Introduction to Large Language Models (LLMs) and Prompt Engineering

Introduction to Large Language Models (LLMs) and Prompt Engineering
Published 5/2025
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz, 2 Ch

Learn how to use and launch large language models (LLMs) like GPT, Llama, Claude T5, and BERT and design prompts for optimal AI workloads.

Introduction to Large Language Models (LLMs) and Prompt Engineering guides you to launch LLMs like GPT, Llama, Claude, T5, and BERT at scale. It presents a step-by-step approach to building and deploying LLMs, with real-world case studies to illustrate the concepts. It also covers how to begin your LLM journey with prompt engineering with optimal instruction placements and prompting across models. The video works toward building a Retrieval-Augmented Generation (RAG) system with LLMs. It fills a gap in the market by providing a guide to using LLMs and will be a valuable resource for anyone looking to use LLMs in their projects.

About the Instructor

Learn How To:

Apply large language models (LLMs) and use semantic search with them
Utilize principles of prompt engineering to build agents and a retrieval-augmented generation (RAG) bot with OpenAI and GPT-4
Understand how AI agents are built and operated
Who Should Take This Course:

Machine learning engineers with experience in ML and want to learn more about LLMs
Developers, data scientists, and engineers who are interested in using LLMs for their projects
Those who want the best outputs from Generative LLMs and Embedding models
Skill Level:

Beginner to Intermediate
Course requirement:

Python 3 proficiency with some experience working in interactive Python environments including Notebooks (Jupyter/Google Colab/Kaggle Kernels)