Advanced Bioengineering II: Theory, Computation, & Analysis

This course covers theoretical and computational principles, tools, and techniques essential for bioengineers, including: 1. Mathematical Frameworks in Bioengineering: Covers biomolecular kinetics, ordinary differential equation models, and reaction-diffusion. 2. Molecular Simulation Techniques: Includes stochastic and deterministic methods. 3. Practical Approaches Using Python and MATLAB: Focuses on data analysis, coding (with key packages), classical machine learning, and image processing. 4. Fundamentals of AI/ML: Addresses supervised and unsupervised learning, neural networks, and Poisson distributions.