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"

  • Stanford Online

    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 stars, 1.4K reviews, Advanced, Course, 1 - 3 Months

  • 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

  • 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

  • IIT Guwahati

    Skills you'll gain: Relational Databases, Package and Software Management, Generative AI, Data Visualization, Time Series Analysis and Forecasting, Linear Algebra, C (Programming Language), Java Programming, Cloud Computing, Data Structures, R (Software), Data Warehousing, Database Management, Social Network Analysis, Econometrics, File I/O, Probability, Bayesian Network, English Language, Algorithms

    Degree · 1 - 4 Years

  • Stanford Online

    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 stars, 1.6K reviews, Advanced, Specialization, 3 - 6 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

    Intermediate · Specialization · 3 - 6 Months

  • 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)

    4 stars, 6 reviews, Intermediate, Course, 1 - 4 Weeks

  • Imperial College London

    Skills you'll gain: Generative AI, Tensorflow, Autoencoders, Generative Model Architectures, Bayesian Network, Deep Learning, Image Analysis, Bayesian Statistics, Model Optimization, Probability Distribution, Model Training, Sampling (Statistics), Data Transformation

    4.7 stars, 109 reviews, Advanced, Course, 1 - 3 Months

  • Imperial College London

    Skills you'll gain: Tensorflow, Generative AI, Recurrent Neural Networks (RNNs), Autoencoders, Generative Model Architectures, Data Pipelines, Keras (Neural Network Library), Model Evaluation, Deep Learning, Image Analysis, Model Training, Bayesian Network, Transfer Learning, Convolutional Neural Networks, Computer Programming, Model Optimization, Applied Machine Learning, Bayesian Statistics, Supervised Learning, Natural Language Processing

    4.8 stars, 722 reviews, Intermediate, Specialization, 3 - 6 Months

  • Birla Institute of Technology & Science, Pilani

    Skills you'll gain: Artificial Intelligence, Artificial Intelligence and Machine Learning (AI/ML), Reinforcement Learning, Computational Logic, Agentic systems, Bayesian Network, Decision Intelligence, Machine Learning, Bayesian Statistics, AI literacy, Markov Model, Algorithms, Computational Thinking, Probability, Model Optimization, Probability & Statistics, Probability Distribution

    Intermediate · Course · 1 - 3 Months

  • Stanford Online

    Skills you'll gain: Bayesian Network, Bayesian Statistics, 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 stars, 491 reviews, Advanced, Course, 1 - 3 Months

  • Stanford Online

    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, Statistical Modeling, Model Training, Probability Distribution, Model Optimization, Statistical Methods, Probability & Statistics, Algorithms

    4.6 stars, 305 reviews, Advanced, Course, 1 - 3 Months