Prompt Engineering for Full-Stack Developers

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Prompt Engineering Fundamentals for Developers

Learn the fundamentals of prompt engineering for developers. Understand why LLMs are the new "super IDE", how they interpret code instructions, context windows, model selection, and the difference between deterministic and creative prompts.

Please enroll in this course to access the modules.

Learning objectives Understand why LLMs are the new "super IDE" for developers Learn how LLMs interpret code instructions Master context windows for code (very important!) Select appropriate models for coding tasks Differentiate between deterministic vs creative code prompts Write structured prompts vs vibe-based natural prompts

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Core Prompt Patterns for Coding

Master core prompt patterns for coding tasks. Learn code generation, refactoring, debugging, architecture design, API design, file system design, component generation, and multi-prompt chaining patterns.

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Learning objectives Master code generation pattern Learn refactor pattern for improving existing code Understand debugging pattern for finding and fixing bugs Apply architecture design pattern Generate API designs using prompts Create file system design prompts Generate component prompts (React, Vue, Next.js) Create backend service prompts (Django, Flask, Node.js, FastAPI) Implement multi-prompt chaining for large features

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Vibe Coding – Natural Language to Production Code

Learn "Vibe Coding" - converting ideas to working code without writing boilerplate. Master conversational refactoring, natural-language scaffolding, and turning design mockups into code.

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Learning objectives Understand what "Vibe Coding" is Convert ideas → working code without writing boilerplate Master conversational refactoring Use natural-language scaffolding for Django views, serializers, models Build React components using natural language Generate SQL queries based on rules Turn design mockups into code

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Prompting for Backend Development

Speed up backend development 4× using structured prompt templates. Learn REST API generation, CRUD automation, ORM model generation, database schema prompts, migrations, business logic, API documentation, and performance optimization.

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Learning objectives Generate REST APIs using prompts Automate CRUD boilerplate creation Generate ORM models (Django / SQLAlchemy / Prisma) Create database schema prompts Write migrations with AI Write business logic with domain constraints Generate API documentation Optimize backend performance using prompting

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Prompting for Frontend Development

Produce clean frontend components with proper props, states, and logic. Learn React/Next.js component generation, state management scaffolding, styling prompts, UI debugging, Figma to code conversion, reusable components, and accessibility.

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Learning objectives Generate React / Next.js components using prompts Scaffold state management Use styling prompts (Tailwind, CSS Modules, Styled Components) Debug UI rendering issues via prompts Convert Figma designs to code Implement reusable UI components via prompting Create accessibility prompts

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AI-Assisted System Design for Full-Stack Developers

Use LLMs as a senior architect to plan systems rapidly. Learn to generate architecture diagrams, design microservices, create data flow diagrams, choose design patterns, generate scalable app boilerplate, and use multi-agent prompting.

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Learning objectives Generate architecture diagrams using prompts Design microservices through prompting Create data flow + sequence diagrams Choose correct design patterns Generate boilerplate for scalable apps Use multi-agent prompting for large systems (AI as architect + reviewer + tester)

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Prompting for Debugging & Optimization

Solve bugs 2–5× faster with step-by-step debugging prompts. Learn debugging patterns, error-log prompting, security audits, performance optimization, refactoring entire codebases, and advanced "fix-this-file" instructions.

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Learning objectives Master debugging pattern: "Find the bug → explain → propose fix → rewrite file" Use error-log prompting Perform security audit prompting (OWASP) Optimize performance using prompts Refactor entire codebases using structured prompting Apply "Fix-this-file" advanced instructions

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Full-Stack Workflow Automations Using Prompting

Automate 40–60% of "boring tasks" using prompts. Learn to generate test cases, auto-generate documentation, create API collections, write Git commit messages, generate CI/CD pipelines, and create deployment scripts.

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Learning objectives Generate test cases (backend + frontend) Auto-generate documentation Auto-generate API collections (Postman / Thunderclient) Write Git commit messages using prompts Write CI/CD YAML pipelines using prompts Generate deployment scripts (AWS / Docker / NGINX)

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Building LLM-Powered Full-Stack Apps

Integrate LLMs into real enterprise apps safely. Learn prompt engineering for RAG applications, API calling, tool invocation, LangChain/LlamaIndex integration, structured outputs, AI agents, and handling model hallucination in production.

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Learning objectives Engineer prompts for RAG applications Use API calling & tool invocation prompts Integrate LangChain / LlamaIndex with Django, Node.js Create structured outputs using JSON schema prompts Build AI agents inside full-stack apps Handle model hallucination in production