Trustworthy AI Products


(8 ratings)


3 Days


Cohort-based Course

From product strategy & design to data ethics & security, you will learn best practices for building reliable and responsible AI products.

Course overview

From idea to launch: Learn how to master the complexities that come with AI.

Trustworthy and responsible AI systems are reliable, safe, and secure - and they work for everyone.

Because it's complex to make all of this work well, trustworthy AI is often just seen as a cost factor without much immediate ROI ('we are no charity, we run a business'). But your product will only be successful in the long term if you focus on nailing user trust, legal and regulatory compliance, and your business reputation.

I learned to manage machine learning products the hard way and failed many times - you don't have to. I will provide you with the knowledge and skills you need to stand out in the market and give you and your business a competitive advantage.

Scroll down for the learning outcomes and more detailed curriculum.

Designed for product thinkers. From founders to experienced PMs and engineers who ...


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


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


This course is *NOT* optimized for anyone interested in robotics.

What will this course enable you to do?

Video + Live Classes

I use a mix of videos to pre-watch and live classes.

  • the videos are for foundational content (ML 101, Development flow,...) - you can skip these if you have done Marilys course or 'AI for everyone' from Andrew Ng.
  • the live classes focus deeply on Trustworthy & Responsible AI
Designing Machine Learning (ML) Products

  • Understand key ML concepts and speak the same language as your engineers.
  • Build your ML business case. Is ML the right solution?
  • Frame the user problem and define the right success metrics. Even the best ML model will fail if this is not done well.
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.
Data Privacy, User Trust & Ethics

  • Apply a human-centered design approach to reinforce user trust.
  • Best practices for collecting, managing, using data in a responsible way.
  • Sources of bias in AI models.
  • Understand the role of company culture to deal with new complexities for inclusive AI products.
AI Governance
  • Understand the technical and legal aspects of ensuring the safety and security of AI systems.
  • Processes, policies, and frameworks to use for governance.
  • Identify and assess risks specific to ML products.

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!

Schedule - Crash Course

8 hours - 1 week - small cohorts
  • Tue, Wed, Thurs - March 14,15,16

    18:00-19:30 CET (or 9-10:30 am PT)

    • 3 days, 1.5h live lecture per day. I will stay online for another 30min for Q&A.
    • I use a mix of live presentation and hands-on workshop style with team activities.
    • I usually share a pre-read or pre-watch for each session to make sure participants are at the same level.
  • Video content (approx. 4h)

    at your own schedule

    I pre-recorded sessions to consume at your own time. This includes:

    • foundational content (i.e. Machine Learning or Product Management) so we can focus discuss the essentials of Trustworthy AI in live classes.
    • conversations with guest speakers (i.e. data scientists, ...)
  • Q&A

    I do offer dedicated time for Q&A, both right after our live sessions and one more separate session.

    That said, I am more than happy to hop on a short 1:1 call anytime during or shortly after the course to make sure all your questions are answered.

Course Syllabus


Machine Learning 101 (Video)

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.


ML or not ML? (Video)

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.


Problem Framing (Live)

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!


Product Development with ML (Video)

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.


Fail Better (Live)

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 :)


Stakeholder Management & Cultural Transformation (Live)

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.


Risk Assessment (Live)

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.


User Trust and Ethics (Live)

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.

We will discuss relevant examples and best practices.


AI Governance (Live)

Learn about processes, policies, and frameworks that organizations use to oversee and manage the development, deployment, and use of AI systems.


Security & Safety (Live)

Learn about malicious attacks, how to ensure data privacy and security, and practices towards AI systems that are robust and reliable.


Explainable AI (Video, Guest speaker)

Recent advances in making sure AI systems are transparent and interpretable, allowing stakeholders to understand how and why the system is making decisions.

What others say about me

        As PM I wanted to understand better how ML works in general and how to identify problems that are well suited to be solved with this tech. Not only did Karins well structured course deliver on that. I also got deep insights into how bring an ML product from Inception to production and huge collection of relevant high quality content that I can use.
D.S. (Course Participant)

D.S. (Course Participant)

Cohort Dec 2022
        Great introductory course for Product Managers / Technical Program Managers to understand the basics of ML products - how to plan them, how to build (and what *not* to build), the implications they may have on the organisation and society. The recommended readings were great, and the special guests throughout the course were also very insightful.
M.M. (Course Participant)

M.M. (Course Participant)

Cohort Dec 2022
        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
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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?

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.


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

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