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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


  • D

    Duke University

    Bayesian Statistics

    Skills you'll gain: Bayesian Statistics, Statistical Hypothesis Testing, Statistical Modeling, Statistical Methods, Statistical Inference, Statistical Programming, Statistical Analysis, Probability & Statistics, Regression Analysis, Data Analysis, R Programming, Statistical Software, Probability, Data-Driven Decision-Making, Predictive Modeling, Model Evaluation, Probability Distribution

    3.8
    Rating, 3.8 out of 5 stars
    ·
    798 reviews

    Intermediate · Course · 1 - 3 Months

  • G

    Google Cloud

    Transformer Models and BERT Model

    Skills you'll gain: Large Language Modeling, Natural Language Processing, Generative Model Architectures, Transfer Learning

    4.1
    Rating, 4.1 out of 5 stars
    ·
    125 reviews

    Advanced · Course · 1 - 4 Weeks

  • Status: New
    New
    Status: Free Trial
    Free Trial
    C

    Coursera

    Grow Trees & Powerful Ensembles

    Skills you'll gain: Classification And Regression Tree (CART), Model Deployment, Model Optimization, Decision Tree Learning, Predictive Modeling, Model Evaluation, Model Training, Predictive Analytics, Machine Learning Methods, Random Forest Algorithm, Applied Machine Learning, Data-Driven Decision-Making, Performance Tuning, Feasibility Studies, Scikit Learn (Machine Learning Library), Data Visualization, Performance Analysis, Statistical Methods, Cost Benefit Analysis, Performance Measurement

    Intermediate · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    D

    DeepLearning.AI

    Sequence Models

    Skills you'll gain: Recurrent Neural Networks (RNNs), Hugging Face, Natural Language Processing, Generative AI, Artificial Neural Networks, Embeddings, Large Language Modeling, Deep Learning, Transfer Learning, Fine-tuning, Data Preprocessing

    4.8
    Rating, 4.8 out of 5 stars
    ·
    31K reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    U

    University of Glasgow

    Explainable deep learning models for healthcare - CDSS 3

    Skills you'll gain: Autoencoders, Model Evaluation, Deep Learning, Recurrent Neural Networks (RNNs), Applied Machine Learning, Machine Learning, Convolutional Neural Networks, Electocardiography, Artificial Neural Networks

    4.6
    Rating, 4.6 out of 5 stars
    ·
    15 reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    D

    DeepLearning.AI

    Build Better Generative Adversarial Networks (GANs)

    Skills you'll gain: Generative Adversarial Networks (GANs), Generative AI, Generative Model Architectures, PyTorch (Machine Learning Library), Model Training, Model Evaluation, Responsible AI, Data Ethics, Machine Learning, Image Quality

    4.7
    Rating, 4.7 out of 5 stars
    ·
    685 reviews

    Intermediate · Course · 1 - 4 Weeks

  • U

    University of Colorado Boulder

    Introduction to Bayesian Statistics for Data Science

    Skills you'll gain: Bayesian Statistics, Statistical Inference, Statistical Modeling, Predictive Analytics, Predictive Modeling, Statistical Methods, Data Ethics, Data Science, Probability, Regression Analysis, Probability Distribution

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    U

    University of California, Santa Cruz

    Bayesian Statistics: Time Series Analysis

    Skills you'll gain: Time Series Analysis and Forecasting, Forecasting, Bayesian Statistics, R Programming, Statistical Analysis, Statistical Modeling, R (Software), Regression Analysis, Statistical Methods, Data Analysis, Correlation Analysis, Model Evaluation, Probability Distribution

    4.3
    Rating, 4.3 out of 5 stars
    ·
    18 reviews

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    U

    University of Colorado Boulder

    Discrete-Time Markov Chains and Monte Carlo Methods

    Skills you'll gain: Artificial Intelligence, Machine Learning Methods, Generative AI, Machine Learning Algorithms, Mathematical Theory & Analysis

    Build toward a degree

    4.8
    Rating, 4.8 out of 5 stars
    ·
    12 reviews

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    J

    Johns Hopkins University

    Computational and Graphical Models in Probability

    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

    Intermediate · Course · 1 - 4 Weeks

  • Status: New
    New
    Status: Free Trial
    Free Trial
    A

    Arizona State University

    Bayesian Statistical Concepts and Methods

    Skills you'll gain: Bayesian Statistics, Statistical Modeling, Bayesian Network, Statistical Methods, Statistical Analysis, Data Analysis, R (Software), Statistical Programming, R Programming, Data-Driven Decision-Making, Statistical Inference, Markov Model, Network Model, Simulations, Sampling (Statistics), Probability Distribution, Dependency Analysis

    Intermediate · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    M

    Microsoft

    Generative AI for Data Science with Copilot

    Skills you'll gain: Generative AI, Microsoft Copilot, Generative Model Architectures, Generative Adversarial Networks (GANs), Responsible AI, Data Ethics, Data Security, Information Privacy, Anomaly Detection, Model Evaluation, Data Analysis

    4.7
    Rating, 4.7 out of 5 stars
    ·
    37 reviews

    Beginner · Course · 1 - 4 Weeks

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

  • Bayesian Statistics: Duke University
  • Transformer Models and BERT Model: Google Cloud
  • Grow Trees & Powerful Ensembles: Coursera
  • Sequence Models: DeepLearning.AI
  • Explainable deep learning models for healthcare - CDSS 3: University of Glasgow
  • Build Better Generative Adversarial Networks (GANs): DeepLearning.AI
  • Introduction to Bayesian Statistics for Data Science: University of Colorado Boulder
  • Bayesian Statistics: Time Series Analysis: University of California, Santa Cruz
  • Discrete-Time Markov Chains and Monte Carlo Methods: University of Colorado Boulder
  • Computational and Graphical Models in Probability: Johns Hopkins University

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