Complete AI Engineer 3 Day Bootcamp
Vivian Aranha
Founder & AI Instructor at School of AI
This course is popular
5 people enrolled last week.
Build Production-Ready AI Apps with RAG, Agents, and Real Deployment
AI is transforming software development, but many professionals struggle to move beyond tutorials and actually build real AI applications. Most courses focus on theory or simple prompts, without teaching how to design complete AI systems.
This bootcamp bridges that gap.
In three intensive days, you will learn the core capabilities of modern AI engineering: working with LLM APIs, prompt engineering, Retrieval-Augmented Generation (RAG), AI agents, and deployment. Instead of just learning concepts, you will build real applications step by step—from your first AI-powered app to a document-aware RAG system and an autonomous AI agent.
By the end of the program, you will have designed, built, and deployed a production-ready AI application. You’ll leave with practical skills, a portfolio project, and the confidence to build intelligent AI systems for real-world use cases.
What you’ll learn
Learn to build and deploy real AI apps using LLMs, RAG, and agents—transforming from AI user to production-ready AI engineer.
Write Python scripts to call LLM APIs and handle responses
Design prompts and parameters to control model behavior
Build a simple AI assistant with conversation memory
Use system prompts and role prompting techniques
Generate structured outputs like JSON and formatted responses
Experiment with prompt chaining to improve reasoning
Ingest documents, chunk text, and generate embeddings
Store and retrieve vectors using a vector database
Build a document chat system that answers questions from PDFs
Integrate web search and APIs into AI workflows
Implement tool calling and structured outputs
Build a research assistant that gathers and summarizes information
Implement task loops, tool usage, and agent memory
Build an agent that researches a topic and generates a report
Design workflows for multi-step AI reasoning and execution
Build a backend API using FastAPI
Connect AI pipelines to application endpoints
Add logging, monitoring, and cost optimization practices
Learn directly from Vivian
Vivian Aranha
AI architect with 2.2M+ learners, building enterprise-grade agentic systems
Who this course is for
Software Developers Transitioning into AI Engineering
Want to build AI-powered applications using LLM APIs, RAG systems, and agent workflows.Data Scientists Expanding into AI Application Development
Want to move beyond models and build real AI products and deploy production systemsTech Professionals and Builders Creating AI Products
PMs, founders, and engineers who want to build and launch practical AI applications.
What's included
Live sessions
Learn directly from Vivian Aranha in a real-time, interactive format.
Lifetime access
Go back to course content and recordings whenever you need to.
Community of peers
Stay accountable and share insights with like-minded professionals.
Certificate of completion
Share your new skills with your employer or on LinkedIn.
Build a Complete AI Application in Just 3 Days
Go from zero to a working AI system by building a real application step-by-step using LLM APIs, RAG pipelines, and AI agents. You will design, develop, and deploy a production-ready project during the bootcamp.
Hands-On AI Engineering Labs
Learn by doing. Every major topic includes guided labs where you implement prompts, APIs, retrieval pipelines, and agents so you gain practical experience building real AI systems.
Master Modern AI Application Architecture
Understand how AI apps are structured—from frontend to backend orchestration, context management, vector databases, and tool integrations used in real production systems.
Build AI Agents that Use Tools and Perform Tasks
Create autonomous AI agents capable of planning steps, calling tools, retrieving information, and generating structured outputs for complex workflows.
Leave with a Portfolio-Ready AI Project
Finish the bootcamp with a fully working AI application, a deployable backend API, and a GitHub project you can showcase in your AI engineering portfolio.
Maven Guarantee
This course is backed by the Maven Guarantee. Students are eligible for a full refund up until the halfway point of the course.
Course syllabus
61 lessons • 9 projects
Week 1
Day 1 — Foundations of AI Engineering: 1. AI Engineering Landscape
Day 1 — Foundations of AI Engineering: 2. Large Language Models
Day 1 — Foundations of AI Engineering: 3. Prompt Engineering
Day 1 — Foundations of AI Engineering: 4. Using LLM APIs
Day 1 — Foundations of AI Engineering: 5. Building Your First AI App
Day 1 - Hands-On Exercises
Day 2 — AI Applications & RAG Systems: 1. AI Application Architecture
Day 2 — AI Applications & RAG Systems: 2. Retrieval Augmented Generation (RAG)
Day 2 — AI Applications & RAG Systems: 3. Knowledge Base Systems
Day 2 — AI Applications & RAG Systems: 4. Context Management
Day 2 — AI Applications & RAG Systems: 5. Building AI Tools
Day 2 - Hands-On Exercises
Day 3 — AI Agents & Production Deployment: 1. AI Agents
Day 3 — AI Agents & Production Deployment: 2. Agent Architecture
Day 3 — AI Agents & Production Deployment: 3. Building Autonomous Systems
Day 3 — AI Agents & Production Deployment: 4. Deploying AI Applications
Day 3 — AI Agents & Production Deployment: 5. Production AI Engineering
Day 3 - Hands-On Exercises
Schedule
Live sessions
1-2 hrs
Projects
5-7 hrs
Async content
12-15 hrs
Frequently asked questions
$50
USD
7 days left to enroll