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Intro to LLMs

Get started with Large Language Models. Understand how they work and how to use them effectively.

Schedule

April 18, 2026

Duration

2 Hours

Project

Hands-on capstone

Detailed Curriculum

3 practical sections built around live exercises.

01

How LLMs think in tokens

Develop a practical mental model for what language models are good at and where they fail.

Topics covered

  • LLMs vs search engines and traditional software
  • Tokens, context windows, and model memory
  • Temperature, system prompts, and instruction hierarchy
  • Hallucinations and verification habits

Hands-on lab

Compare several prompts and inspect how small context changes affect the output.

02

Prompting for useful outputs

Move from casual prompting to repeatable task design.

Topics covered

  • Role, task, context, and format
  • Examples and constraints
  • Structured output requests
  • Prompt iteration and evaluation

Hands-on lab

Create a reusable prompt template for research, summarization, or document drafting.

03

Workflow integration

Learn where LLMs fit inside day-to-day business and engineering workflows.

Topics covered

  • Human review loops
  • Document and data workflows
  • Tool selection between ChatGPT, Claude, and Gemini
  • Privacy and data handling basics

Hands-on lab

Map one current workflow and redesign it with a practical LLM assist step.

What You Get Out Of It

Concrete capabilities you should leave with.

Explain LLM concepts without jargon

Create clearer prompts for reliable outputs

Recognize when an LLM should not be trusted blindly

Identify useful LLM opportunities in real workflows