Added more courses that are just released by Udacity and Coursera (Data Engineer Nanodegree and Tensorflow Specialization)

Update 7-22-19: Finished Sequence Models course

Update 11-24-19: Finished ConvNet course

• Coursera’s Machine Learning (Andrew Ng)
• Coursera’s Deep Learning Specialication (Andrew Ng):
  • Neural Networks and Deep Learning
  • Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization (IN PROGRESS)
  • Structuring Machine Learning Projects (IN PROGRESS)
  • Convolutional Neural Networks
  • Sequence Models
• Coursera’s Tensorflow in Practice Specialization
• fast.ai courses:
  • Introduction to Machine Learning for Coders
  • Practical Deep Learning for Coders
  • Cutting Edge Deep Learning for Coders
  • Computational Linear Algebra
• Udacity’s Data Engineer Nanodegree
• MIT 6.S094: Deep Learning for Self-Driving Cars (Lex Fridman)
• Stanford 224d: Deep Learning for Natural Language Processing (Richard Socher)
• Coursera’s Probabilistic Graphical Models Specialization (Daphne Koller)
  • PGM 1: Representation
  • PGM 2: Inference
  • PGM 3: Learning