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LLM ops, evaluation & research curriculum▌

For ML platform and research adjacent teams—expects quantitative literacy.

Discuss this track →Browse program pages

About the Instructor

Yash Thakker

AI Instructor & Product Leader

Yash Thakker has 12+ years of experience building AI products and has taught 160,000+ students across 50+ courses. He facilitates corporate AI training for enterprises including Tata, PayPal, and Fortune 500 teams. Yash holds an MBA from SIMSREE and a B.Tech in Information Technology. Based in Mumbai, he delivers programs globally, specializing in Claude AI, generative AI, and practical AI implementation for regulated industries.

Credentials

  • MBA, SIMSREE (Sydenham Institute of Management Studies)
  • B.Tech, Information Technology, University of Mumbai
  • 12+ years building AI products
  • 160,000+ students trained across 50+ courses
LinkedIn →Contact →

program objectives

  • Build eval suites spanning offline, online, and human preference layers.
  • Discuss fine-tuning vs. RAG vs. prompt-only with total-cost framing.

how we deliver

  1. 1

    Discovery call & problem framing

    We align on sponsors, success metrics, and constraints (2026 tool landscape, data rules, procurement gates) before anything is scheduled company-wide.

  2. 2

    Stakeholder interviews & day-in-the-life context

    Short conversations with practitioners (not only leadership) so scenarios reflect real workflows—not generic slide demos.

  3. 3

    Curriculum design & artifacts

    Modular agenda, exercise scripts, evaluation rubrics, and governance checkpoints matched to your vocabulary (banking, FMCG, engineering, etc.).

  4. 4

    Engaged, hands-on delivery

    Facilitation-led sessions with live exercises, breakout prompts, and documented failure modes—minimum passive lecture time.

  5. 5

    Post-session support: documentation & next steps

    Written recap, pilot backlog, links to explainx.ai courses for scaled upskilling, and optional office hours so momentum doesn’t stop at the workshop.

modules

Evaluation architecture

Beyond leaderboard chasing.

session outline

  • Task suites
  • Judge models
  • Human calibration

labs

  • Design minimal harness

beyond-catalog topics (custom)

  • Synthetic data pitfalls in highly regulated verticals

quick contact

Scope or pilot this curriculum

Share sponsor, headcount, and cities — we reply with timing and options. Rough budget helps us match the right depth.

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faq

GPU budget discussions?

We can integrate CapEx/OpEx framing with your FinOps partners when invited.

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