Computational Learning Theory Courses and Certifications

Explore computational learning theory, focusing on binary classification and incremental learning models, with insights into various AI approaches and research areas.

• openHPI
• 3 weeks
• On-Demand
• Free Online Course

Association for Computing Machinery (ACM)

Leslie G. Valiant - Turing Award Lecture 2010

Explore computational learning theory, machine learning, and brain modeling with Leslie G. Valiant, 2010 ACM Turing Award winner, as he discusses his groundbreaking research and insights.

• YouTube
• 1 hour 4 minutes
• On-Demand
• Free Video

Institute for Pure & Applied Mathematics (IPAM)

Learning of Neural Networks with Quantum Computers and Learning of Quantum States with Graphical Models

Explores quantum algorithms for neural network learning and quantum state learning using graphical models, showcasing advancements in computational efficiency and sample complexity for specific quantum states.

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

Institute for Pure & Applied Mathematics (IPAM)

Smoothed Analysis for Learning Concepts with Low Intrinsic Dimension

Explore smoothed analysis in machine learning, focusing on low-dimensional concepts and their applications. Gain insights into new algorithms for agnostic learning and margin-based approaches.

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

Institute for Pure & Applied Mathematics (IPAM)

Learning-Augmented Online Optimization

Explore learning-augmented online optimization with Google's Ravi Kumar, covering computational and statistical gaps in learning and optimization techniques.

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

Institute for Pure & Applied Mathematics (IPAM)

A Perceptron Trio - Computational vs Statistical Gaps in Learning and Optimization

Explore perceptron algorithms in machine learning, focusing on computational and statistical aspects in optimization and learning theory.

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

Stony Brook Mathematics

Learning Low-Degree Functions on the Discrete Hypercube

Explore computational learning theory through function reconstruction on the discrete hypercube, connecting polynomial inequalities to query complexity and improving upon classical algorithms.

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

NCCR SwissMAP

Learning Sparse Boolean Functions: Neural Networks Need a Hierarchical Degree Chain

Explore neural networks' requirements for learning sparse Boolean functions, focusing on the hierarchical degree chain concept in this advanced workshop on spin glasses.

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

Simons Institute

New Directions in Property Testing

Explore recent advancements in property testing algorithms, including new problems and frameworks connected to machine learning theory and high-dimensional data analysis.

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

Simons Institute

Educability - Understanding Higher-Level Intelligence

Exploring human educability: synthesizing learning from experience, others, and chaining knowledge. Proposes a computational approach to understanding and replicating broader human capabilities beyond example-based learning.

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

Brown University;  Georgia Tech

Machine Learning 1—Supervised Learning

1 review

Explore supervised learning techniques like decision trees, neural networks, and SVMs. Gain skills to understand and interpret machine learning technologies for various data science applications.

• Udacity
• Finished
• Free Online Course