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

Duke University
Intermediate · Course · 1 - 3 Months

University of Colorado Boulder
Build toward a degree
Intermediate · Course · 1 - 4 Weeks

Arizona State University
Intermediate · Course · 1 - 4 Weeks

DeepLearning.AI
Intermediate · Course · 1 - 4 Weeks

Duke University
Intermediate · Course · 1 - 3 Months

Dartmouth College
Build toward a degree
Intermediate · Course · 1 - 3 Months

Lund University
Beginner · Course · 1 - 3 Months

University of California San Diego
Mixed · Course · 1 - 3 Months

University of Minnesota
Beginner · Course · 1 - 4 Weeks

Beginner · Course · 1 - 4 Weeks

École Polytechnique Fédérale de Lausanne
Advanced · Course · 1 - 3 Months