Prompt Engineering & AI Communication
Communicate with AI the way professionals do — and get dramatically better results.
The single biggest determinant of what you get from AI is how you communicate with it. This programme teaches prompt engineering as a practical, transferable skill — not just for one AI tool, but across the entire modern AI ecosystem. You'll learn how LLMs interpret language, how to structure prompts for different tasks, and how to iterate toward exactly the result you need.
Prerequisites
- —Basic familiarity with at least one AI assistant (ChatGPT, Claude, Gemini)
- —No technical background required
What you'll be able to do
- ✓Write prompts that consistently produce accurate, useful, and well-structured outputs
- ✓Apply different prompting techniques for different types of tasks
- ✓Use role prompting, few-shot examples, and chain-of-thought reasoning effectively
- ✓Iterate and refine AI outputs through skilled follow-up prompting
- ✓Adapt prompting approaches for text, code, research, and creative tasks
- ✓Get dramatically better results from any AI system you use
Curriculum
1. How LLMs Interpret Prompts
- ·Why prompt wording changes everything
- ·How models predict and generate token by token
- ·What the model 'knows' and 'doesn't know'
- ·Common failure modes and how to avoid them
2. Prompt Structure
- ·The anatomy of a high-quality prompt
- ·Instructions, context, examples, and constraints
- ·What to include — and what to leave out
- ·Formatting prompts for clarity
3. Core Prompting Techniques
- ·Zero-shot vs. few-shot prompting
- ·Chain-of-thought reasoning for complex tasks
- ·Role and persona prompting
- ·Constrained generation for precise outputs
4. Iterative Prompting
- ·Treating AI dialogue as an iterative process
- ·How to refine and improve AI outputs through conversation
- ·When to restart vs. when to continue refining
- ·Building multi-turn workflows with AI
5. Prompting Across AI Systems
- ·Differences between ChatGPT, Claude, and Gemini
- ·System prompts and their role in shaping AI behaviour
- ·API-level prompting vs. chat interface prompting
- ·Adapting your approach across models
6. Prompting for Text & Writing
- ·Writing assistance prompts that produce professional results
- ·Editing, rewriting, and tone adjustment prompts
- ·Summarisation and synthesis prompts
- ·Template and structure generation
7. Prompting for Research & Analysis
- ·Research prompts that find, compare, and synthesise
- ·Fact-checking and source evaluation prompting
- ·Data interpretation and insight extraction
- ·Building research workflows with chained prompts
8. Prompting for Code & Creative Tasks
- ·Code generation, debugging, and explanation prompts
- ·Creative task prompting: storytelling, copywriting, ideation
- ·Image generation prompts: structure and techniques
- ·Building prompt libraries for repeated tasks
Format & Duration
Duration
4 weeks
Format
Self-Paced
Level
Beginner
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