Neural Breakdown with AVB Courses

Training Vision Language Models from Scratch Using Text-Only LLMs

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Discover how to transform text-only LLMs into powerful Vision Language Models using Q-Former architecture from BLIP-2, with complete code implementation and training guide.

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

Context Engineering with DSPy - Comprehensive Hands-On Course for Building LLM Applications

Master DSPy for building reliable LLM applications with RAG, multi-agent systems, tool calling, and advanced context engineering techniques in this comprehensive hands-on guide.

• YouTube
• 1 hour 22 minutes
• Self-Paced
• Free Video

Multi-Agent Reinforcement Learning - AI Navigation in Obstacle Courses

Explore multi-agent reinforcement learning by training AI teams to navigate obstacle courses using PPO, MA-PPO, and centralized training methods for cooperative behaviors.

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

The 6 Questions That Every Reinforcement Learning Algorithm Must Answer

Discover the 6 fundamental questions every RL algorithm must answer, covering Q-learning, policy gradients, actor-critics, and model-based approaches in a clear framework.

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

How to Build Your Own Long-Term Agentic Memory System for LLMs - Mem0 from Scratch with DSPy

Master building agentic memory systems for LLMs using DSPy and QDrant, recreating Mem0's core components from scratch with embeddings, vector databases, and tool calling.

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

Best NLP, Transformers, and LLM Research Papers of 2024 - A Comprehensive Review

Explore groundbreaking developments in LLM research through a curated analysis of 2024's most influential papers, covering tokenization, RNN revival, Mamba architecture, and advanced prompting techniques.

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

Exploration in Sparse RL Environments - Curiosity and Random Network Distillation (RND)

Explore self-supervised exploration methods in reinforcement learning with Curiosity and Random Network Distillation (RND), learning how these techniques help agents navigate sparse environments through Python and PyTorch implementations.

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

Diffusion Language Models vs Autoregressive Language Models - Complete Gemini Diffusion Breakdown

Explore the differences between diffusion and autoregressive language models, focusing on Google Gemini's approach, training methods, and comparative advantages over traditional GPT models.

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

From Attention to Generative Language Models - Building Transformers from Scratch

Master the fundamentals of Causal Generative Language Models through hands-on Pytorch implementation, covering attention mechanisms, transformers, and neural architectures with practical code examples.

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

Fine-tuning LLMs with Huggingface and PyTorch - A Step-by-Step Tutorial

Master fine-tuning techniques for LLMs using Huggingface and PyTorch, from tokenization to LORA adapters, with hands-on implementation using Meta's Llama-3.2-1B-Instruct model.

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

TextGrad Tutorial - Optimize LLM Prompts, Math and Code

Master TextGrad framework for optimizing LLM prompts through practical examples covering hallucination reduction, code optimization, math problem-solving, and prompt fine-tuning techniques.

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

Building YOLO Neural Networks for Object Detection in Python and PyTorch - Part 1

Master the implementation of YOLO neural networks in Python and PyTorch, covering architecture, data preprocessing, Feature Pyramid Networks, and object detection fundamentals.

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

DSPy Tutorial - Programming Language Models with 8 Key Examples

Master DSPy framework through 8 practical examples, from basic QA to advanced LLM programming concepts like RAG, multi-hop reasoning, and model fine-tuning with popular language models.

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

History of Computer Vision and CNN Architectures: From LeNet to Vision Transformers

Explore the evolution of Computer Vision through key architectural innovations, from early CNNs to modern Vision Transformers, with clear visualizations explaining breakthrough moments in deep learning history.

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

Text-to-Image Diffusion AI Model Implementation - A Line-by-Line Code Tutorial

Dive into the fundamentals of diffusion AI models through hands-on PyTorch implementation, covering everything from basic concepts to advanced Latent Diffusion Models for text-to-image generation.

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