Computational and Graphical Models in Probability
Completed by Mikaela Aghajanyan
August 24, 2025
15 hours (approximately)
Mikaela Aghajanyan's account is verified. Coursera certifies their successful completion of Computational and Graphical Models in Probability
What you will learn
Master techniques for simulating random variables, including the Inverse Transformation and Rejection Methods using R programming.
Analyze complex networks using Exponential Random Graph Models to model and interpret social structures and their dependencies.
Understand and apply probabilistic graphical models, including Bayesian networks, to reason about uncertainty and infer relationships in data.
Skills you will gain
- Category: Network Analysis
- Category: Simulations
- Category: Statistical Methods
- Category: Probability Distribution
- Category: Applied Machine Learning
- Category: Data Visualization
- Category: Sampling (Statistics)
- Category: Bayesian Network
- Category: Network Model
- Category: R (Software)
- Category: Statistical Programming
- Category: Statistical Modeling
