This course is designed to build a strong foundation in Data Science and Machine Learning. The course proceeds in 3 parts, following the Data Science Process and covers - Obtaining, processing and cleaning data; Exploratory Data Analysis; and Modelling, including classification and recommendation engines.

This course builds on the fundamentals taught in ML-1. We continue our modeling journey from DS-1 with tree-based models: these have proved to be the best models outside of deep learning. Specifically, we focus on Random Forests and Boosting. We then move on to key Bayesian and other statistical concepts that help us qualify the uncertainty in the prediction of our models, and help us make decisions.

The objective of this module is to provide fundamental understandings of machine learning models and get you working with the basic concepts of ML and AI. You will start with the regression models (KNN, Linear, Multi, Poly) and then move on to classification models (kNN, Logistic). Finally, the course will provide a basic understanding of modern neural networks.

This course is a follow up to AI-1. The objective of this module is to provide you, the student, with a deeper intuition and understanding of neural networks including network architecture choices, activation functions, feed-forward, convolutional neural networks and auto-encoders. At the end of this course, you will be able to run a variety of advanced machine learning models, and learn to apply them to practical image recognition problems.

The objective of this advanced course is to provide fundamental understanding of the concepts behind Generative Models and Reinforcement Learning and apply them to real world problems. The first half of the course starts with generative models and covers autoencoders, variational autoencoders and Generative Adversarial Networks. The second half of the course takes you to Reinforcement Learning.

This is a 12-16 week Capstone project or Internship for those who have completed AI Y, or have equivalent preparation to join this course directly. At the end of AI Z you will be proficient at learning and applying cutting-edge skills to solve real-world problems. You will be well prepared for top employment opportunities worldwide. This course is available as a stand alone micro-certification with a state-of-the art-employment guarantee for high scorers. Direct admission (for those who have not taken the AI-Y module) with employment guarantee is via an examination and interview.