Bayesian Statistics

Bayesian Statistics is a theoretical framework for interpreting statistical data using probabilities. Coursera's Bayesian Statistics catalogue teaches you how to apply the core principles of Bayesian thinking to real-world statistical problems. You'll learn about Bayesian inference and modeling, probability distributions, and the decision-making process in uncertain situations. Furthermore, you'll gain skills in computational techniques and probabilistic programming languages. This knowledge can be utilized in various fields, such as data analysis, machine learning, and artificial intelligence, strengthening your ability to make informed decisions based on data.
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Explore the Bayesian Statistics Course Catalog

  • Status: Free Trial

    Skills you'll gain: Probability, Probability & Statistics, Probability Distribution, Bayesian Statistics, Statistical Methods, Data Analysis, Statistical Inference, Statistical Analysis, Artificial Intelligence

  • Status: Free Trial

    Johns Hopkins University

    Skills you'll gain: Precision Medicine, Game Theory, Reinforcement Learning, Data-Driven Decision-Making, Clinical Trials, Bioinformatics, Data Analysis, Image Analysis, Analytics, Markov Model, Bayesian Statistics, Time Series Analysis and Forecasting, Data Science, Predictive Analytics, Strategic Decision-Making, Anomaly Detection, Probability Distribution, Cybersecurity, Statistical Analysis, Machine Learning Methods

  • Status: Free Trial

    University of Washington

    Skills you'll gain: Regression Analysis, Applied Machine Learning, Feature Engineering, Machine Learning, Image Analysis, Unsupervised Learning, Predictive Modeling, Classification And Regression Tree (CART), Supervised Learning, Bayesian Statistics, Statistical Modeling, Artificial Intelligence, Deep Learning, Data Mining, Computer Vision, Statistical Machine Learning, Predictive Analytics, Text Mining, Machine Learning Algorithms, Big Data

  • Status: Free Trial

    Imperial College London

    Skills you'll gain: Tensorflow, Generative Model Architectures, Data Pipelines, Keras (Neural Network Library), Deep Learning, Image Analysis, Computer Programming, Program Development, Data Validation, Applied Machine Learning, Bayesian Statistics, Supervised Learning, Natural Language Processing, Data Processing, Predictive Modeling, Computer Vision, Machine Learning Methods, Artificial Neural Networks, Machine Learning, Unsupervised Learning

  • Status: Preview

    Johns Hopkins University

    Skills you'll gain: Descriptive Statistics, Linear Algebra, Exploratory Data Analysis, Data-Driven Decision-Making, Data Analysis, Bayesian Statistics, Statistics, Artificial Intelligence and Machine Learning (AI/ML), Artificial Intelligence, Probability, Regression Analysis, Calculus, Statistical Analysis, Advanced Mathematics, Applied Mathematics, Probability Distribution, Mathematical Modeling, Integral Calculus, Algebra, Machine Learning Algorithms

  • Skills you'll gain: Data Ethics, Data Storytelling, Statistical Hypothesis Testing, Statistical Machine Learning, Data Presentation, Regression Analysis, R (Software), Exploratory Data Analysis, Bayesian Statistics, Statistical Methods, Statistical Visualization, Data Literacy, Classification And Regression Tree (CART), Network Analysis, Data Visualization, Data Manipulation, Statistical Modeling, Linear Algebra, Artificial Intelligence and Machine Learning (AI/ML), Object Oriented Programming (OOP)

  • Status: Free Trial

    Skills you'll gain: Time Series Analysis and Forecasting, SAS (Software), Forecasting, Feature Engineering, Statistical Analysis, Data Analysis, Statistical Methods, Regression Analysis, Data Transformation, Exploratory Data Analysis, Predictive Modeling, Applied Machine Learning, Advanced Analytics, Statistical Modeling, Unsupervised Learning, Bayesian Statistics, Automation, Anomaly Detection, Data Processing, Dimensionality Reduction

  • Status: Free Trial

    Skills you'll gain: Statistical Hypothesis Testing, Statistical Methods, Statistical Inference, Bayesian Statistics, Probability & Statistics, Statistical Analysis, Sampling (Statistics), Jupyter, Python Programming, Matplotlib, NumPy

  • Status: Free Trial

    University of Colorado Boulder

    Skills you'll gain: Data Mining, Unsupervised Learning, Big Data, Supervised Learning, Machine Learning Methods, Classification And Regression Tree (CART), Data Analysis, Anomaly Detection, Machine Learning Algorithms, Advanced Analytics, Statistical Analysis, Predictive Modeling, Network Analysis, Exploratory Data Analysis, Bayesian Statistics, Algorithms, Artificial Neural Networks, Scalability

  • Status: Preview

    Skills you'll gain: Probability, Bayesian Statistics, Probability Distribution, Risk Modeling, Mathematical Modeling, Statistical Inference, Markov Model, Reliability, Simulations, Applied Mathematics, Statistical Analysis, Regression Analysis

  • Status: Free Trial

    Skills you'll gain: Statistical Modeling, Statistical Methods, Bayesian Statistics, Statistical Inference, Statistical Software, Statistical Programming, Regression Analysis, Predictive Modeling, Jupyter, Exploratory Data Analysis, Correlation Analysis, Probability Distribution, Python Programming, Data Visualization Software

  • Status: Free Trial

    Skills you'll gain: Supervised Learning, Data Modeling, Unsupervised Learning, Applied Machine Learning, Data Analysis, Regression Analysis, Classification And Regression Tree (CART), Machine Learning Algorithms, Machine Learning, Predictive Modeling, Random Forest Algorithm, Bayesian Statistics