About
AI Academy

AI Engineer Bootcamp

24 weeks — 12 weeks of coursework plus a 12-week industry project. From your first API call to a system in production, you build one delivery chain that can be observed, evaluated and iterated on.

Highlights

  • 12 weeks of structured teaching plus a 12-week real company project you can put on a résumé
  • Every module ends in something that runs AND something that measures it — not a demo that worked once
  • Taught by working North American AI engineers; résumé review, mock interviews, referral network

Curriculum

  1. 1 · LLM engineering foundations: transformer intuition, tokenizers and context budgets, structured output, function calling
  2. 2 · Prompting and evaluation: system prompts, few-shot and chain-of-thought, turning a hunch into a measured score
  3. 3 · Retrieval-augmented generation: chunking, embeddings, choosing a vector store, hybrid search and reranking, citations
  4. 4 · Agents and the tool loop: ReAct, tool calling, task decomposition, retries and multi-agent coordination
  5. 5 · Memory and context engineering: session vs long-term memory, context compression, token cost control
  6. 6 · Model choice and fine-tuning: deciding whether to fine-tune at all, then LoRA and instruction tuning
  7. 7 · Shipping: inference serving, streaming responses, auth and rate limits, multi-tenancy, staged rollout
  8. 8 · Observability and cost: logs, tracing, evaluation dashboards, cost per request
  9. 9 · Safety and boundaries: prompt-injection defence, data leakage, output review
  10. 10–12 · Industry project: real requirements, architecture review, iterative delivery, Demo Day
  11. Job sprint: rewriting your résumé around projects, AI system-design interviews, mock interviews and referrals

Core technologies

Languages & services

Python
TypeScript
FastAPI
Next.js

Models & SDKs

OpenAI API
Claude API
Hugging Face
开源模型部署

Agents & orchestration

LangChain
LangGraph
MCP
Function Calling

Retrieval & storage

pgvector
ChromaDB
PostgreSQL
Redis

Evaluation & observability

LangSmith
离线评测集
追踪与日志
成本看板

Deployment

Docker
vLLM
AWS Lambda
CI/CD

Who this is for

  • Engineers with 0–3 years of experience moving into AI engineering
  • Data or ML backgrounds missing the productionisation half
  • CS graduates and international students targeting North American AI roles