Social And Emotional Learning Courses

Paul Browning

What Is a Social Engineering Attack?

Learn about social engineering attacks, their techniques, and how to protect against them in this informative cybersecurity lesson.

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

Alexander Amini

MIT Introduction to Deep Learning

Comprehensive introduction to deep learning fundamentals, covering perceptrons, neural networks, loss functions, gradient descent, backpropagation, and regularization techniques.

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

The Cherno

Learning C++ for Java, C#, and Python Developers - Code Review

Comprehensive C++ code review covering Git submodules, debugging, optimization, and best practices. Ideal for experienced programmers transitioning to C++ from Java, C#, or Python.

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

Unity

Democratize Machine Learning - ML-Agents Explained

Explore Unity ML-Agents: an open-source toolkit bridging Unity and machine learning. Learn about reinforcement and imitation learning techniques for innovative game development and AI applications.

• YouTube
• 42 minutes
• Self-Paced
• Conference Talk

MITCBMM

Statistical Learning Theory and Applications - Class 16

Explore statistical learning theory, focusing on complexity, dual norm equality, and calligraphic G. Gain insights into advanced concepts and their applications in machine learning.

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

MITCBMM

Statistical Learning Theory and Applications - Class 6

Explore statistical learning theory with focus on Newton's method, recursive computation, and online methods for efficient problem-solving and data analysis.

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

MITCBMM

Statistical Learning Theory and Applications - Class 7

Explore statistical learning theory, covering least squares, gradient descent, regularization, and induction, with insights into historical context and practical applications.

• YouTube
• 1 hour 27 minutes
• Self-Paced
• Free Video

MITCBMM

The Deep Learning Revolution

Explore the evolution of deep learning, from its origins to modern applications, covering key milestones, breakthroughs, and future prospects in AI and neuroscience.

• YouTube
• 1 hour 12 minutes
• Self-Paced
• Free Video

MITCBMM

Deep Learning Tutorial

Explore deep learning fundamentals, from supervised learning to convolutional networks, with practical examples and historical context. Gain insights into advanced concepts and applications.

• YouTube
• 1 hour 8 minutes
• Self-Paced
• Free Video

MITCBMM

Fit Without Fear - An Over-Fitting Perspective on Modern Deep and Shallow Learning

Explore over-fitting in modern machine learning, challenging conventional wisdom and presenting kernel methods as a competitive alternative to deep learning. Insights on interpolation, generalization, and stochastic gradient descent.

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

MITCBMM

Machine Learning and AI for the Sciences - Towards Understanding

Explore ML and AI applications in sciences, focusing on neuroscience, medicine, and physics. Learn about extracting insights from ML models to enhance understanding in fields like quantum chemistry.

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

MITCBMM

Reinforcement Learning

Explore reinforcement learning concepts and their applications in psychology and neuroscience. Hands-on exercises demonstrate how algorithms explain animal learning and dopamine neuron firing.

• YouTube
• 1 hour 10 minutes
• Self-Paced
• Free Video

MITCBMM

Machine Learning Techniques and Applications in Finance, Healthcare and Recommendation Systems

Explore state-of-the-art machine learning techniques and their applications in finance, healthcare, and recommendation systems, focusing on ensemble methods, collaborative filtering, and portfolio construction.

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

MITCBMM

Unsupervised Learning of Spoken Language with Visual Context

Explores unsupervised learning of spoken language using visual context, aiming to develop ASR capabilities for more languages through audio-visual embedding and clustering techniques.

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

MITCBMM

Learning with Symmetry and Invariance for Speech Perception

Explore symmetry and invariance in speech perception, focusing on acoustic variability, feedforward models, and invariant representations. Learn about word orbits, phone representations, and acoustic modeling techniques.

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