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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 Trial
    Free Trial
    U

    University of Pennsylvania

    Modeling Risk and Realities

    Skills you'll gain: Risk Modeling, Risk Management, Mathematical Modeling, Predictive Modeling, Simulation and Simulation Software, Operations Research, Probability Distribution, Data-Driven Decision-Making, Statistical Hypothesis Testing, Statistical Analysis, Microsoft Excel, Excel Formulas

    4.6
    Rating, 4.6 out of 5 stars
    ·
    2.2K reviews

    Mixed · Course · 1 - 4 Weeks

  • Status: Free
    Free
    C

    Coursera

    Build and deploy a stroke prediction model using R

    Skills you'll gain: Feature Engineering, Predictive Modeling, R Programming, Data Analysis, Classification And Regression Tree (CART), Statistical Modeling, Statistical Analysis, Data Cleansing, Exploratory Data Analysis, Applied Machine Learning, Data Manipulation, Application Deployment, Data Transformation, Machine Learning Methods, Interactive Data Visualization, Machine Learning

    4.5
    Rating, 4.5 out of 5 stars
    ·
    24 reviews

    Intermediate · Guided Project · Less Than 2 Hours

  • 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
    ·
    272 reviews

    Intermediate · Project · Less Than 2 Hours

  • Status: New
    New
    Status: Preview
    Preview
    E

    EDUCBA

    SPSS: Apply & Interpret Logistic Regression Models

    5
    Rating, 5 out of 5 stars
    ·
    8 reviews

    Mixed · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    J

    Johns Hopkins University

    Quantifying Relationships with Regression Models

    Skills you'll gain: Regression Analysis, Correlation Analysis, Statistical Inference, Data Analysis, Statistical Modeling, Statistical Analysis, Probability & Statistics

    4.6
    Rating, 4.6 out of 5 stars
    ·
    23 reviews

    Intermediate · 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: Free Trial
    Free Trial
    D

    DeepLearning.AI

    Sequence Models

    Skills you'll gain: Natural Language Processing, Generative AI, Artificial Neural Networks, Tensorflow, Large Language Modeling, Artificial Intelligence and Machine Learning (AI/ML), PyTorch (Machine Learning Library), Deep Learning, Supervised Learning

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

    Intermediate · Course · 1 - 4 Weeks

  • Status: New
    New
    Status: Preview
    Preview
    E

    EDUCBA

    SAS: Apply & Evaluate Poisson & Negative Binomial Models

    Skills you'll gain: SAS (Software), Statistical Modeling, Regression Analysis, Statistical Analysis, Predictive Modeling, Statistical Methods, Statistical Hypothesis Testing

    Mixed · Course · 1 - 4 Weeks

  • C

    Coursera

    Building Statistical Models in R: Linear Regression

    Skills you'll gain: Exploratory Data Analysis, Statistical Modeling, Regression Analysis, Data Visualization, Data Analysis, Statistical Methods, R Programming, Statistical Analysis, Plot (Graphics), Predictive Modeling, Ggplot2

    4.7
    Rating, 4.7 out of 5 stars
    ·
    20 reviews

    Beginner · Guided Project · Less Than 2 Hours

  • Status: Free
    Free
    D

    DeepLearning.AI

    Finetuning Large Language Models

    Skills you'll gain: Large Language Modeling, LLM Application, Prompt Engineering, AI Personalization, Network Model

    4.6
    Rating, 4.6 out of 5 stars
    ·
    592 reviews

    Intermediate · Project · Less Than 2 Hours

  • Status: Free
    Free
    C

    Coursera

    Tidymodels in R: Building tidy machine learning models

    Skills you'll gain: Tidyverse (R Package), Data Visualization, Clinical Data Management, Data Manipulation, Predictive Modeling, R Programming, Data Processing, Data Cleansing, Predictive Analytics, Data Pipelines, Feature Engineering, Applied Machine Learning, Machine Learning, Statistical Modeling, Performance Tuning, Hospital Medicine

    Intermediate · Guided Project · Less Than 2 Hours

  • Status: New
    New
    Status: Free Trial
    Free Trial
    U

    University of Pittsburgh

    Interactive, Geospatial & Narrative Data Visualization

    Skills you'll gain: Data Storytelling, Interactive Data Visualization, Data Visualization Software, Data Presentation, Data Visualization, Tableau Software, Matplotlib, Geospatial Information and Technology, Spatial Analysis, Geospatial Mapping, Visualization (Computer Graphics), Seaborn, Infographics, Heat Maps, Data Ethics, Text Mining, Data Mapping, Network Analysis

    Build toward a degree

    Intermediate · Course · 1 - 3 Months

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1…789…289

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

  • Modeling Risk and Realities: University of Pennsylvania
  • Build and deploy a stroke prediction model using R: Coursera
  • How Diffusion Models Work: DeepLearning.AI
  • SPSS: Apply & Interpret Logistic Regression Models: EDUCBA
  • Quantifying Relationships with Regression Models: Johns Hopkins University
  • Bayesian Statistics: Mixture Models: University of California, Santa Cruz
  • Sequence Models: DeepLearning.AI
  • SAS: Apply & Evaluate Poisson & Negative Binomial Models: EDUCBA
  • Building Statistical Models in R: Linear Regression: Coursera
  • Finetuning Large Language Models: DeepLearning.AI

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