Week 1
Week 1: Foundations of Working With Machines
Programming rigor, APIs, auth boundaries, networking, and debugging discipline.
A technical readiness brief and first backend boundary review.
Open weekPath
AI Engineer Intensive
An English-only, operator-grade eight-week bootcamp for self-learners who want to build, evaluate, deploy, and harden AI systems.
Let me teach you, human, how to work with me in a way that ships real systems, survives contact with production, and becomes portfolio proof.
Curriculum Arc
Eight weeks. No filler.
Week 2
Week 2: Data, ML, and How Models Learn
Data handling, feature thinking, evaluation, and classical ML before the LLM layer.
A simple ML pipeline with evaluation and a leakage audit.
Open weekWeek 3
Week 3: Talking to Models Properly
LLM foundations, structured outputs, prompt architecture, and secure API usage.
A prompt contract and structured-output integration design.
Open weekWeek 4
Week 4: RAG, Context, and Agentic Systems
RAG, retrieval quality, orchestration, and attack-aware agent design.
A retrieval architecture brief and an agent threat model.
Open weekWeek 5
Week 5: Shipping Systems, Not Demos
Containers, deployment, runtime isolation, and hardening the path to production.
A local stack blueprint and deployment hardening plan.
Open weekWeek 6
Week 6: MCP, Evaluation, and LLMOps
MCP, tracing, evals, cost, compliance-aware logging, and post-launch operations.
An evaluation scorecard and post-launch monitoring plan.
Open weekWeek 7
Week 7: Build the Product Core
Translate the curriculum into product loops: onboarding, progression, review, and admin visibility.
A product loop map, review system flow, and admin spec.
Open weekWeek 8
Week 8: Ship the AI Tutor
Polish the capstone, prove launch readiness, and turn the system into a portfolio narrative.
A case study, launch checklist, and personal AI Engineer operating manual.
Open week