Introduction to Large Language Models (LLMs) and Prompt Engineering by Pearson
With Pearson
Liked by 1 user
Duration: 4h 59m
Skill level: Intermediate
Released: 2/26/2026
Course details
Do you know how to launch LLMs like GPT, Llama, Claude, T5, and BERT at scale? This course provides a step-by-step approach for building and deploying LLMs, and it includes real-world case studies that illustrate the concepts. It covers how to begin your LLM journey with prompt engineering by showing how to make optimal instruction placements across models. And it explains how to build a Retrieval-Augmented Generation (RAG) system.
Whether you are a machine learning engineer, LLM developer, data scientist, or engineer who is interested in using LLMs for projects, this course is designed to help you get the best outputs from your models. It is helpful if you already have some Python 3 proficiency and have some experience working in interactive Python environments including Notebooks (examples: Jupyter, Google Colab, Kaggle Kernels, etc.).
Note: This course is provided by Pearson. We are pleased to host this content in our library.
Skills you’ll gain
Earn a sharable certificate
Share what you’ve learned, and be a standout professional in your desired industry with a certificate showcasing your knowledge gained from the course.
-
Showcase on your LinkedIn profile under “Licenses and Certificate” section
-
Download or print out as PDF to share with others
-
Share as image online to demonstrate your skill
Meet the instructor
Contents
What’s included
- Learn on the go Access on tablet and phone
Similar courses
Download courses
Use your iOS or Android LinkedIn Learning app, and watch courses on your mobile device without an internet connection.