Machine Learning Courses and Certifications

Harvard CMSA

What Mathematics Can Help Us Understand and Advance Machine Learning - ML, QML, and Dynamics

Explore the mathematical foundations of machine learning through dynamic systems, chaos theory, and tensor structures, examining their roles in neural networks and language models.

• YouTube
• 1 hour 20 minutes
• Self-Paced
• Free Video

Harvard CMSA

Machine Learning for Protein Structure Prediction - AlphaFold2 and OpenFold - Part 3

Delve into the limitations of AlphaFold2 and explore new insights from OpenFold's retraining approach to protein structure prediction and machine learning evolution.

• YouTube
• 1 hour 33 minutes
• Self-Paced
• Free Video

Harvard CMSA

Machine Learning for Protein Structure Prediction - Algorithm Space - Part 1

Delve into protein structure prediction through machine learning, exploring AlphaFold2's revolutionary approach, co-evolutionary methods, and CNN applications in structural biology.

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

Coding Train

Introduction to Transformers.js - Machine Learning in the Browser with JavaScript

Discover how to implement machine learning models in JavaScript browsers using Transformers.js library, covering pipeline API, sentiment analysis, and language detection with p5.js integration.

• YouTube
• 29 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

Machine Learning (Fall 2019)

Master fundamental machine learning algorithms, techniques, and applications through comprehensive university lectures covering theory and practical implementation.

• YouTube
• 1 day 11 hours 29 minutes
• Self-Paced
• Free Video

UofU Data Science

Machine Learning - Fall 2018

Dive into comprehensive machine learning fundamentals through 27 structured lectures covering algorithms, theory, and practical applications from University of Utah.

• YouTube
• 1 day 10 hours 45 minutes
• Self-Paced
• Free Video

UofU Data Science

Machine Learning - Fall 2016

Dive into comprehensive machine learning fundamentals through university-level lectures covering algorithms, theory, and practical applications from UofU Data Science.

• YouTube
• 1 day 1 hour 42 minutes
• Self-Paced
• Free Video

UofU Data Science

Machine Learning (Fall 2015)

Dive into comprehensive machine learning fundamentals through 28 structured lectures covering algorithms, theory, and practical applications from University of Utah.

• YouTube
• 1 day 11 hours 14 minutes
• Self-Paced
• Free Video

AICamp

4-Week AI and Machine Learning Courses - Full Stack Development with AWS, GCP, and TensorFlow

Master comprehensive AI/ML skills through hands-on projects covering deep learning, NLP, computer vision, and cloud deployment with AWS/GCP in structured 4-week programs.

• YouTube
• 3 hours 25 minutes
• Self-Paced
• Free Video

MITCBMM

Machine Learning Crash Course 2015

Dive into machine learning fundamentals covering linear models, kernels, PCA, clustering, and practical applications with hands-on GURLS framework implementation.

• YouTube
• 10 hours 29 minutes
• Self-Paced
• Free Video

Building Decision Agents with LLMs and Machine Learning Models

Explore designing decision agents that combine DMN, LLMs, and ML models for transparent, scalable automation systems in AI frameworks.

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

ICTP Condensed Matter and Statistical Physics

The Hitchhiker's Guide to Condensed Matter and Statistical Physics - Machine Learning for Condensed Matter

Explore machine learning applications in condensed matter and statistical physics, covering quantum systems, thermodynamic properties, and neural networks for many-body problems.

• YouTube
• 12 hours 58 minutes
• Self-Paced
• Free Video

GERAD Research Center

Koopman Operator Theory Based Machine Learning of Dynamical Systems

Explore Koopman Operator Theory for machine learning of dynamical systems, covering applications in fluid dynamics, power grids, network security, and more.

• YouTube
• 1 hour 5 minutes
• Self-Paced
• Free Video

Harvard CMSA

Mathematics and Machine Learning Closing Workshop

Explore cutting-edge intersections of mathematics and machine learning through expert presentations on topology, fluid dynamics, AI-assisted discovery, and computational methods.

• YouTube
• 12 hours 51 minutes
• Self-Paced
• Free Video