Course: mathematical foundation for AI engineers. This course is designed to provide AI engineers with a comprehensive understanding of the mathematical foundations of artificial intelligence. The curriculum covers essential topics in linear algebra, calculus, probability, statistics, and optimization, with a focus on their applications in machine learning and deep learning. Module 1: Linear Algebra for AI (4 weeks)
Module 2: Calculus for AI (4 weeks)
Module 3: Probability and Statistics for AI (4 weeks)
Module 4: Optimization Techniques for AI (4 weeks)
Module 5: Specialized Mathematical Topics in AI (4 weeks)
Course Assessment: * Quizzes and assignments (40%): Weekly quizzes and assignments will assess the engineers’ understanding of mathematical concepts. * Project (30%): A final project will require engineers to apply mathematical techniques to a real-world AI problem. * Class participation and engagement (30%): Engineers are expected to actively participate in class discussions, ask questions, and provide feedback.
Target Audience: * AI engineers and researchers who want to deepen their understanding of mathematical foundations in AI * Data scientists and machine learning practitioners seeking to improve their mathematical skills * Anyone interested in developing a strong foundation in mathematics for AI applications