Computational Statistics Courses and Certifications

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 Video

Centre de recherches mathématiques - CRM

Integrating Mechanistic Models with Computational Statistics and Machine Learning - New Insights in Biology

Explore integrating mechanistic models with computational statistics and machine learning for new insights in cell and developmental biology. Tackle challenges in analyzing complex quantitative data.

• YouTube
• 1 hour 11 minutes
• On-Demand
• Free Video

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 Video

VinAI

Independent Finite Approximations for Bayesian Nonparametric Inference

Explore independent finite approximations for Bayesian nonparametric inference, comparing them to truncated finite approximations and analyzing their performance in real-world applications.

• YouTube
• 1 hour 16 minutes
• On-Demand
• Free Video

Computational Genomics Summer Institute CGSI

Using Classical Algorithms for Modern Applications: MCMC for Tail Calculations, EM - Lecture

Explore classical algorithms applied to modern challenges: MCMC for tail probability estimation and EM for PET reconstruction. Gain insights into innovative adaptations of established methods for cutting-edge problems.

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

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

Databricks Microcredential

Introduction to Computational Statistics for Data Scientists

109 ratings at Coursera

Learn Bayesian statistics, Monte Carlo methods, and PyMC3 for data science. Gain practical skills in probability, modeling, and inference using Python tools like NumPy, Pandas, and Matplotlib.

• Coursera
• 4 weeks, 10 hours a week
• On-Demand
• Paid Course
• 3 courses

Bayesian Computational Statistics

Rigorous introduction to Bayesian inference, covering theory, computation, and practical implementation using statistical software. Explores advanced topics and applications in data analysis.

• Coursera
• 3 days 16 hours 39 minutes
• On-Demand
• Paid Course

Bayesian Statistical Concepts and Methods

Master Bayesian methods for data analysis using posterior distributions, MCMC algorithms, and hierarchical models with R and Stan platform implementation.

• Coursera
• 5 hours 30 minutes
• On-Demand
• Paid Course

Microcredential

Advanced Statistical Techniques for Data Science

48 ratings at Coursera

Master advanced statistical techniques for data science including regression, model diagnostics, variable selection, Bayesian statistics, and data preparation for complex analysis.

• Coursera
• 16 weeks, 10 hours a week
• On-Demand
• Paid Course
• 5 courses

Data Science Fundamentals Part 2: Unit 2

Master statistical inference through hypothesis testing, confidence intervals, and A/B testing while learning to distinguish correlation from causation for robust data analysis.

• Coursera
• 6 hours 9 minutes
• On-Demand
• Paid Course

Corpus Studies and Statistics in Computational Music Theory - Class 14

Explore advanced corpus analysis techniques in computational music theory, examining Bach and Haydn through statistical methods and music21 tools for distant listening.

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

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 Video

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 Video

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 Video