Bayesian Network

A Bayesian Network is a graphical model that represents the probabilistic relationships among a set of variables. Coursera's Bayesian Network catalogue teaches you the principles and applications of Bayesian Networks, a crucial component of Artificial Intelligence and Machine Learning. You'll learn about the foundation of probabilistic reasoning, inference and learning algorithms, and how to handle uncertainty in complex systems. You'll also gain experience in constructing probabilistic models, making predictions, and improving decision making under uncertainty. Mastering Bayesian Network prepares you for roles in data analysis, machine learning, AI development, and other fields requiring deep knowledge of statistics and probability.

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Results for "Bayesian Network"

  • Arizona State University

    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

  • Stanford University

    Skills you'll gain: Bayesian Network, Decision Intelligence, Bayesian Statistics, Graph Theory, Probability Distribution, Network Model, Statistical Modeling, Markov Model, Probability & Statistics, Network Analysis, Dependency Analysis

    4.6
    Rating, 4.6 out of 5 stars
    1.4K reviews

    Advanced · Course · 1 - 3 Months

  • Status: New

    Coursera

    Skills you'll gain: Bayesian Network, Bayesian Statistics, Network Model, Artificial Intelligence and Machine Learning (AI/ML), Decision Intelligence, Predictive Modeling, Markov Model, Statistical Modeling, Statistical Inference, Graph Theory, Sampling (Statistics), Algorithms

    Intermediate · Course · 1 - 4 Weeks

  • Stanford University

    Skills you'll gain: Bayesian Network, Applied Machine Learning, Machine Learning Algorithms, Bayesian Statistics, Machine Learning Methods, Markov Model, Statistical Machine Learning, Machine Learning, Network Model, Unsupervised Learning, Model Training, Probability Distribution, Model Optimization, Statistical Methods, Probability & Statistics, Algorithms

    4.6
    Rating, 4.6 out of 5 stars
    305 reviews

    Advanced · Course · 1 - 3 Months

  • Dartmouth College

    Skills you'll gain: Supervised Learning, Bayesian Network, Logistic Regression, Artificial Neural Networks, Machine Learning Methods, Statistical Modeling, Predictive Modeling, Model Evaluation, Convolutional Neural Networks, Statistical Machine Learning, Probability & Statistics, Bayesian Statistics, Deep Learning, Artificial Intelligence and Machine Learning (AI/ML), Machine Learning, Machine Learning Algorithms, Statistical Methods, Artificial Intelligence, Regression Analysis, Statistical Inference

    Build toward a degree

    Intermediate · Specialization · 3 - 6 Months

  • Stanford University

    Skills you'll gain: Bayesian Network, Applied Machine Learning, Decision Intelligence, Bayesian Statistics, Graph Theory, Machine Learning Algorithms, Probability Distribution, Network Model, Statistical Modeling, Machine Learning Methods, Markov Model, Machine Learning, Unsupervised Learning, Probability & Statistics, Network Analysis, Statistical Inference, Model Training, Statistical Machine Learning, Model Optimization, Sampling (Statistics)

    4.6
    Rating, 4.6 out of 5 stars
    1.6K reviews

    Advanced · Specialization · 3 - 6 Months

  • EDUCBA

    Skills you'll gain: Artificial Intelligence and Machine Learning (AI/ML), Machine Learning Methods, Artificial Intelligence, Agentic systems, Machine Learning Algorithms, Bayesian Network, Applied Machine Learning, Computational Logic, Machine Learning, Bayesian Statistics, Artificial Neural Networks, Reinforcement Learning, Decision Intelligence, Markov Model, Algorithms, Programming Principles, Data-Driven Decision-Making, Probability & Statistics

    5
    Rating, 5 out of 5 stars
    10 reviews

    Mixed · Course · 1 - 3 Months

  • University of Colorado System

    Skills you'll gain: Bayesian Network, Linear Algebra, Numerical Analysis, Mathematical Modeling, Estimation, Matlab, Statistical Modeling, Markov Model, Simulations, Integral Calculus, Correlation Analysis, Control Systems, Probability, Simulation and Simulation Software, Probability & Statistics, Applied Mathematics, Statistical Methods, Probability Distribution, Time Series Analysis and Forecasting, Forecasting

    4.9
    Rating, 4.9 out of 5 stars
    38 reviews

    Intermediate · Specialization · 3 - 6 Months

  • Status: New

    University of Colorado Boulder

    Skills you'll gain: Bayesian Network, Bayesian Statistics, Markov Model, Probability, Decision Intelligence, Reinforcement Learning, Machine Learning Methods, Artificial Intelligence, Statistical Inference, Statistical Modeling, Network Model, Forecasting, Probability & Statistics, Dependency Analysis, Statistical Methods, Agentic systems, Applied Machine Learning, Probability Distribution, Time Series Analysis and Forecasting, Sampling (Statistics)

    Intermediate · Course · 1 - 4 Weeks

  • Johns Hopkins University

    Skills you'll gain: Mammography, Model Evaluation, Model Training, Artificial Intelligence, Bayesian Network, Image Analysis, AI Product Strategy, Machine Learning Methods, Oncology, Artificial Neural Networks, Medical Imaging, Machine Learning, Applied Machine Learning, Deep Learning, Epidemiology

    4.6
    Rating, 4.6 out of 5 stars
    81 reviews

    Intermediate · Course · 1 - 4 Weeks

  • Dartmouth College

    Skills you'll gain: Bayesian Network, Artificial Neural Networks, Machine Learning Methods, Convolutional Neural Networks, Deep Learning, Tensorflow, Model Training, Model Optimization, Machine Learning, Applied Machine Learning, Bayesian Statistics, Machine Learning Algorithms, Model Evaluation, Network Model, Network Architecture, Algorithms, Probability Distribution

    Build toward a degree

    Intermediate · Course · 1 - 3 Months

  • Stanford University

    Skills you'll gain: Bayesian Network, Machine Learning Methods, Statistical Inference, Markov Model, Statistical Machine Learning, Graph Theory, Sampling (Statistics), Applied Machine Learning, Statistical Methods, Probability & Statistics, Algorithms, Probability Distribution, Machine Learning Algorithms

    4.6
    Rating, 4.6 out of 5 stars
    491 reviews

    Advanced · Course · 1 - 3 Months