Learn about artificial intelligence: Understand how to build systems that can learn and make decisions.
This course will provide an introduction to artificial intelligence (AI) and its applications. You will learn about the fundamentals of AI, including machine learning algorithms, and how to build systems that can learn and make decisions. You will also explore the ethical implications of AI and its potential impact on society.
Within artificial intelligence (AI), explainable AI (XAI), generally overlapping with interpretable AI or explainable machine learning (XML), is a field of research that explores methods that provide humans with the ability of intellectual oversight over AI algorithms. The main focus is on the reasoning behind the decisions or predictions made by the AI algorithms, to make them more understandable and transparent. This addresses users' requirement to assess safety and scrutinize the automated decision making in applications. XAI counters the "black box" tendency of machine learning, where even the AI's designers cannot explain why it arrived at a specific decision.