AI Engineering Bootcamp and Certificate

Plan for about five hours a week: one two-hour Friday build session, project work on your capstone, optional office hours, and short async lessons. The two-week build sprint after teaching ends is yours to finish and ship. Everything is recorded if you fall behind.

No, and you do not need to be a strong coder. We build with coding agents, so you skill up as you go, and Python fundamentals are included as prework. You need some comfort with basic logic and a willingness to build. No AI, machine learning, or research background required.

No. You build the agent loop by hand from the raw API first, so you understand what is actually happening, then use LangGraph as the framework that formalizes it. The goal is fundamentals that outlast any one tool, not memorizing a framework that may be gone next year.

A portfolio of deployed systems: a live LLM service, a RAG pipeline you measured and improved, a multi-agent system, an evaluated build with traces, and an agent with memory. It all ladders into one capstone you ship and demo, with a GitHub repo you can show employers.

You pick a problem in pre-course, then build it across the four weeks: an API in week one, retrieval in week two, an agent in week three, evals and memory in week four. Each weekly assignment is the next piece, and a two-week sprint lets you finish, ending in a live Demo Day.

Taught around TRACE, the error-analysis method teams at the major labs use. Engineers go deep into the tooling, code assertions, validated LLM-as-judge, CI gating, and observability, and learn the discipline that separates serious builders from people guessing.

Every student gets lifetime access to Akis 10-part Think Like an AI Engineer mini course, free. It is the fastest way to lock in the mental models, how LLMs work, prompting, model selection, context, and evals, before the bootcamp goes deep on building. Watch it before week one to hit the ground running.

Every session and office hour is recorded and shared within twenty-four hours, and you get lifetime access to all materials. The community stays active for async support, and you can defer to a future cohort at no extra cost. Live attendance helps, but it is not required to finish.

Take the Builders Bootcamp if you want to ship products with no-code tools. Take this if you want to build real AI systems and agents and understand them under the hood. You write code here, with coding agents helping you skill up, so no prior fluency is required. Many people do Builders first, then come here.

It is built for it. The depth goes straight at what interviewers probe: why retrieval fails, when an agent is wrong, how you prove a system works. You leave with shipped systems to talk about, not just a certificate. One student passed an AI Forward Deployed Engineer interview on the strength of what they built here.

Yes, you earn the Agentic AI Engineering certificate to add to LinkedIn and share with employers. More importantly, you leave with a portfolio of deployed projects and the understanding to defend every decision in them, which is what actually moves an interview.

You will use the OpenAI API, a vector database, LangGraph, and a coding agent (we use Claude Code and Cursor). The pre-check session before week one gets your environment, keys, and accounts working so no live time is lost to setup. Most tools have free or low-cost tiers for the course.

We go deep on the fundamentals instead of touring forty tools. Four focused weeks where you understand each layer rather than skim it, because depth is what survives the next model and what gets you through an interview. Advanced topics are included as marked, self-paced Deep Dives so live time stays focused.

Your purchase is backed by the Maven Guarantee, Mavens satisfaction guarantee, so you are covered early on if the course is not the right fit. If you ever need to step away, you can also defer and rejoin a future cohort at no additional cost.