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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


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    IBM

    Generative AI: Foundation Models and Platforms

    Skills you'll gain: Generative AI, Generative Model Architectures, Generative Adversarial Networks (GANs), OpenAI, Hugging Face, Large Language Modeling, Deep Learning

    4.7
    Rating, 4.7 out of 5 stars
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    341 reviews

    Beginner · Course · 1 - 4 Weeks

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    Johns Hopkins University

    Foundations of Probability and Random Variables

    Skills you'll gain: R Programming, Statistical Analysis, Statistical Methods, Combinatorics, Statistical Programming, Data Analysis, Probability, Statistics, Probability Distribution, Applied Machine Learning, Probability & Statistics, Bayesian Statistics, Data Science, Simulations

    Intermediate · Course · 1 - 3 Months

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    Packt

    Building Retrieval-Augmented Systems & Knowledge Graphs

    Skills you'll gain: Retrieval-Augmented Generation, LLM Application, LangChain, Artificial Intelligence and Machine Learning (AI/ML), Agentic Workflows, Generative AI Agents, AI Integrations, Artificial Intelligence, Large Language Modeling, Taxonomy, Agentic systems, Scalability, Python Programming, System Design and Implementation, Machine Learning, Graph Theory

    Intermediate · Course · 1 - 4 Weeks

  • Status: Free Trial
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    IBM

    Supervised Machine Learning: Classification

    Skills you'll gain: Classification Algorithms, Supervised Learning, Model Evaluation, Data Preprocessing, Logistic Regression, Machine Learning Algorithms, Decision Tree Learning, Model Training, Applied Machine Learning, Statistical Machine Learning, Predictive Modeling, Business Logic, Machine Learning Methods, Scikit Learn (Machine Learning Library), Data Cleansing, Machine Learning, Regression Analysis, Random Forest Algorithm, Model Optimization, Sampling (Statistics)

    4.8
    Rating, 4.8 out of 5 stars
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    465 reviews

    Intermediate · Course · 1 - 3 Months

  • I

    IBM

    Specialized Models: Time Series and Survival Analysis

    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

    4.5
    Rating, 4.5 out of 5 stars
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    147 reviews

    Intermediate · Course · 1 - 4 Weeks

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    University of Pittsburgh

    Bayesian Regression and Model Selection

    Skills you'll gain: Statistical Modeling, Bayesian Statistics, Logistic Regression, Regression Analysis, Predictive Modeling, Mathematical Modeling, Model Evaluation, Statistical Methods, Statistical Machine Learning, Markov Model, Data-Driven Decision-Making, Statistical Inference, Predictive Analytics, Statistical Analysis, Sampling (Statistics), Probability Distribution, Machine Learning Algorithms, Computational Thinking

    Intermediate · Course · 1 - 4 Weeks

  • Status: New
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    University of Pittsburgh

    Bayesian Inference Fundamentals

    Skills you'll gain: Bayesian Statistics, Statistics, Statistical Inference, Probability & Statistics, Statistical Modeling, Statistical Methods, Probability Distribution, Statistical Analysis, Markov Model, Statistical Programming, Algorithms

    Intermediate · Course · 1 - 4 Weeks

  • Status: Free Trial
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    Johns Hopkins University

    Regression Models

    Skills you'll gain: Regression Analysis, Statistical Analysis, Statistical Modeling, Logistic Regression, Data Science, Data Analysis, Statistical Methods, Model Evaluation, Probability & Statistics, Statistical Inference, Statistical Hypothesis Testing

    4.4
    Rating, 4.4 out of 5 stars
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    3.4K reviews

    Mixed · Course · 1 - 4 Weeks

  • Status: Free Trial
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    Coursera

    Generative AI and Large Language Models

    Skills you'll gain: Generative AI, Generative Model Architectures, Large Language Modeling, LLM Application, Generative Adversarial Networks (GANs), Retrieval-Augmented Generation, OpenAI, Hugging Face, OpenAI API, Multimodal Prompts, Responsible AI, AI Security, Autoencoders, Model Deployment, Fine-tuning, Application Deployment

    4.3
    Rating, 4.3 out of 5 stars
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    12 reviews

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
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    University of California, Santa Cruz

    Bayesian Statistics: Mixture Models

    Skills you'll gain: R Programming, R (Software), Statistical Modeling, Bayesian Statistics, Statistical Software, Markov Model, Mathematical Modeling, Statistical Methods, Probability & Statistics, Statistical Inference, Sampling (Statistics), Probability Distribution, Classification Algorithms

    4.5
    Rating, 4.5 out of 5 stars
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    63 reviews

    Intermediate · Course · 1 - 3 Months

  • Status: New
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    U

    University of Colorado Boulder

    Computational Bayesian Statistics for Data Science

    Skills you'll gain: Bayesian Statistics, Data Science, Statistical Machine Learning, Statistical Methods, Statistical Software, Statistical Analysis, Mathematics and Mathematical Modeling, Computational Logic, Statistical Inference, Probability & Statistics, Machine Learning Methods, Computational Thinking

    Intermediate · Course · 1 - 3 Months

  • Status: New
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    Coursera

    Statistical Inference & Predictive Modeling Foundations

    Skills you'll gain: Descriptive Statistics, A/B Testing, Classification And Regression Tree (CART), Dashboard, Dashboard Creation, Model Evaluation, Model Deployment, Data-Driven Decision-Making, Risk Analysis, Histogram, Statistical Inference, Descriptive Analytics, Simulations, Predictive Modeling, Regression Analysis, Data Visualization, MLOps (Machine Learning Operations), Decision Making, Decision Tree Learning, Keras (Neural Network Library)

    Intermediate · Specialization · 3 - 6 Months

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

  • Generative AI: Foundation Models and Platforms: IBM
  • Foundations of Probability and Random Variables: Johns Hopkins University
  • Building Retrieval-Augmented Systems & Knowledge Graphs: Packt
  • Supervised Machine Learning: Classification: IBM
  • Specialized Models: Time Series and Survival Analysis: IBM
  • Bayesian Regression and Model Selection: University of Pittsburgh
  • Bayesian Inference Fundamentals: University of Pittsburgh
  • Regression Models: Johns Hopkins University
  • Generative AI and Large Language Models: Coursera
  • Bayesian Statistics: Mixture Models: University of California, Santa Cruz

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