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From Curious Builder to Applied AI Engineer
Become an Applied AI Engineer in 4 Weeks — by building real systems, not watching lectures.
AI engineering has changed. Tools are evolving weekly, companies are hiring for real applied skill, and teams need people who can ship RAG pipelines, agents, and production-ready AI apps - not just talk about them.
This bootcamp helps you make that leap.
In 4 intense weeks, you’ll move from tinkering to deploying. You’ll build multiple full-stack AI applications, master LangChain, RAG, embeddings, MCP tools, and set up observability with LangFuse — all with real-world patterns used by modern AI teams. You’ll finish with a capstone project that proves you can design, deploy, and scale end-to-end AI systems.
You’ll graduate with:A recruiter-ready portfolio that signals real engineering capability
Confidence to build applied AI systems from scratch
Practical, career-accelerating skills used by AI engineers, founders, and product teams
A certificate and public demo that show you can deliver in real environments
This is not a passive course. It’s a fast, hands-on sprint where you’ll learn the way real engineers learn — If you’re ready to level up (fast), this is your place.
What you’ll learn
Become an Applied AI Engineer in 4 Weeks Build RAG pipelines, AI agents, MCP tools, and production-ready AI apps
Implement embeddings, vector databases, and retrieval logic using real datasets.
Design and evaluate RAG architectures with LangChain best practices.
Debug, optimize, and improve RAG accuracy using observability tools.
Build tool-using agents with structured outputs, memory, and multi-step reasoning.
Integrate agents with external APIs, databases, and task-specific workflows.
Test reliability, prevent hallucinations, and handle failure modes safely.
Use LangChain components to orchestrate prompts, tools, agents, and dataflows.
Build modular, maintainable pipelines using chain/agent abstractions.
Connect front-end, back-end, and LangChain logic into one deployable system.
Containerize applications, manage environments, and version code with Git.
Deploy to Vercel, Render, or cloud environments for real public demos.
Implement environment variables, secure API keys, and backend integrations.
Use LangFuse for tracing, logging, and evaluating model performance.
Measure latency, token usage, cost-per-request, and production metrics.
Optimize prompts, routing logic, and resource usage for real-world scale.
Scope, design, and build an AI system using your choice of RAG, agents, or tools.
Iterate with instructor feedback and peer reviews to improve quality.
Publish a polished demo + GitHub repo you can show to recruiters and employers.
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Who this course is for
Product Managers and aspiring AI engineers looking to break into applied GenAI roles.
Software engineers wanting to level up with LangChain, RAG, and agents
Career switchers looking to move into AI-focused engineering
Prerequisites
Basic Python/JavaScript familiarity
Some coding comfort makes it easier to follow exercises and customize your projects.
Enthusiasm for AI
A strong interest in exploring AI tools and turning ideas into real projects.
Curiosity to learn fast
The main thing you need — a willingness to experiment and build.
What's included
Live sessions
Learn directly from Aki Wijesundara, PhD & Manu Jayawardana in a real-time, interactive format.
Lifetime access
Revisit all lessons, recordings, templates, and code repositories whenever you need — your learning doesn’t expire.
Community of peers
Join a cohort of ambitious builders, stay accountable, and collaborate with engineers, PMs, and founders working on similar goals.
Certificate of completion
Show your new AI engineering skills to employers, add it to LinkedIn, and strengthen your 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
4 live sessions • 22 lessons
Week 1
Dec
5
Week 1 — Foundations & AI Mindset
Fri 12/54:30 PM—5:30 PM (UTC)
Foundations & AI Mindset
Week 2
Prompt to Prototype
Dec
12
Week 2 — Prompt to Prototype
Schedule
Live sessions
2 hrs / week
Join real-time, hands-on workshops where we build AI systems together. Each session walks you through implementing RAG pipelines, agents, tools, and deployment steps — with live debugging, engineering guidance, and direct feedback. You’ll walk away from every session with something working and pushed to your repo.
Fri, Dec 12
4:30 PM—5:30 PM (UTC)
Fri, Dec 5
4:30 PM—5:30 PM (UTC)
Fri, Dec 19
4:30 PM—5:30 PM (UTC)
Fri, Dec 26
4:30 PM—5:30 PM (UTC)
Projects
2 hrs / week
Apply each week’s concepts by building real AI components — RAG pipelines, agents, tools, and mini-systems. These projects help you practice engineering workflows, test ideas, and develop production-ready skills through hands-on implementation.
Async content
1 hr / week
Follow short, structured lessons that reinforce the week’s engineering topics — from LangChain patterns to deployment steps. Use this time to review code examples, improve your understanding, and prepare for live sessions.
Success stories
- The AI training approach is outstanding. Our team learned to build practical AI solutions that we could implement immediately in our educational platform. The hands-on methodology made complex AI concepts accessible to our entire development team.
Kavi T.
CEO of Tilli Kids / Stanford PhD - Not only are the instructors experts in their field, they're incredibly skilled at breaking down complicated AI concepts so students can grasp them quickly. Anyone interested in building foundational AI knowledge should take this training - it's worth the investment.
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Dr. Elizabeth Creighton
Founder & Principal at Brazen - The instructors help break down AI model development and clearly have plenty of experience to help others learn about complex concepts like infrastructure setup. The practical approach to NLP and LLM applications was exactly what our team needed.
Alissa Valentine
NLP & LLM Real World Data Scientist - I sent my team through this training for upskilling, and the results have been remarkable. Within weeks, they became much more efficient at building automations and deploying AI agents at work. This program bridges the gap between theory and practice and it’s had a real impact on our productivity.
Aamir Faaiz
CEO of Bayseian
Who You'll Be Learning From
Learn from Aki & Manu. Previous students are from top companies like Google, Meta & OpenAI.
Here’s what our cohort members are saying
Frequently asked questions
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$999
USD