Statistical Learning Theory Courses and Certifications

Machine Learning Course

An introductory, theory-focused exploration of machine learning covering generalization, model complexity, neural networks, support vector machines, and kernel methods.

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

Machine Learning

Learn about machine learning, the area of artificial intelligence (AI) that is concerned with computational artifacts that modify and improve performance through experience.

• edX
• 14 weeks, 8-10 hours a week
• Self-Paced
• Free Certificate

Information Theory of Deep Learning - Naftali Tishby

Explains deep neural network learning through the Information Bottleneck, linking input compression and mutual information to generalization and accuracy.

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

Big Data Machine Learning | 大数据机器学习

The "Big Data Machine Learning" course is a basic theoretical course for senior undergraduates or graduate students in the information discipline. The purpose is to cultivate students to have an in-de

• edX
• 16 weeks, 3-5 hours a week
• Self-Paced
• Free Certificate

Bloomberg

Foundations of Machine Learning

1 rating

Understand the Concepts, Techniques and Mathematical Frameworks Used by Experts in Machine Learning

• Independent
• Self-Paced
• Free Online Course

Learn common regularization techniques, implement them in Python, and use them to improve machine learning performance on new data.

• Codecademy
• 2 hours
• Self-Paced
• Free Trial Available

Study learning from informant, a formal model of binary classification: prove consistency and mind-change results, apply Blum and Blum's separation technique, and adapt models toward incremental deep learning.

• openHPI
• 3 weeks
• Self-Paced
• Free Certificate

University of Tübingen

Statistical Machine Learning

2 ratings

A mathematically grounded treatment of machine learning, from risk minimization and convex optimization to kernels, learning theory, fairness, and representation methods.

• YouTube
• 1 day 9 hours
• Self-Paced
• Free Online Course

NPTEL;  IISc Bangalore

Pattern Recognition

1 rating

Learn the fundamentals of statistical pattern classification and regression, from Bayes classifiers and density estimation to SVMs and ensemble methods.

• YouTube
• 1 day 16 hours
• Self-Paced
• Free Video

NPTEL;  IISc Bangalore

Pattern Recognition

This course provides a fairly comprehensive view of the fundamentals of pattern classification and regression. Topics covered in the lectures include an overview of pattern classification and regression; Bayesian decision making and Bayes classifier

• YouTube
• 1 day 5 hours
• Self-Paced
• Free Video

StatQuest with Josh Starmer

Regularization Part 1 - Ridge (L2) Regression

Understand how ridge regression reduces overfitting and variance, selects its penalty with cross-validation, and solves regression problems with limited data.

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

Pascal Poupart

Introduction to Machine Learning - Spring 2019 - University of Waterloo

Dive into comprehensive machine learning fundamentals covering neural networks, SVMs, deep learning, CNNs, transformers, and ensemble methods from University of Waterloo.

• YouTube
• 1 day 4 hours 26 minutes
• Self-Paced
• Free Video

Richard McElreath

Statistical Rethinking 2022

Master Bayesian inference, multilevel modeling, and causal reasoning through practical statistical methods that avoid common pitfalls in data analysis and research design.

• YouTube
• 1 day 46 minutes
• Self-Paced
• Free Video

Insights into Mathematics

Real Numbers and Limits

Explore fundamental concepts of real numbers, limits, and mathematical foundations through critical examination of infinity, sequences, and numerical approximation methods.

• YouTube
• 17 hours 19 minutes
• Self-Paced
• Free Video

Machine Learning Foundations

Master machine learning fundamentals with TensorFlow, covering neural networks, computer vision, CNNs, and natural language processing through hands-on coding examples.

• YouTube
• 2 hours 11 minutes
• Self-Paced
• Free Video