The instructor explains complex ideas in a straightforward way. This course truly elevates experimentation skills.

A professionally designed course that delivers real value. Bayesian concepts are explained clearly, and the Excel-to-Python A/B testing workflow feels intuitive and industry-relevant.

An impressive course that balances theory and application, empowering learners to confidently perform Bayesian A/B testing from spreadsheets to Python scripts.

Mastering Bayesian methods here gave me the edge in my senior analyst interview. The focus on real-world uncertainty is a game-changer for business strategy.

This course transformed my understanding of A/B testing by introducing Bayesian methods through simple Excel models before advancing into Python analysis.

It transformed my understanding of uncertainty in experiments. Moving from Excel tables to PyMC models felt like a natural, powerful progression for me.

It transforms complex Bayesian ideas into actionable insights and smoothly guides learners from spreadsheet analysis to Python-based experimentation.

A transformative course for analysts seeking modern experimentation techniques. Bayesian thinking feels intuitive after this training.

The transition into Python for hierarchical modeling is exactly what is needed for modern, scalable healthcare data science projects.

The transition from spreadsheets to Python coding is seamless, making Bayesian A/B testing accessible and highly practical.

Good course to understand theory intuitively, but Pymc package being used is outdated , so commands won't work with new Pymc package