7 Day AI Engineer Bootcamp
Vivian Aranha
Founder & AI Instructor at School of AI
This course is popular
5 people enrolled last week.
Build Production-Ready AI Systems in 7 Days — From LLMs to Agents
AI is moving from experimentation to real-world systems, yet most professionals face a major challenge: knowing how to move from models and prompts to production-ready AI applications.
Many courses teach isolated concepts—prompting, machine learning theory, or model APIs—but very few explain how modern AI systems are actually built, deployed, and managed.
This 7-Day AI Engineer Bootcamp is designed to close that gap.
In this hands-on program, you will learn how AI engineers design and build real systems using LLMs, embeddings, retrieval-augmented generation (RAG), AI agents, APIs, and production deployment patterns.
Instead of focusing only on theory, the course walks you through the complete AI engineering lifecycle: data, prompts, architecture, agents, deployment, monitoring, and scaling.
By the end of the program, you will build a complete AI system, such as a customer support agent, research assistant, or knowledge bot, and understand how to deploy and manage AI applications in real environments.
If you want to move beyond experimenting with AI and start building real AI products, this bootcamp will give you the frameworks, tools, and hands-on experience to do it.
What you’ll learn
Design, build, deploy, and operate production-ready AI systems using LLMs, RAG, agents, APIs, and AI Ops practices.
Build prompt-driven AI applications
Work with OpenAI APIs and Python
Create real AI features such as summarization and classification
Generate embeddings from documents
Store vectors using Chroma or FAISS
Build a “Chat with Your Docs” AI assistant
Understand reasoning loops and agent architectures
Build agents using frameworks like LangGraph or CrewAI
Design single-agent and multi-agent workflows
Build AI APIs using FastAPI
Design scalable AI endpoints
Test and deploy APIs locally or in the cloud
Implement logging and monitoring
Track performance and model responses
Handle hallucinations and failure cases
Design AI system architecture diagrams
Understand scaling and infrastructure patterns
Build and present a production-ready capstone project
Learn directly from Vivian
Vivian Aranha
AI architect with 2.2M+ learners, building enterprise-grade agentic systems
Who this course is for
Software Engineers exploring AI development
Developers who want to build real AI systems using APIs, agents, and modern AI frameworks.Product managers and technical founders
Professionals who want to understand how AI products are designed, built, and deployed.Data professionals transitioning into AI engineering
Analysts & data scientists who want to expand into building end-to-end AI applications.
What's included
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 System in 7 Days
Go from AI fundamentals to building and deploying a full AI-powered application through a guided capstone project.
Learn Modern AI Engineering Tools
Work with LLM APIs, embeddings, vector databases, agent frameworks, FastAPI, and monitoring tools used in real AI systems.
Hands-On Projects Every Day
Each day includes practical labs where you build real AI features like prompt templates, RAG systems, agents, and APIs.
Understand the Full AI Engineering Lifecycle
Learn how AI systems move from idea to production, including data pipelines, deployment, monitoring, and scaling.
Join a Global AI Learning Community
Collaborate with learners worldwide, share projects, ask questions, and continue learning beyond the bootcamp.
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
31 lessons • 13 projects
Week 1
Day 1 – AI Engineering Foundations & Modern AI Stack
Day 2 – Data for AI & Prompt Engineering
Day 3 – LLMs, Embeddings & Retrieval-Augmented Generation (RAG)
Day 4 – Building AI Agents & Tool Use
Day 5 – Model Deployment & AI APIs
Day 6 – AI Ops, Monitoring & Optimization
Day 7 – AI System Design + Capstone Build
Schedule
Projects
5-7 hrs
Async content
5-7 hrs
Frequently asked questions
$20
USD
2 days left to enroll