Bayesian Statistics Courses and Certifications

CppCon

Optimize Automatic Differentiation Performance in C++

Discover advanced C++ techniques for optimizing automatic differentiation performance, from arena allocators to SIMD structures, making AD fast enough to eliminate hand-written derivatives.

• YouTube
• 1 hour
• Self-Paced
• Free Video

Discover AI

Risk-Aware RAG for Smarter AI Reasoning (ARISE)

Discover ARISE, a novel framework using risk-adaptive Monte Carlo Tree Search to guide knowledge-augmented reasoning in LLMs, balancing exploration and exploitation for more robust and efficient reasoning capabilities.

• YouTube
• 18 minutes
• Self-Paced
• Free Video

International Centre for Theoretical Sciences

Workshop on Data Assimilation in Weather and Climate Models 2024

Explore advanced data assimilation techniques for weather and climate modeling through comprehensive theory, hands-on practice, and real-world applications in atmospheric sciences.

• YouTube
• 2 days 3 hours 14 minutes
• Self-Paced
• Free Video

Centre International de Rencontres Mathématiques

CEMRACS 2021 - Mathematical and Computational Methods for High-Dimensional Problems

Explore advanced mathematical methods including Bayesian data assimilation, deep neural networks theory, tensor networks, and high-dimensional function approximation techniques.

• YouTube
• 14 hours 37 minutes
• Self-Paced
• Free Video

UofU Data Science

Machine Learning - Spring 2025

Master foundational ML concepts from decision trees to neural networks, covering theory, algorithms, and practical implementation techniques.

• YouTube
• 1 day 10 hours 25 minutes
• Self-Paced
• Free Video

UofU Data Science

Probabilistic Modeling - Spring 2016

Master statistical inference, Bayesian methods, and uncertainty quantification through comprehensive probabilistic modeling techniques for data science applications.

• YouTube
• 1 day 12 hours 7 minutes
• Self-Paced
• Free Video

Steve Brunton

Bayesian Inference - Overview

Discover how Bayesian inference balances data with prior beliefs to learn probability distributions, including practical hypothesis testing and key limitations.

• YouTube
• 30 minutes
• Self-Paced
• Free Video

Richard McElreath

Statistical Rethinking - Elemental Confounds I - Lecture A06

Uncover how confounding variables distort causal inference and learn systematic approaches to identify and address these fundamental statistical challenges.

• YouTube
• 1 hour 2 minutes
• Self-Paced
• Free Video

Richard McElreath

Statistical Rethinking - Gaussian Processes - Lecture B06

Explore Gaussian processes for flexible non-parametric modeling and spatial correlation analysis in Bayesian statistics.

• YouTube
• 1 hour
• Self-Paced
• Free Video

Steve Brunton

Monte Carlo Sampling and Bootstrapping in Bayesian Inference

Explore Monte Carlo sampling techniques and bootstrapping methods for Bayesian inference through practical algorithms and coin flip demonstrations.

• YouTube
• 18 minutes
• Self-Paced
• Free Video

Steve Brunton

Maximum Likelihood Estimation with Examples

Discover Maximum Likelihood Estimation fundamentals through clear derivations and Poisson distribution examples, building foundation for Bayesian MAP estimation in statistical modeling.

• YouTube
• 24 minutes
• Self-Paced
• Free Video

Institute for Advanced Study

Operator Scaling via Geodesically Convex Optimization, Invariant Theory and Polynomial Identity Testing - Yuanzhi Li

Explore geodesically convex optimization, invariant theory, and polynomial identity testing in this advanced seminar on operator scaling, featuring key theorems and proofs.

• YouTube
• 1 hour 41 minutes
• Self-Paced
• Free Video

OWASP Foundation

Prove It! - Confronting Security With Data

Explore data-driven methods to measure and improve security capabilities in rapidly scaling businesses, focusing on quantitative strategies and decision analysis techniques.

• YouTube
• 44 minutes
• Self-Paced
• Conference Talk

Simons Institute

Sampling Crash Course

Explore geometric methods in optimization and sampling, covering direct methods, Markov chain Monte Carlo, and probabilistic approaches for efficient algorithm design and analysis.

• YouTube
• 1 hour 3 minutes
• Self-Paced
• Free Video

Simons Institute

Dreamcoder- Bootstrapping Inductive Program Synthesis With Wake-Sleep Library Learning

Explore program induction and library learning in AI, focusing on DreamCoder's approach to synthesizing models and systems through neural-guided Bayesian inference and abstraction refinement.

• YouTube
• 47 minutes
• Self-Paced
• Free Video