LLM Engineering: Master AI, Large Language Models & Agents

Learn the core concepts of LLM engineering, from fine-tuning and prompt engineering to building AI agents.
Duration: 1 Day
Hours: 3 Hours
Training Level: All Levels
img
Batch One
Thursday, May 15, 2025
12:00 PM - 03:00 PM (Eastern Time)
Batch Two
Thursday, June 12, 2025
12:00 PM - 03:00 PM (Eastern Time)
Batch Three
Thursday, July 10, 2025
12:00 PM - 03:00 PM (Eastern Time)
Batch Four
Thursday, August 14, 2025
12:00 PM - 03:00 PM (Eastern Time)
Live Session
Single Attendee
$149.00 $249.00
Live Session
Recorded
Single Attendee
$199.00 $332.00
6 month Access for Recorded
Live+Recorded
Single Attendee
$249.00 $416.00
6 month Access for Recorded
Most Popular

About the Course:

This 3-hour live training is designed to provide a deep dive into Large Language Models (LLMs), their inner workings, and their role in AI-driven applications. You will explore how LLMs are trained, optimized, fine-tuned, and leveraged to build AI agents that can automate complex tasks. The session will include hands-on demonstrations, best practices, and industry use cases to help you master LLM engineering and apply it effectively in your projects. This live training will cover hands-on techniques to optimize, deploy, and integrate large language models for real-world applications.

Course Objectives:

  • Understand how LLMs function and their architecture.
  • Learn prompt engineering techniques for optimal responses.
  • Master fine-tuning and embedding models.
  • Build AI agents that interact with APIs and tools.
  • Deploy LLM-based applications efficiently.

Target Audience:

  • AI/ML Engineers & Data Scientists are looking to expand their LLM expertise.
  • Software Developers are interested in integrating AI into applications.
  • Tech Enthusiasts & Researchers keen on understanding LLMs.
  • Business & Product Leaders exploring AI-driven solutions.

Basic Knowledge:

  • Python programming (basic to intermediate)
  • Fundamentals of Machine Learning & NLP
  • Familiarity with APIs and cloud platforms (optional but helpful)

Curriculum
Total Duration: 3 Hours
Introduction to Large Language Models

  • What are LLMs? Evolution & Use Cases
  • Key architectures: Transformer, GPT, LLaMA, Claude
  • Pretraining vs. Fine-tuning vs. Retrieval-Augmented Generation (RAG)

Prompt Engineering & Optimization

  • Zero-shot, few-shot, and chain-of-thought prompting
  • Advanced prompt engineering techniques
  • Handling model biases & improving responses

Fine-Tuning & Embeddings

  • When & why to fine-tune LLMs
  • Using embeddings for search, recommendation, and personalization
  • Tools: OpenAI, Hugging Face, LangChain

Building AI Agents with LLMs

  • What are AI Agents? Role of LLMs in automation
  • Connecting LLMs with APIs, databases & real-world applications
  • Implementing multi-agent collaboration

Deployment & Real-World Applications

  • Running LLMs on cloud & edge
  • Cost optimization & performance tuning
  • Case studies: Chatbots, automation, coding assistants