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AI & ML

Machine learning, LLMs, and AI engineering in production. Discover the real-world tools powering today's AI products and how to enter this fast-growing space as an OPT student.

Machine LearningLLMsAI EngineeringMLOps

Duration

4 months

Starts

July 2026

Format

Live · Cohort

Tuition

$1,999

16-Week Curriculum

Week by week, from fundamentals to a job-ready profile — every module ships a hands-on deliverable.

  1. 1

    Python for AI Engineering

    Python refresh, notebooks, APIs, environments, package management

    Build: AI utility scripts

    Python confidence

  2. 2

    NLP + Transformers Foundations

    Tokenization, embeddings intuition, attention, transformers overview

    Build: Text preprocessing notebook

    LLM intuition

  3. 3

    Prompt Engineering

    Zero-shot, few-shot, chain-of-thought, structured outputs, prompt templates

    Build: Prompt cookbook

    Prompt engineering confidence

  4. 4

    LLM APIs

    OpenAI/Gemini/Anthropic style APIs, SDKs, rate limits, retries, safety basics

    Build: Multi-model prompt app

    API integration readiness

  5. 5

    Embeddings + Vector Databases

    Embeddings, similarity search, chunking, metadata, indexing

    Build: Semantic search app

    Retrieval fundamentals

  6. 6

    RAG Foundations

    Ingestion pipelines, retrieval strategies, context optimization, citations

    Build: Document Q&A chatbot

    Enterprise GenAI basics

  7. 7

    Advanced RAG

    Hybrid search, reranking, parent-child chunks, query rewriting, evaluation

    Build: Enterprise knowledge bot

    Production RAG readiness

  8. 8

    LangChain / Orchestration

    Chains, tools, memory, prompt templates, output parsers

    Build: Workflow-based AI assistant

    Framework readiness

  9. 9

    AI Agents

    Tool calling, planning, agent loops, browser/file/database tools

    Build: Task automation agent

    Agentic AI fundamentals

  10. 10

    Multimodal AI

    Text + image understanding, OCR pipelines, vision-language use cases

    Build: Document/image assistant

    Multimodal project readiness

  11. 11

    Multi-Agent Systems

    Supervisor agents, role-based agents, workflow graphs

    Build: Research assistant system

    Multi-agent architecture

  12. 12

    Fine-Tuning + PEFT Basics

    Supervised fine-tuning intuition, LoRA, adapters, dataset prep

    Build: Domain adaptation mini project

    Model customization skills

  13. 13

    Evaluation + Guardrails

    Hallucination detection, evaluation metrics, red teaming, guardrails, prompt injection defense

    Build: Evaluation suite

    Evaluation + safety skills

  14. 14

    Deployment + LLMOps

    FastAPI, Docker, model serving, caching, observability, prompt versioning

    Build: Deployed RAG API

    Production deployment skills

  15. 15

    Cloud + Scalable GenAI

    AWS/Azure/GCP deployment options, vector DB hosting, queues, async workloads

    Build: Cloud-hosted GenAI app

    Cloud AI engineering

  16. 16

    Capstone + Placement Preparation

    End-to-end GenAI product, GitHub portfolio, resume, system design, mock interviews

    Build: Final capstone + portfolio

    GenAI job-ready

Apply for this cohort

25 of 70 seats left · July 2026 – Nov 2026