The Course Structure

This course consists of the following modules:

Introduction To Artificial Intelligence: a general introduction to artificial intelligence and the various subdomains like computer vision and natural language processing. This introduction is also covered in the Azure AI Fundamentals course and will count towards your preparation for the AI-900 certification exam.

Loading And Processing Data: this module will teach you how to perform Feature Engineering by processing raw data from a machine learning dataset and prepare it for AI training.

Regression: in this module we will dive into the world of regression, which is the act of using a machine learning model to make numerical predictions for a dataset. We'll look at the mathematical background of regression, and how to evaluate regression results to determine if they are accurate.

Binary Classification: in this module you'll learn how to train a machine learning model to make binary yes/no predictions. Just like with regression, we'll look at the mathematics behind classification and determine how to evaluate classification results.

Multi-class Classification: we'll conclude the course by looking at multi-class classification models, which generate categorical predictions with more than two possible outcomes.

Each module starts with an introduction and continues with a set of 5-minute video lessons that explain a specific topic. Then there's a recap to summarize everything you've learned, and a quiz to test your knowledge. The module concludes with a lab exercise that will show you how to implement what you just learned by building an ML.NET machine learning application in C#.

And at the end of the course, there's a course recap with a summary of everything you've learned throughout the entire course.