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Generative AI & LLMsbeginner

How LLMs Work & Prompt Engineering

Understand what large language models are, why they make mistakes, and how to write prompts that get reliable results.

Lessons
11 lessons in 3 modules
Study time
about 6 hours
Duration
~3 weeks at your own pace

Free plan: counts as one of your 2 new courses this month. Plans

What you'll learn

  • Explain tokens, training and why LLMs hallucinate
  • Write clear prompts with context, examples and structure
  • Use AI for study, writing and coding while checking its work
  • Understand the basics of building an app on an LLM API

Syllabus

  1. Module 1How LLMs workJust enough theory.3 lessons
    1. What a language model isExplain next-token prediction in plain words.25 min
    2. Tokens, context windows and temperatureDescribe how input length and settings affect answers.30 min
    3. Training, fine-tuning and hallucinationsExplain why models make confident mistakes.30 min
  2. Module 2Prompting techniquesGet better answers.4 lessons
    1. Clear instructions and contextRewrite a vague prompt into a precise one.30 min
    2. Examples and output formatsUse examples and formats like tables or JSON.30 min
    3. Step-by-step reasoning and self-checksAsk for reasoning and verification on hard tasks.30 min
    4. Prompting for codeGet useful code from AI and review it properly.30 min
  3. Module 3Using AI responsiblyAccuracy, privacy and building.4 lessons
    1. Checking facts and sourcesVerify AI answers before relying on them.30 min
    2. Privacy, safety and academic honestyDecide what not to share with AI tools and how to use them honestly.30 min
    3. Building with an LLM APIDescribe how an app sends prompts to a model and handles replies.30 min
    4. Project: your personal prompt libraryCreate reusable prompts for your study or work tasks.40 min