OpenAI: Prompt Engineering for Developers
Design reliable, cost-efficient prompts using personas, few-shot examples, chain-of-thought, prompt chaining, and injection defense. Five hands-on labs from classifier to document pipeline.
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About This Course
Course Curriculum
10 Lessons
System Prompts, Personas & Zero-Shot Design
Learn how system prompts work, how to assign personas, design zero-shot instructions, and control output format — the foundation of reliable prompt engineering.
Persona-Based Assistants - Lab Exercises
Build three AI assistants with distinct personas — customer support agent, code reviewer, and technical writer — using the same underlying question to demonstrate system prompt power.
Few-Shot Prompting & Chain-of-Thought
Learn how to guide model behavior with example pairs, when chain-of-thought improves accuracy, and how to use self-consistency for reliable outputs.
Ticket Classifier with Few-Shot Examples - Lab Exercises
Build a support ticket classifier using few-shot examples that routes to engineering, billing, or sales with ≥85% accuracy on a 20-ticket test set.
Advanced Techniques: ReAct, Meta-Prompting & Prompt Chaining
Master advanced prompt patterns: ReAct for reasoning + tool use, meta-prompting for self-improvement, prompt chaining for complex pipelines, and injection defense.
Prompt Chain & Injection Defense - Lab Exercises
Build a three-stage NLP pipeline (summarize → extract entities → classify sentiment) and a prompt injection interceptor that blocks known attack patterns.
Prompt Optimization at Scale
Learn token efficiency techniques, eval-driven prompt improvement loops, A/B testing, prompt versioning, and compression strategies for production prompts.
Prompt Optimization Lab - Lab Exercises
Build a prompt optimizer that takes verbose baseline prompts, applies compression techniques, and measures quality retention via automated LLM-as-judge evaluation.
Capstone Briefing: Intelligent Document Processor
Review all prompt engineering techniques from the course and get briefed on the capstone document processing pipeline you'll build next.
Capstone Project: Document Processor
Build a three-stage document processing pipeline: entity extraction (few-shot), classification (CoT), executive summary (persona) — with injection guard and per-stage cost tracking.
This course includes:
- 24/7 AI Instructor Support
- Live Lab Environments
- 5 Hands-on Lessons
- Completion Badge
Earn Your Badge
Complete all lessons to unlock the OpenAI Prompt Engineer achievement badge.
OpenAI Prompt Engineer
Awarded for completing Prompt Engineering for Developers. Demonstrates ability to design personas, apply few-shot prompting, build prompt chains with injection defense, and optimize prompts at scale using OpenAI models.
Skills You'll Earn
Complete all lessons in this course to earn this badge