Prompt Engineering for Developers
Master prompt engineering for production code — structured outputs, RAG, security, testing, and cost optimization across OpenAI, Claude, and Gemini APIs.
You’re already using AI in your code. Copilot suggests completions, ChatGPT debugs your errors, Claude reviews your PRs. But when you integrate LLMs into production applications — chatbots, data pipelines, code generation tools — prompt quality becomes an engineering discipline.
A bad prompt costs money (wasted tokens), creates security holes (prompt injection), and produces unreliable outputs (hallucinations). A good prompt is testable, versioned, optimized, and secure.
This course treats prompt engineering as a proper engineering practice:
- Write prompts that produce reliable, structured outputs across providers
- Build RAG pipelines that ground LLM responses in your data
- Secure your prompts against injection attacks (OWASP Top 10 for LLMs)
- Test prompts systematically with evaluation frameworks
- Ship prompts to production with versioning, A/B testing, and monitoring
What You'll Learn
- Apply advanced prompting techniques — few-shot, chain-of-thought, and system prompts — for reliable code generation
- Implement structured outputs using JSON mode, function calling, and Pydantic validation
- Build RAG pipelines that ground LLM responses in your own data
- Identify and mitigate prompt injection attacks using OWASP-recommended defenses
- Design evaluation frameworks that test prompt quality systematically
- Execute production prompt management — versioning, A/B testing, and cost optimization
After This Course, You Can
What You'll Build
Course Syllabus
Who Is This For?
- Developers building LLM-powered features into applications
- Engineers adding AI to existing products or building AI-native apps
- Anyone who calls AI APIs and wants to do it reliably, securely, and cost-effectively
Frequently Asked Questions
What programming experience do I need?
You should be comfortable with Python or JavaScript and understand REST APIs. This is a developer course — we write code, not just prompts.
Which AI APIs does this cover?
OpenAI (GPT-4.1, GPT-5), Anthropic (Claude 4), and Google Gemini. The principles apply across all providers.
How is this different from the basic Prompt Engineering course?
This course focuses on API integration, structured outputs, security, testing frameworks, and production management — the engineering side of prompting, not just the writing side.
Is there a certificate?
Yes. Complete all 8 lessons and quizzes to earn a verifiable Prompt Engineering for Developers certificate.
