Bayesian Inference Courses and Certifications

Probability for Statistics and Data Science

1225 ratings at Udemy

Probability for improved business decisions: Introduction, Combinatorics, Bayesian Inference, Distributions

• Udemy
• 3 hours 40 minutes
• On-Demand
• Paid Course

Introduction to Uncertainty Quantification

10 ratings at Coursera

Master the fundamentals of Uncertainty Quantification through probability theory, uncertainty propagation, surrogate modeling, reliability analysis, and Bayesian methods for mathematical and engineering systems.

• Coursera
• 1 day 5 hours 57 minutes
• On-Demand
• Paid Course

Bayesian Networks 1 - Inference - Stanford CS221: AI

Explore Bayesian networks for AI, covering probabilistic inference, modeling, and applications in object tracking, language modeling, and document classification.

• YouTube
• 1 hour 22 minutes
• On-Demand
• Free Online Course

Introduction to Scientific Machine Learning

1 review

Learn the basics of machine learning with hands-on practical examples on engineering applications.

• edX
• 16 weeks, 6-7 hours a week
• On-Demand
• Free Online Course (Audit)

Introduction to Bayesian Statistics for Data Science

Explore the theoretical foundations of Bayesian statistics and apply them to data science problems, covering probability theory, Bayes' theorem, prior distributions, practical applications, and ethical considerations.

• Coursera
• 1 day 13 hours 29 minutes
• On-Demand
• Paid Course

Time, Change, and Decisions for Marketing

Revolutionize marketing strategies with advanced analytics, optimizing decision-making through Bayesian networks, time series forecasting, and causal modeling for data-driven, adaptive campaigns.

• Coursera
• 22 hours 53 minutes
• On-Demand
• Paid Course

Applied Bayesian for Analytics

Learn how to construct, fit, estimate and compute Bayesian statistical models with the help of OpenBUGS (freely available software)

• edX
• 6 weeks, 2-3 hours a week
• On-Demand
• Free Online Course (Audit)

Probability / Stats: The Foundations of Machine Learning

57 ratings at Udemy

Real-world, code-oriented learning for programmers to use prob/stats in all of CS, Data Science and Machine Learning

• Udemy
• 6 hours 42 minutes
• On-Demand
• Paid Course

Bayesian Statistics: Time Series Analysis

17 ratings at Coursera

Explore time series analysis through Bayesian statistics, covering AR processes and Normal Dynamic Linear Models. Apply concepts using R for practical data analysis and forecasting.

• Coursera
• 19 hours 29 minutes
• On-Demand
• Paid Course

EDUCBA

Data Science with Python: Analyze & Visualize

15 ratings at Coursera

Master Python programming for data analysis, visualization, and machine learning with hands-on projects covering statistics, regression, and real-world applications.

• Coursera
• 7 hours 59 minutes
• On-Demand
• Paid Course

Richard McElreath

Bayesian Inference Is Just Counting

Explore foundations of Bayesian data analysis, focusing on conceptual understanding and causal inference. Learn key principles from renowned expert Richard McElreath's book, covering topics like T-tests and machine learning.

• YouTube
• 2 hours 2 minutes
• On-Demand
• Free Video

Bayesian statistics

6 ratings at OpenLearn

This free course is an introduction to Bayesian statistics. Section 1 discusses several ways of estimating probabilities. Section 2 reviews ideas of conditional probabilities and introduces Bayes’ ...

• OpenLearn
• 12 hours
• On-Demand
• Free Certificate

The Royal Institution

Is Reality a Controlled Hallucination? - Exploring Consciousness and Perception

Explore consciousness as a controlled hallucination through innovative theories and experiments. Delve into perception, self-awareness, and the nature of reality with neuroscientist Anil Seth.

• YouTube
• 1 hour 4 minutes
• On-Demand
• Free Video

Society for Industrial and Applied Mathematics

Bayesian Inference with Plug-and-Play Priors - Imaging and Inverse Problems Seminar

Explore Bayesian imaging with Plug & Play methods, focusing on convergence guarantees and well-posed models. Learn about novel algorithms for Monte Carlo sampling and MAP inference in inverse problems.

• YouTube
• 53 minutes
• On-Demand
• Free Video

Alan Turing Institute

Semantic Models for Higher-Order Bayesian Inference - Sam Staton, University of Oxford

Explore probabilistic programming for Bayesian modeling, focusing on advanced languages with higher-order functions and continuous distributions. Learn about quasi-Borel spaces and modular inference algorithms.

• YouTube
• 41 minutes
• On-Demand
• Free Video