AI Engineering

    Become a production AI Engineer. Go beyond calling an API to building real, reliable LLM systems: production-grade RAG with hybrid search and reranking, agents with tool-use, MCP integration, proper eval pipelines, cost optimization, and FastAPI deployment. Build the exact 2026 stack employers screen for, with evaluation and cost modeling as first-class skills — the two things that separate engineers who've shipped from those who've only watched tutorials.

    Duration

    18 weeks (4.5 months)

    Level
    intermediate

    About This Course

    This is the core professional course of the NoobSync HI AI track. It turns someone who can already call an LLM API into an engineer who designs and ships production AI systems — the role companies are hiring for fastest in 2026. You will master the complete modern AI engineering stack: production RAG (chunking strategies, hybrid dense + keyword search, reranking), vector databases in depth, prompt engineering treated as versioned software, agents and tool-use with the ReAct pattern, MCP (Model Context Protocol) for connecting models to real systems, structured outputs, and proper deployment with FastAPI. Two themes run through every module because they are the highest-signal skills in AI hiring: evaluation (building real eval pipelines so you can prove your system works) and cost optimization (model routing, prompt caching, and budgeting so your systems are affordable at scale). Most courses treat these as afterthoughts. We treat them as core engineering. Through hands-on projects building production-grade components and a comprehensive capstone shipping a complete end-to-end GenAI application — ingestion, hybrid RAG, an agent with tools, a FastAPI service, evaluation, and cost tracking with a live demo — you will graduate ready for AI Engineer, LLM Engineer, and RAG Engineer roles. Our Human Intelligence approach ensures you develop the architectural judgment that distinguishes engineers from prompt-tinkerers.
    FOUNDING PRICE
    From ₹12,500/month

    Full payment or EMI options available

    *payment plans via checkout EMI or as offered during admissions.

    Regular ₹99,999

    Founding pricing — for our first 50 students across all programs.

    Early Bird Special — Limited time pricing

    No cash refunds — free course transfer available in special cases

    Course Curriculum (14 Weeks)

    Course Content & Projects

    Comprehensive Learning Experience

    After enrollment, you will receive detailed course materials, week-by-week curriculum, and capstone project specifications. All resources and project details are shared in your student dashboard.

    Full curriculum access • Live sessions • Project guidance • Mentor support

    Career Outcomes

    Potential Job Roles:

    AI Engineer
    LLM Engineer
    RAG Engineer
    GenAI Engineer
    GenAI Application Developer
    AI Product Engineer

    Target Salary Range:

    $90-150k(Global)

    Certificate of Completion

    Earn a blockchain-verified certificate upon successful completion.

    HI Focus: Skills AI Cannot Replace

    Architectural judgment — deciding how to design a system, not just code it
    Evaluation thinking — knowing how to prove a system actually works
    Cost discipline — building systems that are affordable at scale
    Tradeoff reasoning — balancing quality, latency, and cost
    Failure anticipation — designing for what goes wrong in production
    System-level thinking — seeing how retrieval, agents, and models fit together

    "Anyone can call an API. Engineers build systems that work, prove it, and pay for themselves"

    Skills You'll Gain

    Async Python for AI systems
    Multi-provider LLM API mastery
    Prompt engineering as versioned software
    Production RAG (chunking, hybrid search, reranking)
    Vector database design and selection
    Agents and tool-use (ReAct pattern)
    MCP (Model Context Protocol) integration
    Structured outputs and schema enforcement
    Building eval pipelines (offline + LLM-as-judge)
    Cost and latency optimization (model routing, caching)
    Guardrails and reliability
    FastAPI deployment for AI services

    Prerequisites

    Building with AI (or equivalent experience)
    Comfortable writing Python
    Comfortable calling LLM APIs
    Understands basic RAG and prompting concepts
    15-20 hours per week availability

    Frequently Asked Questions