By Jasmin Sultana Shimu, crafted with insights from ChatGPT
A structured journey from foundational prompting to advanced LLM system design.
This repository provides a hands-on, self-paced curriculum for learning Prompt Engineering using ChatGPT (GPT-4 / GPT-4o) and modern LLM ecosystems.
It’s built for developers, students, and professionals who want to design, optimize, and deploy AI-powered workflows confidently.
Inspired by:
Vanderbilt University • DeepLearning.AI • LearnPrompting.org • Udemy • FreeCodeCamp
| Audience | Focus |
|---|---|
| 🧑💻 CSE Students | Learn prompt engineering as a programming skill and apply it to projects and automation. |
| 💼 Developers | Build, test, and document intelligent LLM-based apps. |
| 🧠 Non-Coders & Professionals | Boost productivity, writing, and research using prompt frameworks. |
| 🤖 AI Enthusiasts | Explore reasoning frameworks, multi-agent systems, and ethical AI design. |
By completing this course, you will:
- Understand and apply prompt engineering principles effectively.
- Master structured prompting, chain-of-thought, and reasoning techniques.
- Build prompt-driven apps, AI assistants, and RAG-based workflows.
- Apply safe, ethical, and transparent AI design practices.
- Prepare for Prompt Engineer, LLM Specialist, or AI Developer roles.
Prompt Architecture • LLM Reasoning • API-Based Prompting
Chain-of-Thought & ReAct Design • RAG Grounding • Ethical Prompting
AI-Assisted Coding • Automation with ADA • Multi-Agent Workflows
| Level | Duration | Focus |
|---|---|---|
| 🟢 Beginner (Modules 0–3) | 2–3 weeks | Core LLM principles & prompt basics |
| 🟡 Intermediate (Modules 4–6) | 3–4 weeks | Patterns, few-shot learning, reasoning |
| 🔵 Advanced (Modules 7–10) | 4–6 weeks | Systems, automation, ethics |
| 🧩 Bonus + Capstones | 1–2 weeks | Portfolio, review, certification |
Total Duration: 10–14 weeks (self-paced)
- Track 0 – AI Literacy Bootcamp: AI fundamentals, responsible use, and collaboration.
- Track A – Foundations: Prompt anatomy, tone control, and evaluation methods.
- Track B – Intermediate: Prompt patterns, reasoning frameworks, and RAG design.
- Track C – Advanced: Agentic workflows, automation, ADA, and ethical design.
- Bonus Track: No-code prompting for creativity and productivity.
- Capstone I – Specialized AI Assistant:
Create a domain-specific assistant (education, marketing, data science). - Capstone II – Master Engineer Challenge:
Build a team-based, multi-agent system with evaluation and safety mechanisms.
- 🏅 Explorer Badge: Modules 0–3
- ⚙️ Engineer Badge: Modules 4–6
- 🧱 Architect Badge: Modules 7–10
Includes AI-assisted rubric grading, peer challenges, and leaderboard ranking.
GPT-4 / GPT-4o • Claude 3.5 • Gemini Advanced • LangChain • LlamaIndex • DSPy
Midjourney • Runway • ElevenLabs • Perplexity AI • Zapier • Make • GitHub Copilot • MkDocs
Aligned with:
- DeepLearning.AI Prompt Engineering Certificate
- OpenAI Developer Path
- Google AI Essentials
- IEEE / ISO AI Ethics Guidelines
Career Path: Prompt Engineer → LLM Specialist → AI Architect → Researcher / Consultant
- Coursera – Prompt Engineering for ChatGPT (Vanderbilt University)
- DeepLearning.AI – ChatGPT Prompt Engineering for Developers
- Udemy – Prompt Engineering: Getting Future Ready
- LearnPrompting.org – Free Open Curriculum
- FreeCodeCamp – Prompt Engineering Tutorials
- Complete all modules (0–10) and the bonus section.
- Submit Capstone Projects I & II.
- Publish your portfolio and documentation on GitHub.
- Earn your certification and digital badges.
- Apply your skills in research or industry.
Licensed under CC BY-NC 4.0.
You may share and adapt this material for non-commercial purposes with attribution.