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  • Probabilistic Graphical Models

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


  • Status: Free
    Free
    D

    DeepLearning.AI

    Knowledge Graphs for RAG

    Skills you'll gain: LangChain, Large Language Modeling, Query Languages, Data Storage, Semantic Web, Unstructured Data, Graph Theory, Text Mining

    4.7
    Rating, 4.7 out of 5 stars
    ·
    88 reviews

    Intermediate · Project · Less Than 2 Hours

  • Status: Free Trial
    Free Trial
    U

    University of Washington

    Practical Predictive Analytics: Models and Methods

    Skills you'll gain: Unsupervised Learning, Supervised Learning, Predictive Analytics, Statistical Modeling, R Programming, Statistical Methods, Decision Tree Learning, Statistical Inference, Statistical Analysis, Machine Learning Algorithms, Machine Learning, Graph Theory, Probability & Statistics, Network Analysis, Big Data, Sampling (Statistics), Random Forest Algorithm

    4.1
    Rating, 4.1 out of 5 stars
    ·
    323 reviews

    Mixed · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    U

    University of California, Santa Cruz

    Bayesian Statistics: Mixture Models

    Skills you'll gain: R Programming, Statistical Modeling, Bayesian Statistics, Statistical Software, Markov Model, Mathematical Modeling, Statistical Methods, Probability & Statistics, Unsupervised Learning, Machine Learning Algorithms

    4.5
    Rating, 4.5 out of 5 stars
    ·
    62 reviews

    Intermediate · Course · 1 - 3 Months

  • Status: New
    New
    Status: Preview
    Preview
    E

    EDUCBA

    Logistic Regression with R: Build & Predict

    Skills you'll gain: Predictive Modeling, R Programming, Feature Engineering, Statistical Modeling, Risk Modeling, Classification And Regression Tree (CART), Regression Analysis, Predictive Analytics, Machine Learning Methods, Data Processing, Supervised Learning, Performance Measurement, Credit Risk, Dimensionality Reduction

    Mixed · Course · 1 - 4 Weeks

  • Status: New
    New
    Status: Free Trial
    Free Trial
    S

    Simplilearn

    Attention Mechanisms and Transformer Models Course

    Skills you'll gain: Generative Model Architectures, Generative AI, OpenAI, Large Language Modeling, Prompt Engineering, Artificial Neural Networks, Deep Learning, Natural Language Processing, Machine Learning Methods

    Beginner · Course · 1 - 4 Weeks

  • Status: Free
    Free
    D

    DeepLearning.AI

    How Diffusion Models Work

    Skills you'll gain: Generative AI, Generative Model Architectures, Jupyter, Prompt Engineering, Sampling (Statistics), Artificial Neural Networks, Algorithms

    4.6
    Rating, 4.6 out of 5 stars
    ·
    273 reviews

    Intermediate · Project · Less Than 2 Hours

  • Status: Free Trial
    Free Trial
    E

    Edureka

    Predictive Modeling with Python

    Skills you'll gain: Predictive Modeling, Predictive Analytics, Statistical Methods, Data Analysis, Statistical Analysis, Machine Learning, Scikit Learn (Machine Learning Library), Machine Learning Algorithms, Python Programming, Data Manipulation, Pandas (Python Package), NumPy

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    U

    University of Michigan

    Fitting Statistical Models to Data with Python

    Skills you'll gain: Statistical Modeling, Statistical Methods, Bayesian Statistics, Statistical Inference, Statistical Software, Statistical Programming, Regression Analysis, Predictive Modeling, Jupyter, Exploratory Data Analysis, Correlation Analysis, Probability Distribution, Python Programming, Data Visualization Software

    4.4
    Rating, 4.4 out of 5 stars
    ·
    713 reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    S

    SAS

    Modeling Time Series and Sequential Data

    Skills you'll gain: Time Series Analysis and Forecasting, SAS (Software), Forecasting, Regression Analysis, Applied Machine Learning, Statistical Analysis, Advanced Analytics, Statistical Methods, Predictive Modeling, Statistical Modeling, Bayesian Statistics, Artificial Neural Networks

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    J

    Johns Hopkins University

    What are the Chances? Probability and Uncertainty in Statistics

    Skills you'll gain: Statistics, Regression Analysis, Probability, Statistical Hypothesis Testing, Probability Distribution, Statistical Analysis, Statistical Inference, Sampling (Statistics), Combinatorics

    4.6
    Rating, 4.6 out of 5 stars
    ·
    18 reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    P

    Packt

    Natural Language Processing - Probability Models in Python

    Skills you'll gain: Cryptography, Generative Model Architectures, Probability Distribution, Machine Learning Algorithms, Algorithms

    Intermediate · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    I

    Illinois Tech

    Bayesian Computational Statistics

    Skills you'll gain: Bayesian Statistics, Data Analysis, Statistical Inference, Regression Analysis, Statistical Analysis, Statistical Modeling, Statistical Programming, Statistical Software, R Programming, Markov Model, Probability, Simulations, Probability Distribution

    Build toward a degree

    Intermediate · Course · 1 - 3 Months

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1…678…290

In summary, here are 10 of our most popular probabilistic graphical models courses

  • Knowledge Graphs for RAG: DeepLearning.AI
  • Practical Predictive Analytics: Models and Methods: University of Washington
  • Bayesian Statistics: Mixture Models: University of California, Santa Cruz
  • Logistic Regression with R: Build & Predict: EDUCBA
  • Attention Mechanisms and Transformer Models Course: Simplilearn
  • How Diffusion Models Work: DeepLearning.AI
  • Predictive Modeling with Python : Edureka
  • Fitting Statistical Models to Data with Python: University of Michigan
  • Modeling Time Series and Sequential Data: SAS
  • What are the Chances? Probability and Uncertainty in Statistics: Johns Hopkins University

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