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Generative AI: Prompt Engineering Basics

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  • Explain the concept, relevance, and best practices of prompt engineering to guide generative AI models in producing meaningful, accurate outputs.

  • Apply prompt engineering techniques to text prompts, improving the reliability and quality of large language models.

  • Practice prompt engineering techniques and approaches, including interview pattern, chain-of-thought, tree-of-thought, to improve prompt outcomes.

  • Explore commonly used tools for prompt engineering to aid with prompt engineering.

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Description

🎯 Course Title:

Generative AI: Prompt Engineering Basics

Course Duration:

4 to 6 weeks (can be adapted for workshops or bootcamps)

Target Audience:

Beginners to intermediate learners (non-programmers welcome)

Prerequisites:

  • Basic digital literacy

  • Familiarity with ChatGPT or similar AI tools (optional but helpful)


🗂️ Course Modules Overview

Module 1: Introduction to Generative AI

  • What is Generative AI?

  • Overview of LLMs (Large Language Models)

  • Use cases: text generation, summarization, translation, code generation, image generation

  • Tools overview: ChatGPT, Claude, Gemini, DALL·E, Midjourney, etc.

Hands-On: Try simple prompts in ChatGPT or Claude


Module 2: Understanding Prompt Engineering

  • What is a prompt?

  • Types of prompting:

    • Zero-shot

    • One-shot

    • Few-shot

  • Prompt structure and formatting

  • Importance of clarity and instruction

Activity: Craft zero-shot and few-shot prompts for rewriting text


Module 3: Prompt Design Techniques

  • Role prompting (e.g. “Act as a…”)

  • Chain of Thought prompting

  • Instructional prompting (imperative tone, constraints)

  • Controlling tone, style, format

  • Avoiding hallucinations

Lab: Rewrite prompts to improve output quality


Module 4: Image Prompting Basics

  • Introduction to text-to-image tools (DALL·E, Midjourney)

  • Prompt structure for visual generation

  • Styling keywords (e.g. “hyperrealistic”, “minimalist”, “cyberpunk”)

  • Parameters and modifiers (e.g. resolution, aspect ratio)

Hands-On: Generate an image using DALL·E or Midjourney


Module 5: Advanced Prompting Techniques

  • Prompt chaining & context preservation

  • Dynamic prompt injection

  • Prompt templates for automation

  • API-based prompt engineering (e.g. OpenAI API)

Project Idea: Build a prompt-driven mini-app (e.g. blog post generator)


Module 6: Ethics, Safety & Limitations

  • AI bias and fairness

  • Misuse of generative AI (deepfakes, misinformation)

  • Safety filters and guardrails

  • Prompting for trustworthy outputs

Discussion: Review real-world examples of responsible vs irresponsible prompting


🧪 Assessment & Projects

  • Weekly prompt challenges

  • Final Project: Create a prompt toolkit (for writing, design, coding, etc.)

  • Peer reviews and reflection logs

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