The Full Stack Courses

Introduction to Deep Learning - Full Stack Deep Learning - March 2019

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Comprehensive introduction to AI and deep learning, covering key concepts, applications, and historical context. Explores data processing, computational requirements, and course structure.

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

Factored Cognition Primer by Ought

Explore factored cognition through a hands-on livecoding session, diving into Ought's primer to understand complex problem-solving techniques and AI-assisted reasoning.

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

Getting Started with LLMs - Livecoding by Jeremy Howard

Explore LLM-based data analysis and synthetic data generation for the "LLM Science Exam" Kaggle competition through a hands-on livecoding session.

• YouTube
• 2 hours 16 minutes
• On-Demand
• Free Video

Ethics - Full Stack Deep Learning - Spring 2021

Explore AI ethics, covering long-term challenges, hiring practices, fairness, representation, and best practices. Gain insights into crucial ethical considerations for AI development and implementation.

• YouTube
• 1 hour 5 minutes
• On-Demand
• Free Video

Data Management - Full Stack Deep Learning - Spring 2021

Explore ML infrastructure for data management: ingestion, storage, processing, exploration, labeling, and versioning. Learn about tools and best practices for effective dataset handling in deep learning projects.

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

Troubleshooting Deep Neural Networks - Full Stack Deep Learning - Spring 2021

Learn a systematic approach to troubleshoot deep neural networks, from starting simple to tuning hyperparameters, with practical strategies for implementation, debugging, evaluation, and improvement.

• YouTube
• 1 hour 7 minutes
• On-Demand
• Free Video

Infrastructure & Tooling - Full Stack Deep Learning - Spring 2021

Comprehensive overview of ML infrastructure and tools, covering software engineering, computing, resource management, frameworks, experiment management, and hyperparameter optimization for practitioners.

• YouTube
• 1 hour 7 minutes
• On-Demand
• Free Video

ML Projects - Full Stack Deep Learning - Spring 2021

Learn to set up ML projects professionally, covering lifecycle, feasibility, impact, archetypes, metrics, and baselines. Gain insights into project management and optimization for successful machine learning implementations.

• YouTube
• 1 hour 13 minutes
• On-Demand
• Free Video

Transfer Learning and Transformers - Full Stack Deep Learning - Spring 2021

Explore transfer learning's evolution from computer vision to NLP, diving into embeddings, language models, and the revolutionary Transformer architecture. Gain insights into various models and their applications.

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

Recurrent Neural Networks - Full Stack Deep Learning - Spring 2021

Explore Recurrent Neural Networks: architecture, challenges, solutions, and applications. Dive into LSTMs, bidirectionality, attention mechanisms, CTC loss, and non-recurrent sequence models like WaveNet.

• YouTube
• 1 hour 6 minutes
• On-Demand
• Free Video

Computer Vision Applications - Full Stack Deep Learning - Spring 2021

Comprehensive overview of deep learning applications in computer vision, covering ConvNet architectures, detection methods, and advanced tasks like 3D shape inference and style transfer.

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

Convolutional Neural Networks - Full Stack Deep Learning - Spring 2021

Explore convolutional neural networks, from basic operations to advanced concepts like dilated convolutions and pooling. Learn about the classic LeNet architecture and gain insights into ConvNet implementation.

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

Deep Learning Fundamentals - Full Stack Deep Learning

Comprehensive overview of deep learning basics, covering neural networks, learning problems, optimization techniques, and architectural considerations for AI practitioners.

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

Coding a Neural Network - Full Stack Deep Learning - Spring 2021

Code a neural network from scratch using Google Colab, NumPy, PyTorch, and Keras. Learn linear regression and multi-layer perception models through hands-on implementation and visualization.

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

Andrej Karpathy on AI at Tesla - Full Stack Deep Learning - August 2018

Explore Tesla's AI innovations with Andrej Karpathy, delving into cutting-edge deep learning applications in autonomous driving and computer vision.

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