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Data Operations for AI Products Certification

Jeanne Williams

ex-Head of tPgM/Ops @ Google & ex-Apple

Become the Data Operations leader AI product teams need to ship with confidence

This is the first certification designed specifically for AI Product Teams focused on Data operations, AI operations, and cross-functional execution — built from 20+ years of real experience running AI/ML programs, data pipelines, infra, privacy, and readiness operations at global scale (Google, Apple).

You’ll leave with a repeatable system, templates, and a DataOps operating model.

ʏᴏᴜ ᴡɪʟʟ ʟᴇᴀʀɴ ʜᴏᴡ ᴛᴏ:

  • Build DataOps workflows (intake → validation → delivery) that scale

  • Audit data quality across the 6 core dimensions (freshness, coverage, etc.)

  • Translate governance (GDPR/AI Act/CCPA) into real operational processes

  • Decide when to automate vs use human-in-the-loop for quality & compliance

  • Build observability + measurement loops (golden sets, logs, dashboards)

  • Define OKRs and operating models for DataOps as a function


ʏᴏᴜ’ʟʟ ʙᴜɪʟᴅ ᴀ ʀᴇᴘᴇᴀᴛᴀʙʟᴇ ᴏᴘᴇʀᴀᴛɪɴɢ ᴍᴏᴅᴇʟ

That you can apply at work immediately with our capstone project:

  • Data intake + requirements

  • Governance constraints + access model

  • Pipeline strategy (ETL/ELT)

  • Readiness + quality checks

  • Human-in-the-loop plan

  • Metrics + monitoring plan

What you’ll learn

Master the Data Ops systems behind successful AI products, lead execution, reduce risk, and earn trust across Eng, Research, and leadership

  • Understand how modern AI pipelines work and where failures occur.

  • Learn the frameworks to diagnose root-cause data issues with confidence.

  • Become the manager who brings clarity and structure to complex, ambiguous AI programs.

  • Run intake, validation, and alignment workflows that surface blockers early.

  • Communicate data requirements with precision and authority.

  • Position yourself as the central orchestrator ensuring teams move together—not in silos.

  • Define success using product, data delivery, and operational metrics.

  • Implement observability, golden test sets, structured logging, and validation loops.

  • Communicate impact to leadership with metrics that influence strategy.

  • Evaluate data across relevance, accuracy, coverage, completeness, consistency, and freshness.

  • Apply operational checks used in top AI teams to validate datasets.

  • Build trust with engineering by identifying risks early and preventing costly failures.

  • Translate GDPR, AI Act, CCPA and organizational philosophies into actionable processes.

  • Define data policies, access models, and trust frameworks that teams can rely on.

  • Become a strategic partner to Legal, Privacy, and Policy through strong DataOps leadership.

Learn directly from Jeanne

Jeanne Williams

Jeanne Williams

Contact

ex-Head of tPgM/Ops @ Google & ex-Chief of Staff @ Apple

Apple
Google

Who this course is for

  • Tech Team Leaders who must guide AI-driven teams and need DataOps expertise to improve delivery, quality, and cross-functional execution.

  • Tech PgMs who want to deepen their AI, data, and governance expertise to advance into senior, high-impact roles.

  • Cross-functional tech professionals who partner with AI teams and need DataOps skills to execute and scale AI initiatives.

What's included

Jeanne Williams

Live sessions

Learn directly from Jeanne Williams in a real-time, interactive format.

Interactive Exercises

During our live sessions, you will get paired up with other students to solve a problem

Maven Guarantee

This course is backed by the Maven Guarantee. Students are eligible for a full refund up until the halfway point of the course.

Course syllabus

4 live sessions • 5 lessons

Week 1

Feb 23—Mar 1

    Week 1 — Foundation + Strategy

    2 items

    Feb

    25

    [Data Operations for AI Products] Session 1: The DataOps reality behind successful AI Products

    Wed 2/255:00 PM—6:30 PM (UTC)

    Feb

    27

    [Data Operations for AI Products] Session 2: Governance + Data Strategy for AI Products

    Fri 2/275:00 PM—6:30 PM (UTC)

Week 2

Mar 2—Mar 6

    Mar

    2

    [Data Operations for AI Products] Session 3: Data readiness & quality operations

    Mon 3/25:00 PM—6:30 PM (UTC)

    Mar

    6

    [Data Operations for AI Products] Session 4: Measurement, metrics, and building a Data Operations org

    Fri 3/65:00 PM—6:30 PM (UTC)

    Week 2 — Readiness + Execution

    2 items

    Your Data Operations Blueprint for an AI Product

    1 item

Schedule

Live sessions

3-5 hrs

    • Wed, Feb 25

      5:00 PM—6:30 PM (UTC)

    • Fri, Feb 27

      5:00 PM—6:30 PM (UTC)

    • Mon, Mar 2

      5:00 PM—6:30 PM (UTC)

    • Fri, Mar 6

      5:00 PM—6:30 PM (UTC)

Projects

4 hrs

Async content

2 hrs

$999

USD

Feb 23—Mar 6
Enroll