LLMOps & AI Reliability

    Become the engineer who keeps AI systems reliable in production. Master the discipline behind "if you can't measure it, you can't ship it": observability and tracing, eval sets at scale, regression pipelines, drift detection, cost/latency dashboards, and eval-gated CI/CD. This is LLMOps — the modern operations layer for the LLM era — built entirely around the single biggest signal in AI hiring: eval literacy.

    Duration

    16 weeks (4 months)

    Level
    intermediate

    About This Course

    Most AI systems work in a demo and quietly break in production. LLMOps & AI Reliability is the specialization that prevents that. It teaches the operational discipline that production AI teams depend on — and that almost no course teaches at this level. You will master AI observability (tracing LLM and agent systems with OpenTelemetry, the 2026 standard), the modern tooling stack (LangSmith, Langfuse, Helicone, Braintrust, Promptfoo), and how to design evaluation sets at scale — both curated offline sets and online LLM-as-judge evals running on real production traces. You'll track the metrics that matter (task success, latency, cost-per-task), build regression pipelines that re-run on every change, and detect the drift that silently degrades AI systems over time. The centerpiece is the "ship gate": a versioned eval set, a numerical score, and a regression alarm — the discipline that separates teams who ship reliably from teams who "ship by vibe" and regress within sixty days. You'll build eval-gated CI/CD that blocks bad changes before they reach users, and learn incident response for when an AI system misbehaves in production. Through hands-on projects and a comprehensive capstone building a complete LLMOps pipeline around a real AI application, you'll graduate ready for LLMOps Engineer, Eval Engineer, and AI Reliability Engineer roles — premium specializations in high demand. Our Human Intelligence approach ensures you develop the judgment to decide what to measure and what "good enough to ship" really means.
    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 (13 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:

    LLMOps Engineer
    Eval Engineer
    AI Reliability Engineer
    AI Platform Engineer
    AI Infrastructure Engineer
    Production AI Engineer

    Target Salary Range:

    $120-180k(Global)

    Certificate of Completion

    Earn a blockchain-verified certificate upon successful completion.

    HI Focus: Skills AI Cannot Replace:

    Deciding what to measure — choosing the metrics that actually matter
    Defining "good enough to ship" — a judgment, not a number
    Diagnosing incidents — reasoning from traces to root cause
    Reliability culture — building a team habit of measurement
    Calibrating judgment — knowing when to trust an eval or a benchmark
    Operational maturity — anticipating how systems fail before they do

    "Anyone can ship an AI demo. Reliability engineers make sure it still works on day sixty."

    Skills You'll Gain

    AI observability and tracing (OpenTelemetry)
    The LLMOps tooling stack (LangSmith, Langfuse, Helicone, Promptfoo, Braintrust)
    Designing eval sets at scale (offline + online)
    LLM-as-judge design and calibration
    Metrics: task success, latency, cost-per-task
    Understanding and using benchmarks correctly
    Regression detection and the "ship gate"
    Drift detection and monitoring
    Eval-gated CI/CD for AI
    Incident response for AI systems
    Reliability SLOs and on-call practices
    Cost and latency operations

    Prerequisites

    AI Engineering (or equivalent production AI experience)
    Comfortable building RAG and agent systems
    Comfortable with Python and APIs
    Understands basic evaluation concepts
    15-20 hours per week availability

    Frequently Asked Questions