Prompt Engineering: Free Iterative Learning Course

This self‑paced course uses a simple summarization task to introduce the core techniques of prompt engineering. Through a series of iterative modules, you’ll learn how to craft effective prompts, add context and constraints, and refine your instructions to get better results from AI models.

Course Overview

By the end of this course you will:

Understand what prompts are and how they influence AI outputs.
Learn to add context and specify constraints to improve responses.
Practise iteratively refining prompts for better results.
Apply these techniques to a final project of your choice.

Module 1: Understanding Prompts & Baseline Example

Objective: Learn what a prompt is and try a baseline summarisation task.

Prompts are your inputs into an AI system. They are the conversation starters that tell the model what you need. A prompt can be as simple as a single sentence or a detailed set of instructions. To start, you’ll ask an AI model to summarise an article using a basic prompt.

Exercise

Choose a short article or use this sample text:
In 2025, renewable energy capacity continued to soar, with solar and wind installations breaking records worldwide. Experts predict that by 2030, over half of global electricity will come from clean sources.
Open your preferred chatbot (e.g., ChatGPT) and enter the prompt:
Summarise this article in a few sentences.
Review the AI’s response. Note its length, tone and the information it includes.

Tip: The AI will respond based on your prompt’s wording. Keep the prompt simple for this first attempt.

Module 2: Adding Context

Objective: See how adding context or a persona changes the AI’s output.

Giving the model a role or context often results in more tailored responses. For example, asking an AI to act as an expert changes its tone and focus.

Exercise

Using the same article, enter the following prompt:
You are an experienced news editor. Summarise this article for an audience of 12‑year‑olds in three sentences.
Compare this response to the baseline summary. How did the tone, vocabulary and level of detail change?
Try another persona (e.g., “As a science teacher…”). Observe how the output adjusts.

Tip: Providing context helps the model understand your expectations and tailor its response appropriately.

Module 3: Being Specific With Constraints

Objective: Practise adding constraints to produce more targeted outputs.

Specific prompts lead to more precise results. You can specify format (bullet points), length, audience or focus.

Exercise

Refine your prompt by adding constraints:
List the three most important facts from this article as bullet points. Explain each in one sentence.
Review the response. Does it follow the requested format? Are the key facts clear?
Experiment with different constraints:
Summarise the article in exactly 40 words. or
Explain the article’s significance in two sentences using simple language.

Tip: The more specific your instructions, the more controlled the output will be. Constraints help you achieve the length, tone or structure you need.

Module 4: Iterative Refinement

Objective: Learn to refine prompts over multiple rounds to improve the result.

Prompt engineering is iterative. After receiving a response, you can clarify instructions or add new constraints to enhance the output.

Exercise

Start with the persona prompt from Module 2. After reviewing the summary, follow up with additional instructions, such as:
Great! Now shorten each sentence to fewer than ten words.
Observe how the AI refines its output. If necessary, continue iterating: ask it to adjust the tone, include or exclude certain details, or format the response differently.
Document each prompt and response. Reflect on which prompts produced the most useful output and why.

Tip: Treat the AI like a collaborator. Refining your instructions step by step helps the model zero in on your goals.

Module 5: Final Project

Objective: Apply all the techniques you’ve learned to a new piece of text.

Choose an article, blog post or report that interests you. Use context, constraints and iterative refinement to craft a polished summary or analysis.

Steps

Read your chosen text and identify the key information you want to extract.
Write an initial prompt (Module 1 style) and capture the AI’s output.
Add context by assigning a role or audience (Module 2).
Introduce constraints to shape the response (Module 3).
Iteratively refine the output until you’re satisfied (Module 4).
Submit your final prompt and the AI’s final response as your project deliverable.

Conclusion & Next Steps

Congratulations on completing this course! You’ve seen how adding context, specifying constraints and iterating prompts can dramatically improve AI outputs. Continue practising with new tasks—compose emails, brainstorm ideas or draft reports—and observe how the AI responds.

For deeper reading on effective prompt design, visit guides like MIT’s “Effective Prompts for AI”.
Staying curious and experimenting will help you master prompt engineering in any domain.