Approaches for statistical inference -- The Bayes approach -- Bayesian computation -- Model criticism and selection -- The empirical Bayes approach -- Bayesian design -- Special methods and models -- ...

In the announcement, FDA Commissioner Mackary said, “Bayesian methodologies help address two of the biggest problems of drug ...

Articulate the primary interpretations of probability theory and the role these interpretations play in Bayesian inference Use Bayesian inference to solve real-world statistics and data science ...

This course offers a rigorous yet practical exploration of Bayesian reasoning for data-driven inference and decision-making. Students will gain a deep understanding of probabilistic modeling, and ...

This course focuses on experimental design and applied statistical methods for data analysis. Students will learn how to design and interpret experiments considering multiple variables, avoiding ...

Innovative technologies of the Fourth Industrial Revolution (4IR) are transforming and modernizing the way data is generated, collected, and analyzed across different industries and fields of study. 1 ...

In recent years, JupyterLab has rapidly become the tool of choice for data scientists, machine learning (ML) practitioners, and analysts worldwide. This powerful, web-based integrated development ...