Skill Path
AI Model Training & Deployment
Learn the fundamentals of AI model training and deployment, from building GPT models to deploying them at scale.
Includes Neural Networks, Transformer Architecture, Model Optimization, and more.
This skill path includes
Video lessons synced with hands-on coding
AI tutor for instant coding help
Build real projects from scratch
Assessments to validate mastery
About this skill path
AI model training has become increasingly powerful through the years. In this skill path, you'll learn how to build, train, and deploy transformer models like GPT-2. You'll work through fundamental concepts including tokenization, embeddings, attention mechanisms, and gain the skills necessary to develop and optimize large language models.
Skills you'll gain
Transformer architecture fundamentals
Model training and optimization
Tokenization and embeddings
GPU acceleration and scaling
Course Curriculum
5 sections · 21 lessons · 596 steps
1
Foundations
Optional - Skip if familiar with Python & Math
Essential Python and linear algebra fundamentals for deep learning. Start here if you need a refresher on Python programming or mathematical concepts.
2
Language Models Fundamentals
Build neural networks from scratch. Create an autograd engine, implement backpropagation, and develop character-level language models.
3
Deep Learning Internals
Master advanced neural network training techniques. Deep dive into batch normalization, initialization strategies, manual backpropagation, and hierarchical models.
Build a GPT from scratch. Understand self-attention, transformers, tokenization, and reproduce GPT-2 with production-grade training.
Demonstrate your mastery by studying the complete evolution of a GPT-2 training script, then building it yourself from scratch.