Introduction -- Introduction to AI and ML -- Essential Concepts in Artificial Intelligence and Machine Learning -- Data Understanding, Representation, and Visualization -- Linear Methods -- Perceptron and Neural Networks -- Decision Trees -- Support Vector Machines -- Probabilistic Models -- Dynamic Programming and Reinforcement Learning -- Evolutionary Algorithms -- Time Series Models -- Deep Learning -- Emerging Trends in Machine Learning -- Unsupervised Learning -- Featurization -- Designing and Tuning -- Model Pipelines -- Performance Measurement -- Classification -- Regression -- Ranking -- Recommendations Systems -- Azure Machine Learning -- Open Source Machine Learning Libraries -- Amazon's Machine Learning Toolkit: Sagemaker -- Conclusion.