The purpose of this series of courses is to teach the basics of Computational Statistics for the purpose of performing inference to aspiring or new Data Scientists. This is not intended to be a comprehensive course that teaches the basics of statistics and probability nor does it cover Frequentist statistical techniques based on the Null Hypothesis Significance Testing (NHST)
WHAT YOU WILL LEARN
Coursera
Discover the power of Bayesian statistics in this beginner-friendly online course. Start from the basics of probability and delve into advanced Bayesian modeling and inference techniques. Perfect for aspiring or new data scientists looking to expand their expertise with Python and Jupyter notebooks.
Coursera
Dive into the world of Bayesian statistics with 'Bayesian Inference with MCMC' on Coursera. This course is designed to equip you with essential skills in Markov Chain Monte Carlo (MCMC) methods for performing complex Bayesian analyses. Starting from the basics, you'll learn how to apply these algorithms effectively using Python and Jupyter notebooks, focusing on PyMC3 for practical Bayesian modeling.
Coursera
Dive into the world of Bayesian modeling and inference with our expert-led Introduction to PyMC3 course. Learn how to harness the power of PyMC3, a Python library designed for probabilistic programming, to tackle complex statistical problems effectively. This course is perfect for data scientists, statisticians, and anyone interested in expanding their knowledge in scalable Bayesian analysis.