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Building trusted machine learning products

8.3

(4 ratings)

·

2 Weeks

·

Cohort-based Course

Address the unique complexities and risks of machine learning (ML) with product management best practices from industry leaders like Google.

Hosted by

Karin Schöfegger

A scientist turned product coach & trainer with 15+ years at Google, N26, IBM.

Last chance to enroll

3

days

7

hours

12

mins

Course overview

This is the course I wish existed when I started as an ML Product Manager.

I learned ML product management the hard way - you don't have to. Solve user problems with a deeper understanding of ML systems. Apply an effective & thoroughly probed development process & best practices. Use human-centered design & risk assessment for user & stakeholder trust.

Building better ML products. This course is for software product managers, who ...

01

... want to introduce ML to solve specific user or business problems but are unsure how to get started.

02

... are already using ML, want to become more efficient and manage their risks more proactively.

03

This course is *NOT* optimized for hardware products (i.e. robots).

What will this course enable you to do?

Machine Learning (ML) Foundation for your Product


  • Speak the same language as your engineers and know what they are talking about.
  • Frame the user problem and define the right success metrics. Even the best ML model will fail if this is not done well.
  • Help your team decide how  ML can and cannot help solve your user problem.
Product Development Workflow & Stakeholder Management
  • Lead your team through each step of the development lifecycle for ML products.
  • Cooperate with various roles at the right time in the development lifecycle. Many roles add value, not just engineers.
  • Manage your stakeholders more effectively given the different nature of ML.
Risk Management, User Trust, Ethics and Culture
  • Understand key elements of a great company culture to deal with new complexities to build inclusive products.
  • Identify risks specific to ML products. Apply selected best practices to address & mitigate those.
  • Apply a human-centered design approach to reinforce user trust.

Nice to meet you!

Karin Schöfegger

Karin Schöfegger

Product Coach & Consultant, Ex-Google, Ex-N26.

I’m one of the leading ML-product experts in Europe with 15+ years of professional experience:

  • Most recently I worked at Google Assistant and Google Research on various ML-based products.
  • I launched an ML infrastructure for YouTube to train, launch and operate our video-based algorithms and spearheaded the introduction of ML governance tools
  • Led 'Smart Banking' for unicorn bank N26
  • Consulted mainly data-driven businesses at IBM
  • Built recommender systems as a research scientist (yes, I once knew how to code :))
  • I studied theoretical Mathematics with a focus on Artificial Intelligence and Information Processing


Machine Learning is complex, but it is not magic. Everyone can learn the fundamentals to help build better ML products for the benefit of our society. Driven by this belief, l regularly give talks, workshops, and courses (mainly internally at Google, but also at public conferences incl. GraceHopper) to lift the perceived veil of secrecy around machine learning.


As a product coach & consultant, I work for startups and companies mainly in Europe.


Interested in learning more about me? Head over to my website!


Do you have any questions to make sure this course is the right one for you?

You can book a free coffee chat using with me! I would be more than happy to clarify your questions to make sure your money is worth the investment!

I also run very small cohorts (max 15 people), there is also some room to adapt the content to the needs of the participants!

8.3

(4 ratings)

What others say about me

        Karin did an outstanding job in creating, managing and delivering courses and talks for our Product Manager community. I can highly recommend Karin as an amazing AI speaker and trainer.
Anders Sandholm

Anders Sandholm

Google Product Manager AI/NLP | Board Member | Ex-McKinsey
        Karin is a thought leader in the ML space, with experience at tech giants and startups alike. When combined with her years of experience as a PM, the result is a methodological and practical approach to building responsible AI that can change the world. I would highly recommend Karin's courses to anyone looking to understand the PM role with AI/ML.
Maritza Bonano

Maritza Bonano

Global Program Manager at Meta
        Karin excels at explaining the complexities of AI to various audiences, from beginners to highly technical folks. She is passionate about principled AI development and cares deeply about educating others on the topic in order to bring the greatest benefit to society.
Grace Kwak Danciu

Grace Kwak Danciu

Group Product Manager Google
        Karin enabled me to understand the bigger picture of ML product development, become aware of important pillars of our startup setup and to design a cohesive strategy for our seed phase. All this with a sharp mind, open heart, and sincere support - I highly recommend working with her!
John Lack

John Lack

Founder Resolvi App, Mindful Leadership trainer, Coach
        When it comes to building ML products, Karin is an amazing resource. I had the pleasure of being Karin’s manager at Google Research, working together to develop innovative products that pushed the boundaries of ML. Karin’s deep experience across multiple industries and products gives her a unique perspective in the space.
Rob Wong

Rob Wong

Director of Product at Google

Course Syllabus

01

Machine Learning 101 (optional)

We will dive into what is ML, AI, and key concepts as well as common use cases.

