Probabilistic Graphical Models courses can help you learn Bayesian networks, Markov random fields, and inference algorithms. You can build skills in modeling uncertainty, reasoning under uncertainty, and making predictions based on incomplete data. Many courses introduce tools like TensorFlow Probability and PyMC3, which are used for implementing these models and performing complex calculations, enabling you to apply your knowledge to real-world data analysis and machine learning tasks.

Coursera
Intermediate · Course · 1 - 4 Weeks

DeepLearning.AI
Intermediate · Course · 1 - 4 Weeks

Advanced · Course · 1 - 3 Months

University of California, Santa Cruz
Intermediate · Course · 1 - 3 Months

University of Minnesota
Mixed · Course · 1 - 4 Weeks

Imperial College London
Advanced · Course · 1 - 3 Months

Coursera
Intermediate · Course · 1 - 4 Weeks

University of Colorado Boulder
Build toward a degree
Intermediate · Course · 1 - 3 Months

Amazon Web Services
Beginner · Course · 1 - 4 Weeks
University of Michigan
Intermediate · Course · 1 - 3 Months
Duke University
Beginner · Course · 1 - 4 Weeks

Coursera
Intermediate · Course · 1 - 4 Weeks