teaching

Modern Statistics for Engineers

This course covers fundamentals of modern statistics and its applications in different engineering disciplines. The focus is on understanding and implementing different statistical concepts and utilizing Python programming to solve real-word problems. These include Probability, Probabilistic Models, Bayesian versus Frequentist Statistics, Density Estimation, Clustering, Classification, Kernel Methods, Gaussian Processes, Optimization, Error Estimation, Markov Processes, Monte Carlo and MCMC Inference.