Course curriculum

  • 1
    Introduction to the Course
    • Course Overview
    • Course Handouts
  • 2
    Getting Started with Training LLMs from Scratch
    • Introduction to Training LLMs From Scratch
    • What do you mean by Training LLMs from Scratch?
    • Why train your own LLMs?
    • Quiz
  • 3
    Important Concepts for Training LLMs from Scratch
    • Chinchilla Scaling Laws
    • Parallel and Distributed paradigm
    • Data Parallelism
    • Model Parallelism
    • Pipeline Parallelism
    • Fully Sharded Data Parellelism/ZeRO 3
    • Tensor Parallelism
    • 2D and 3D Parallelism
    • Quiz
  • 4
    Steps involved in Training LLMs from Scratch
    • Overview of Steps Involved in Training LLMs from Scratch
    • Training Data Curation
    • Data preprocessing
    • Tokenization
    • Model Architecture
    • Model Evaluation
    • Quiz
  • 5
    Training your own LLMs from Scratch
    • Estimate Cost of Training LLMs from Scratch
    • Hands on - Setting up runpod and intro
    • Hands on - Dataset curation and preprocessing
    • Hands on - Training BPE Tokenizer
    • Hands on - Training LLMs from Scratch using DeepSpeed ZeRO 3/FSDP Distributed Training on 8 GPUs
    • Quiz
    • Assignment
  • 6
    Aligining LLM with Human Preferences
    • Recap of Instruction Following LLM
    • Introduction to Alignment Methods
    • Reinforcement Learning from Human Feedback (RLHF)
    • Aligning LLMs to Human Preferences with RLHF
    • DPO and IPO
    • Preference tuning LLMs with DPO
    • Quiz
  • 7
    What Next?
    • Recent Advancements
    • Share your Experience!