Computational Statistics Courses and Certifications

Alan Turing Institute

Langevin Monte Carlo: Randomized Midpoint Method Revisited

Explore advanced Langevin Monte Carlo techniques, focusing on the Randomized Midpoint method's superior sampling error guarantees and recent improvements for high-dimensional target distributions.

• YouTube
• 39 minutes
• On-Demand
• Free Online Course

Alan Turing Institute

New Challenges in Computational Statistics

Explore cutting-edge computational statistics challenges and innovations in this lecture by Professor Gareth Roberts, focusing on complex data analysis and algorithm advancements in statistical science.

• YouTube
• 1 hour 4 minutes
• On-Demand
• Free Online Course

Deep Generative Models - Maximum Likelihood Learning - Lecture 4

Explore maximum likelihood learning in deep generative models with Stanford's Stefano Ermon. Gain insights into advanced AI techniques and their applications in this comprehensive lecture.

• YouTube
• 1 hour 24 minutes
• On-Demand
• Free Online Course

Databricks

Introduction to Bayesian Statistics

45 ratings at Coursera

Learn probability, Bayesian modeling, and inference using Python and Jupyter notebooks. Gain hands-on experience with distributions, sampling algorithms, and computational statistics techniques.

• Coursera
• 12 hours 47 minutes
• On-Demand
• Free Online Course (Audit)

The Julia Programming Language

Probability via Computation - Week 4

Explore probability concepts through computational methods, covering random sampling, Monte Carlo simulations, Bernoulli trials, and the Central Limit Theorem with practical examples and visualizations.

• YouTube
• 26 minutes
• On-Demand
• Free Online Course

The Royal Institution

The Future of Crime Detection and Prevention

Expert panel explores AI's role in predicting and preventing crime, discussing technological advancements, ethical concerns, and the future of law enforcement and security.

• YouTube
• 44 minutes
• On-Demand
• Free Online Course

Alan Turing Institute

The Mother of All Representer Theorems for Inverse Problems and Machine Learning - Michael Unser

Explore the mathematical foundations of inverse problems and machine learning, focusing on representer theorems, Banach spaces, and kernel methods for advanced data science applications.

• YouTube
• 48 minutes
• On-Demand
• Free Online Course

Alan Turing Institute

Affine Spline Insights into Deep Learning - Richard Baraniuk, Rice University

Explore deep learning through affine splines, understanding neural networks as matched filterbanks and partition-based signal distances. Gain insights into data augmentation and future research directions.

• YouTube
• 38 minutes
• On-Demand
• Free Online Course

Alan Turing Institute

On the Unreasonable Effectiveness of Compressive Imaging - Ben Adcock, Simon Fraser University

Explores compressive imaging's effectiveness, discussing compressed sensing theory, optimal sampling strategies, and practical applications in data science and imaging technology.

• YouTube
• 41 minutes
• On-Demand
• Free Online Course

APS Physics

Inverse Problems on Graphs with Geometric Deep Learning

Explores geometric deep learning for graph inverse problems, focusing on non-Euclidean geometries, physics-based approaches, and applications in particle physics and community detection.

• YouTube
• 33 minutes
• On-Demand
• Free Online Course

Simons Institute

Optimal Iterative Algorithms for Problems With Random Data

Explore optimal iterative algorithms for statistical problems with random data, focusing on computational complexity and efficient solutions in statistical inference.

• YouTube
• 53 minutes
• On-Demand
• Free Online Course

Alan Turing Institute

Two Decentralised Learning Problems - Sketching and Policy Evaluation - Justin Romberg, Georgia Tech

Explore cutting-edge decentralized learning techniques in sketching and policy evaluation with Justin Romberg from Georgia Tech. Gain insights into advanced mathematics for data science.

• YouTube
• 46 minutes
• On-Demand
• Free Online Course

Alan Turing Institute

Deep Dictionary Learning Approaches for Image Super-Resolution - Pier Luigi Dragotti, Imperial

Explore cutting-edge deep dictionary learning techniques for image super-resolution with Pier Luigi Dragotti from Imperial College, bridging mathematics and data science in this advanced workshop.

• YouTube
• 44 minutes
• On-Demand
• Free Online Course

IEEE

Cookbook Lower Bounds for Statistical Inference in Distributed and Constrained Settings - Part 3

Explore advanced statistical inference techniques for distributed and constrained environments, focusing on lower bound analysis and practical applications in complex data scenarios.

• YouTube
• 1 hour 10 minutes
• On-Demand
• Free Online Course

try! Swift Conference

Train Your Swift - Computational Statistics in Swift Examples

Explore statistical models, bag-of-words classification, and Markov Chain algorithms in Swift. Learn to implement mathematical concepts for sorting, classifying, and generating data through practical examples.

• YouTube
• 29 minutes
• On-Demand
• Conference Talk