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.

Intermediate · Course · 1 - 4 Weeks

Coursera
Intermediate · Course · 1 - 4 Weeks

★ 4.8 (459) · Intermediate · Course · 1 - 3 Months

Johns Hopkins University
★ 4.4 (3.4K) · Mixed · Course · 1 - 4 Weeks

Coursera
Intermediate · Course · 1 - 3 Months

H2O.ai
★ 3.6 (14) · Intermediate · Specialization · 3 - 6 Months

University of California, Santa Cruz
★ 4.8 (497) · Intermediate · Course · 1 - 3 Months

Google Cloud
★ 4.5 (1.4K) · Beginner · Course · 1 - 4 Weeks

Google Cloud
★ 4.1 (125) · Advanced · Course · 1 - 4 Weeks

Coursera
Intermediate · Course · 1 - 4 Weeks

University of Pittsburgh
Beginner · Course · 1 - 4 Weeks

Johns Hopkins University
Intermediate · Course · 1 - 3 Months