Foundations of Mathematics for Artificial Intelligence

Mathematics is integral to the development of AI, serving as the foundation for the algorithms, models, and methodologies that enable machines to process and analyze vast amounts of data. Consequently, for professionals looking to understand, design, and leverage AI systems, a deep understanding of the mathematical concepts powering the field is essential. 
 
In this dynamic, first-of-its-kind program, you’ll take a deep dive into the mathematics that makes advanced computational technologies possible. Alongside accomplished global peers, you’ll explore a range of topics from various mathematical subfields—from linear algebra to analysis to optimization to machine learning theory—and discover how these concepts relate to widely used machine learning models and associated Python code. You’ll emerge with a solid foundation in the mathematics of AI—and the skills you need to excel in any AI-focused professional course or job.

• Explore the key mathematical concepts that power the development of AI algorithms and models
• Learn how to formulate mathematical problems as machine learning problems
• Acquire a deeper understanding of machine learning models, including their strengths and limitations
• Discover how to modify advanced machine learning models
• Understand how to reduce risk in the machine learning-developmental cycle

This course is designed for participants who have a bachelor's degree (at a minimum) and at least three years of professional experience in any computation-driven industry. Professionals who will particularly benefit from the curriculum include:

• Machine learning scientists
• Machine learning engineers
• Data scientists
• Research and development engineers
• Technical leads
• Technical managers
• Quantitative analysts