Stanford University Coursera course taught by Andrew NG
The syllabus include the following
Week 1 :- Linear Regression with One Variable
Week 2 :- Linear Regression with Multiple Variables
Week 3 :- Logistic Regression and Regularization
Week 4 :- Neural Networks: Representation
Week 5 :- Neural Networks: Learning
Week 6 :- Advice for Applying Machine Learning and Machine Learning System Design
Week 7 :- Support Vector Machines
Week 8 :- Unsupervised Learning and Dimensionality Reduction
Week 9 :- Anomaly Detection and Recommender Systems
Week 10:- Large Scale Machine Learning
Week 11:- Application Example: Photo OCR