7-Day Practical AI Bootcamp: Build AI Apps, RAG, and Agents

Artificial Intelligence is changing how software, business, research, education, and productivity tools are built. But many AI courses spend too much time on theory and not enough time building practical applications.This course is different.In this hands-on 7-day AI bootcamp, you will learn modern AI by building real projects from scratch. You will start with a simple AI assistant, then move into prompt engineering, AI-powered applications, PDF chat using RAG, autonomous agents, multi-agent workflows, and a final deployable AI knowledge base assistant.This course is designed for beginners to intermediate learners who want practical AI skills without getting lost in heavy machine learning theory. You do not need a deep math or data science background. The focus is on building working AI applications using tools that developers, students, analysts, managers, and entrepreneurs can use immediately.Throughout the bootcamp, you will build seven practical projects:AI AssistantPrompt Engineering PlaygroundAI Resume AnalyzerPDF Chat Assistant with RAGAutonomous Research AgentMulti-Agent Content TeamAI Knowledge Base Assistant with DockerBy the end of this course, you will understand how modern AI applications are structured, how to work with LLMs, how to write better prompts, how to build RAG pipelines, how AI agents work, and how to package an AI app for deployment.This is not just a theory course. Every day includes a hands-on lab and a portfolio-ready deliverable.What You Will LearnUnderstand modern AI, Generative AI, and Large Language ModelsBuild your first AI assistant using Python and StreamlitWrite stronger prompts using roles, rules, context, and output formatsBuild a prompt engineering playgroundCreate an AI Resume AnalyzerExtract text from PDF, TXT, and DOCX filesBuild a PDF Chat Assistant using RAGUse ChromaDB as a local vector databaseUnderstand embeddings and semantic searchBuild an autonomous research agentCreate a multi-agent content workflowPackage an AI application with DockerPrepare a portfolio-ready GitHub projectUnderstand responsible AI basics and safety guardrailsWho This Course Is ForThis course is for:Beginners who want to learn practical AIDevelopers who want to build AI applicationsStudents building portfolio projectsAnalysts and managers who want hands-on AI skillsEntrepreneurs exploring AI product ideasProfessionals transitioning into AIInstructors who want a practical AI project roadmapRequirementsBasic Python knowledge is helpfulBasic command line knowledge is helpfulNo machine learning background requiredNo advanced math requiredA computer with Python installedOptional: OpenAI API keyOptional: Ollama for local LLM usageCourse OutcomeBy the end of this course, you will not just understand AI concepts — you will have built real AI applications that you can show in your portfolio, resume, interviews, GitHub, or business demos.Final Course PromiseIn one week, you will go from basic AI concepts to building and packaging practical AI applications using LLMs, prompt engineering, RAG, agents, multi-agent systems, and Docker.