Complete Prompt Engineering & AI Vibe Coding Course (AI-Assisted Development Master Program)

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Introduction to AI-Assisted Coding

What is prompt engineering and vibe coding, how LLMs generate code, strengths and limitations, human+AI collaboration, when not to trust AI.

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Learning objectives Define prompt engineering and vibe coding Understand how LLMs generate code Know strengths, limitations, and when not to trust AI Apply human+AI collaboration model

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Understanding Large Language Models

Tokens and context windows, temperature and sampling, system prompts, instruction following, hallucination, model limitations.

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Learning objectives Understand tokens and context windows Use temperature and sampling effectively Apply system prompts and instruction following Recognize hallucination and model limitations

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Prompt Engineering Fundamentals

Clear instruction writing, role-based and constraint-based prompting, output formatting, step-by-step prompting, iterative refinement.

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Learning objectives Write clear instructions Use role-based and constraint-based prompting Control output formatting Apply step-by-step and iterative refinement

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Structured Prompt Patterns

Zero-shot, few-shot, chain of thought, self-consistency, tree of thought, reflection prompting.

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Learning objectives Apply zero-shot and few-shot prompting Use chain of thought, self-consistency, tree of thought Apply reflection prompting

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Code Generation Prompts

Generating functions and full applications, clean code, documentation, tests, comments.

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Learning objectives Generate functions and full applications Prompt for clean code, documentation, tests, comments

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Debugging with AI

Explaining errors, step-by-step debug prompts, root cause analysis, refactoring, performance optimization, code review prompts.

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Learning objectives Use AI to explain errors and debug step-by-step Apply root cause analysis and refactoring prompts Optimize performance and use code review prompts

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Building Applications with AI

Breaking requirements into prompts, backend/frontend/database generation, API design, authentication setup.

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Learning objectives Break requirements into prompts Generate backend, frontend, database schema Design APIs and set up authentication with AI

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AI for System Design

Architecture diagrams, scalable systems, microservices design, system planning, deployment strategy prompts.

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Learning objectives Generate architecture diagrams and design scalable systems Use AI for microservices and system planning Apply deployment strategy prompts

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AI in Software Lifecycle

PRDs, test cases, CI/CD scripts, Docker files, documentation.

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Learning objectives Write PRDs and generate test cases with AI Generate CI/CD scripts and Docker files Use AI for documentation

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AI Pair Programming

Live code refinement, incremental building, versioning prompts, prompt templates, coding speed optimization.

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Learning objectives Refine code live and build incrementally with AI Version prompts and use templates Optimize coding speed

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Prompt Chaining

Multi-step prompt workflows, breaking large tasks, memory-based prompts, reusable prompt libraries.

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Learning objectives Build multi-step prompt workflows Break large tasks and use memory-based prompts Maintain reusable prompt libraries

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AI Agents for Development

Tool calling, function calling, automated code fixers, multi-agent development, auto testing agents.

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Learning objectives Use tool and function calling Apply automated code fixers and multi-agent development Use auto testing agents

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Full Stack Web App with AI

Project planning, backend API, frontend UI, database integration, deployment.

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Learning objectives Plan and build full stack web app with AI Generate backend API, frontend UI, integrate database Deploy with AI assistance

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AI SaaS App Development

Idea validation, feature planning, subscription system, logging and monitoring.

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Learning objectives Validate ideas and plan features with AI Build subscription system Apply logging and monitoring

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Automation Projects

Web scrapers, data analysis scripts, workflow automation, AI bots.

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Learning objectives Build web scrapers and data analysis scripts with AI Implement workflow automation and AI bots

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Security in AI Coding

Detecting vulnerabilities, secure code prompts, preventing injection attacks, code review for security.

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Learning objectives Detect vulnerabilities with AI Use secure code prompts and prevent injection attacks Apply code review for security

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Responsible AI Use

Avoiding over-reliance, verifying AI code, licensing and legal awareness, ethical AI development.

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Learning objectives Avoid over-reliance and verify AI code Understand licensing and legal aspects Practice ethical AI development

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AI Productivity Framework

Personal prompt library, prompt templates, reusable AI workflows, rapid prototyping strategy.

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Learning objectives Build personal prompt library and templates Create reusable AI workflows Apply rapid prototyping strategy

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AI for Interview Preparation

Solving DSA with AI, mock interview simulation, system design practice, code review practice.

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Learning objectives Use AI for DSA and mock interviews Practice system design and code review with AI

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Becoming a 10x AI Developer

Thinking in prompts, AI as thought partner, architecture-level prompting, scaling development speed.

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Learning objectives Think in prompts and use AI as thought partner Apply architecture-level prompting Scale development speed