This will foster a common understanding on the vast variety of interpretations as to what AI and all sub-categories entail. It also ensures a relatively similar knowledge level across all participants of the course.

02

ML or not ML?

ML is hip. But not every problem is best solved with ML. We will discuss examples of where it works and where it doesn’t with real life case studies from my consulting experience.

03

Problem Framing

We will practice framing user problems and defining key metrics to align your team and measure success. We will discuss a few examples, so make sure to  bring your own!

04

Product Development with ML

We will go through and discuss all the steps in the iterative process, essential tasks to get done at every step of the process, and learn tools on how to best identify where the key risks lie. Additionally, we will explore which agile methodologies are suitable to use with your engineering teams.

05

Fail Better

No course in the world can keep you from constantly learning. ML models will fail in ever new ways. We will explore how to identify potential errors early, how to prepare for them, and discuss real failure cases. This is also a good brief for your PR department :)

06

Stakeholder Management & Cultural Transformation

We will discuss the roles you will likely work with, and how to best collaborate with every single one of them. You will also learn key cultural standards that are necessary to working with ML. And if they aren’t in place yet, we will explore ways how you can get the ball rolling on this culture change.

07

Risk Assessment

You will be able to apply a proven risk assessment guide to prevent, to the extent it is feasible, the most common causes of (human) error.

08

User Trust and Ethics

AI systems have a huge impact on their users and our society as a whole. Developing them comes with a special responsibility for the future.

I will close the course with a discussion of relevant examples and share more resources to explore on your own.

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Join an upcoming cohort

Building trusted machine learning products

2022-Dec

$640 USD

Dates

Dec 1 - 13, 2022

Payment Deadline

Nov 30, 2022

Don't miss out! Enrollment closes in 4 days

Course schedule

8h hours - 2 weeks - small cohorts
  • Tuesdays & Thursdays

    16:00 - 17:30 CET (10:00 - 11:30 ET)

    November cohort: Nov 8th, 10th, 15th, 17th

    December cohort: Dec 1st, 6th, 8th, 13th


    • I use a mix of live presentation and hands-on workshop style with team activities.
    • I reserve +30min per session to allow for overflow time in case of questions
    • Small cohorts - 15 people max.
  • Bonus: Nov 11th - Dec 13th

    Optional Product Coaching 1:1 (55min)

    Each course participant can get access to a personal Product Coaching session for any questions you may want to bring to me (European time!). The topics can be course related, or from your product management day to day job.

    Upon signup for the course, I will share my calendly.

Learning is better with small cohorts

Learning is better with small cohorts

Learn with a small cohort of peers

I will have small cohorts of max. 15 people to foster an environment in which you can learn effectively from me, feel more safe asking lots of questions and share your experiences and thoughts. I will also share real examples from my career.

Active hands-on learning

This course builds on live workshops and hands-on projects.

Interactive

You’ll be interacting with other learners through breakout rooms and group discussions.

Stay in the loop for upcoming cohorts

Sign up to be the first to know about course updates.

Frequently Asked Questions

I have a few questions prior to signing up. Can I get in touch with you?
What happens if I can’t make a live session?
I work full-time, what is the expected time commitment?
What’s the refund policy?
Do you offer discounts?
Can I do the 1:1 coaching also after Dec 11th?
I don't need the 1:1 coaching, can I have a discount?
What happens if the dates or times dont work for me?
A pattern of wavy dots
Join an upcoming cohort

Building trusted machine learning products

2022-Dec

$640 USD

Dates

Dec 1 - 13, 2022

Payment Deadline

Nov 30, 2022

Don't miss out! Enrollment closes in 4 days

$640 USD

8.3

(4)

·

2 Weeks