Prompt Engineering Mastery
Frameworks and best practices to get the most out of any AI model
What you'll be able to do
- Write reliable, well-structured prompts for real tasks
- Apply techniques like few-shot, chain-of-thought, and role prompting
- Reduce hallucination and steer model behavior
- Build and evaluate repeatable prompt workflows
Before you start
- Basic comfort using AI chat tools
- Clear writing skills
- No coding required to start
Phase 1 · Foundations of Prompting
How LLMs Read Your Prompt
Tokens, context windows, temperature, and why models behave the way they do. The mental model behind every good prompt.
- OpenAI: Prompt Engineering Guidedocfree
- Anthropic: Prompt Engineering Overviewdocfree
- learnprompting.org: Basics (free)coursefree
- Explain tokens vs. words with a real example
- Show how temperature changes output
- Map a context window budget for a long task
Core Prompting Patterns
Zero-shot, few-shot, role prompting, and structured output. The building blocks you will reuse everywhere.
- Prompt Engineering Guide (promptingguide.ai)docfree
- Anthropic: Use examples (multishot)docfree
- Google: Prompting guide 101 (free PDF)articlefree
- Convert a zero-shot prompt to few-shot and compare
- Force valid JSON output with a schema
- Use role + tone constraints for a brand voice
Phase 2 · Advanced Reasoning & Frameworks
Chain-of-Thought & Reasoning Techniques
CoT, self-consistency, ReAct, and step-back prompting to unlock reliable reasoning on hard tasks.
- Anthropic: Let Claude think (chain of thought)docfree
- ReAct: Reasoning + Acting (paper)articlefree
- DeepLearning.AI: ChatGPT Prompt Engineering for Developers (free)coursefree
- Improve a math/logic task with CoT
- Build a ReAct loop with a tool call
- Measure accuracy gain before/after
Prompt Frameworks & Reusable Templates
RTF, CRISPE, and Costar frameworks; building a personal prompt library and system prompts that scale.
- Anthropic: System promptsdocfree
- CO-STAR framework (writeup)articlefree
- Anthropic Prompt Librarydocfree
- Author a reusable system prompt with variables
- Build a 5-prompt personal library
- Document when each framework fits
Phase 3 · Real-World Applications
Prompting for Production: Evaluation & Guardrails
Reducing hallucinations, prompt injection defense, evals, and keeping outputs safe and consistent.
- Anthropic: Reduce hallucinationsdocfree
- OWASP Top 10 for LLM Applicationsarticlefree
- Anthropic: Define success & build evalsdocfree
- Write an eval set for a real task
- Harden a prompt against injection
- Add citation/grounding to reduce hallucination
Capstone: Ship a Prompt-Powered Tool
Design, test, and document a real assistant (support bot, writing aid, or data extractor) end to end.
- OpenAI Cookbook (examples)repofree
- Anthropic Cookbook (GitHub)repofree
- Spec the task + success metric
- Iterate prompts against the eval set
- Publish a writeup of what worked
Frequently asked
Is the Prompt Engineering Mastery roadmap free?+
Yes. The entire Prompt Engineering Mastery roadmap and every curated resource is free to follow on Commit. You can track your progress, keep a daily streak, and earn a shareable certificate at no cost — there is no paywall.
How long does the Prompt Engineering Mastery roadmap take to complete?+
About 70 hours of focused study across 6 courses and 3 stages. At roughly one hour a day that is about 3 months; you can move faster by studying more each day.
Do I get a certificate for finishing the Prompt Engineering Mastery roadmap?+
Yes. When you complete the roadmap on Commit you receive a verifiable certificate of completion that you can add to LinkedIn and your public Commit profile as proof of what you finished.
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