Training and Deploying Open-Source LLMs on Bare Metal

Course Overview

Learn how to write practical AI applications via hands-on labs. You will design and develop Transformer models, ensuring data security in your work. The course covers AI transformer architectures, Python programming, hardware requirements, training techniques, and AI tasks like classification and regression. It includes hands-on exercises with open-source LLM frameworks, advanced topics like fine-tuning and quantization, and offers AI certification from Alta3 Research. Ideal for Python Developers, DevSecOps Engineers, and Managers or Directors, the course requires basic Python skills and provides access to a GPU-accelerated server for practical experience.

Objectives

• Train and optimize Transformer models with PyTorch.
• Master advanced prompt engineering.
• Understand AI architecture, especially Transformers.
• Write a real-world AI web application.
• Describe tokenization and word embeddings.
• Install and use frameworks like Llama-2.
• Apply strategies to maximize model performance.
• Explore model quantization and fine-tuning.
• Compare CPU vs. GPU hardware acceleration.
• Understand chat vs. instruct interaction modes.

Audience

• Project Managers
• Architects
• Developers
• Data Acquisition Specialists

Prerequisites

• Python – PCEP Certification or Equivalent Experience
• Familiarity with Linux