Probabilistic Graphical Models Courses
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.
Popular Probabilistic Graphical Models Courses and Certifications
Johns Hopkins University
Skills you'll gain: Regression Analysis, Statistical Analysis, Statistical Modeling, Logistic Regression, Data Science, Data Analysis, Statistical Methods, Model Evaluation, Predictive Modeling, Probability & Statistics, Statistical Inference, Statistical Hypothesis Testing, Probability Distribution
University of California, Santa Cruz
Skills you'll gain: Bayesian Statistics, Statistical Inference, Statistical Methods, Probability & Statistics, Statistics, Statistical Modeling, Probability, Statistical Programming, Statistical Analysis, Statistical Software, Probability Distribution, Data Analysis, R Programming, Regression Analysis, R (Software), Analytical Skills, Statistical Visualization, Predictive Modeling, Data Visualization, Data Modeling
Skills you'll gain: Time Series Analysis and Forecasting, Deep Learning, Statistical Analysis, Predictive Modeling, Statistical Methods, Forecasting, Data Preprocessing, Statistical Modeling, Statistical Machine Learning, Applied Machine Learning, Data Transformation, Model Evaluation, Unsupervised Learning, Dimensionality Reduction
Universidad Nacional Autónoma de México
Skills you'll gain: Statistical Inference, Statistical Hypothesis Testing, Probability Distribution, Sampling (Statistics), Probability & Statistics, Probability, Statistical Methods, Statistics, Statistical Modeling, Statistical Analysis, Descriptive Statistics
Imperial College London
Skills you'll gain: Generative AI, Tensorflow, Autoencoders, Generative Model Architectures, Bayesian Network, Deep Learning, Image Analysis, Bayesian Statistics, Model Optimization, Probability Distribution, Model Training, Sampling (Statistics), Data Transformation
Johns Hopkins University
Skills you'll gain: Network Analysis, Statistical Modeling, Bayesian Network, Applied Machine Learning, R (Software), R Programming, Social Network Analysis, Statistical Methods, Simulations, Network Model, Statistical Analysis, Probability & Statistics, Statistical Programming, Probability Distribution, Sampling (Statistics), Data Visualization, Machine Learning, Statistical Hypothesis Testing
Johns Hopkins University
Skills you'll gain: Statistical Inference, Statistical Hypothesis Testing, Probability & Statistics, Probability, Statistics, Bayesian Statistics, Statistical Methods, Statistical Modeling, Statistical Analysis, Probability Distribution, Sampling (Statistics), Sample Size Determination, Data Analysis
Google Cloud
Skills you'll gain: Large Language Modeling, Prompt Engineering, LLM Application, Generative AI
Birla Institute of Technology & Science, Pilani
Skills you'll gain: Data Analysis, Statistical Analysis, Statistical Methods, Analysis, Quantitative Research, Data Visualization, Predictive Modeling, Applied Mathematics
University of California, Santa Cruz
Skills you'll gain: Bayesian Statistics, Statistical Modeling, Statistical Methods, Model Evaluation, Markov Model, Statistical Analysis, Statistical Software, Sampling (Statistics), Mathematical Modeling, Regression Analysis, R Programming, Logistic Regression, Simulations, Data Analysis, Correlation Analysis, Probability Distribution
Johns Hopkins University
Skills you'll gain: R Programming, Statistical Analysis, Statistical Methods, Combinatorics, Statistical Programming, Data Analysis, Probability, Probability Distribution, Applied Machine Learning, Probability & Statistics, Bayesian Statistics, Data Science, Simulations
Coursera
Skills you'll gain: Model Optimization, Token Optimization, Model Deployment, Generative AI, Performance Tuning, Model Evaluation, Performance Testing, Cross Platform Development, PyTorch (Machine Learning Library), Memory Management, Development Environment, Hardware Architecture, Scalability
In summary, here are 10 of our most popular probabilistic graphical models courses
- Regression Models:Â Johns Hopkins University
- Bayesian Statistics: From Concept to Data Analysis:Â University of California, Santa Cruz
- Specialized Models: Time Series and Survival Analysis:Â IBM
- EstadÃstica y probabilidad: principios de Inferencia: Universidad Nacional Autónoma de México
- Probabilistic Deep Learning with TensorFlow 2:Â Imperial College London
- Computational and Graphical Models in Probability:Â Johns Hopkins University
- Statistical Inference:Â Johns Hopkins University
- Introduction to Large Language Models:Â Google Cloud
- Probability and Statistics:Â Birla Institute of Technology & Science, Pilani
- Bayesian Statistics: Techniques and Models:Â University of California, Santa Cruz
