Class is in session

Develop judgement in building real-world AI products

5.0 (5)

·

3 Weeks

·

Cohort-based Course

Build the necessary technical depth to make trade-offs and exercise judgement during the lifecycle of an AI driven product

Previously at

Google
Etsy
Product School
Stanford University

Course overview

What Shipra will teach in 3 weeks

ABOUT THE INSTRUCTOR


With over 10+ years of experience launching AI products at Google, a strong technical acumen and unique teaching ability; Shipra Malhotra is now offering this course to help you level up your skills in building and launching successful AI driven products.


ABOUT THE COURSE


This course is designed to give you --

1) Foundational technical knowledge of key concepts

2) Planning the right dataset and roadmap

3) Methods of evaluation for testing, diagnosis and ongoing monitoring of AI powered products

4) Frameworks for making key decisions during the development life-cycle of AI powered products

5) Ways to keep abreast in this ever-changing field


This course will be heavy in the usage of examples (specially from Search and Recommender systems) for the purposes of demonstrating key principles.


Guest talks on --

1) Upcoming AI startups and evaluating their potential

2) Case study on innovative data techniques in building AI powered products

3) How traditional AI problems of trust, safety and privacy apply to GenAI applications

4) Non-conventional applications of LLMs in BioTech and Climate

Who is this course for

01

Current Product Managers pivoting to building AI powered products

02

Mid-career and Lead AI Product Managers looking to refine their decision-making skills

03

Senior Engineers pivoting from traditional software development to AI powered products

What you’ll get out of this course

Fundamentals of AI Development - A History

How has AI developed over the years?

What were the key breakthroughts and what did they enable?

What can we expect in the future?

Preparing to use AI in your Product

When should you do it? And when should you not?

How do you prepare the right dataset? (Even when it's non obvious)

What requirements must be set in advance to form a complete picture?

How do you plan the right set of milestones or experiments?

Making Trade-offs in Architecture Design

How do you balance cost of development and maintenance with accuracy and latency?

Does the time-to-market justify the above?

What are the key paradigms for a safe user experience in AI products?

Evaluating an AI Product

How do I diagnose deficiencies in my product?

How do I make launch decisions?

How do I explain why my product is behaving a certain way?

How do I monitor my product on an ongoing basis and avoid PR fiascos?

Keeping Abreast

Reading materials and selected sources for staying up-to-date

Guest Lectures

Veterans from the industry speaking about their experience with AI and their ground-up experience

This course includes

5 interactive live sessions

Lifetime access to course materials

4 in-depth lessons

Direct access to instructor

1 projects to apply learning

Guided feedback & reflection

Private community of peers

Course certificate upon completion

Maven Satisfaction Guarantee

This course is backed by Maven’s guarantee. You can receive a full refund within 14 days after the course ends, provided you meet the completion criteria in our refund policy.

Course syllabus

Week 1

Nov 23—Nov 24

    Nov

    23

    History of AI Development - Key Breakthroughs

    Sat 11/236:00 PM—7:30 PM (UTC)

    Nov

    23

    Preparing for an AI Powered Product or Feature

    Sat 11/239:00 PM—10:30 PM (UTC)

Week 2

Nov 25—Dec 1

    Nov

    30

    Evaluating, Monitoring and Explaining your AI Product

    Sat 11/306:00 PM—7:30 PM (UTC)

    Nov

    30

    Key Decisions in the Product Lifecycle

    Sat 11/309:00 PM—10:00 PM (UTC)

Week 3

Dec 2—Dec 8

    Dec

    7

    Keeping Abreast

    Sat 12/76:00 PM—6:45 PM (UTC)

Post-course

    Key Decision Making during the Lifecycle of Development

    1 item

Bonus

    Guest Talk : Upcoming AI startups and their Market Potential

    1 item

    Guest Talk : Novel techniques for Data-Collection and Evaluation

    1 item

    Guest Talk : Non traditional AI applications and Parallel Opportunities

    1 item

    Guest Talk: Scope of Trust, Safety and Privacy issues in GenAI Applications

    1 item

5.0 (5 ratings)

What students are saying

Meet your instructor

Shipra Malhotra

Shipra Malhotra

Search ML Lead @Etsy, ex Google, Product School Speaker, Mentor and Coach

Shipra Malhotra is a veteran at building AI powered products with 10+ years of experience.


She is teaching this course with collated knowledge and best practices from her experience, network and all the nuggets on the internet.

A pattern of wavy dots

Be the first to know about upcoming cohorts

Develop judgement in building real-world AI products

Course schedule

4-5 hours per week

  • Saturdays

    We will take Saturday day-time PST for live sessions and project discussions.


    All live lectures will allow for QnA.

Learning is better with cohorts

Learning is better with cohorts

Active hands-on learning

This course builds on live workshops and hands-on projects

Interactive and project-based

You’ll be interacting with other learners through breakout rooms and project teams

Learn with a cohort of peers

Join a community of like-minded people who want to learn and grow alongside you

Frequently Asked Questions

A pattern of wavy dots

Be the first to know about upcoming cohorts

Develop judgement in building real-world AI products