Description:

Mathematics for AI is a comprehensive course that covers the foundational mathematical concepts and techniques used in the field of Artificial Intelligence. This course is designed to provide you with a solid understanding of the mathematical principles that underpin various AI algorithms and models.

Key Highlights:

• Gain a strong foundation in mathematical concepts relevant to AI
• Learn essential mathematical frameworks for AI, such as linear algebra, calculus, and probability theory
• Explore mathematical optimization techniques used in AI
• Understand the mathematics behind machine learning algorithms and neural networks
• Apply mathematical concepts to solve real-world AI problems

What you will learn:

• Foundations of Linear Algebra
  Learn about vectors, matrices, vector spaces, linear transformations, and eigenvalues.
• Calculus for AI
  Understand the principles of differentiation, integration, and optimization.
• Probability and Statistics
  Explore the fundamentals of probability theory and basic statistical concepts.
• Mathematical Optimization
  Discover optimization methods such as gradient descent and convex optimization.
• Mathematics for Machine Learning
  Get introduced to mathematical concepts behind machine learning algorithms and neural networks.