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

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

Historical Perspectives on AGI: Definitions, Consciousness, and Alignment Challenges

Explore key debates around AGI through expert perspectives on consciousness, behavior, and alignment, examining scientific theories and current limitations in artificial intelligence development.

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

Multimodal AI: From First Principles to Neural Networks That See, Hear and Write

Explore the evolution and capabilities of multimodal AI systems, from fundamental principles to advanced models that combine vision, text, and audio for sophisticated machine learning tasks.

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

Vision Transformers: Understanding Self-Attention and Implementation in PyTorch

Dive into Vision Transformers through clear visualizations and hands-on PyTorch implementation, mastering self-attention mechanisms and comparing them with CNNs in computer vision tasks.

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

Retrieval Augmented Generation (RAG) - Building Powerful LLM Pipelines

Dive into the fundamentals of Retrieval Augmented Generation (RAG), exploring advanced techniques from basic pipelines to modern frameworks for building powerful LLM systems with external knowledge integration.

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

Understanding Text-to-Video Diffusion Models - From Core Concepts to Latest Developments

Explore the evolution of text-to-video diffusion models, from fundamental concepts to cutting-edge implementations like SORA, covering key challenges and breakthroughs in video generation AI technology.

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

The Machine Learning Behind Apple Intelligence - Understanding Modern LLM Architecture

Dive into the technical architecture and algorithmic innovations behind Apple's Foundation Language Models, exploring key concepts from transformer decoders to quantization and reinforcement learning.

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

Segment Anything 2 (SAM 2) - Network Architecture and Implementation Explained

Delve into META AI's SAM-2 technology and understand the advanced network architecture behind promptable visual segmentation for automated object detection in videos.

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