Machine Learning System Design

13 June, 2024Amsterdam, The Netherlands

2 days
In Person
Machine Learning

Are you a machine learning practitioner who struggles with designing, reasoning, and communicating about larger ML systems? Then this training is for you! Get ready to develop your skills and knowledge in this exciting field! Be sure to bring your own business case to get the most out of the training.

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Looking to upskill your team(s) or organization?

Nico will gladly help you further with custom training solutions for your organization.

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2 days


09:00 – 17:00









What will you learn?

With the industry moving towards end-to-end ML teams to enable them to implement MLOPs practices, it is paramount for you to understand ML from a systems perspective.

In this course, you will gain a thorough understanding of the technical intricacies of designing valuable, reliable and scalable ML systems. The session enables you to identify trade-offs and bottlenecks in a system. Plus, you’ll learn how to effectively communicate and collaborate with other people and departments. The training will contain a mix of theory and practice. As we will share common methodologies and frameworks and apply them straight away to a real business case.

After the training, you will be able to:

Assess the requirements for ML systems by applying the ‘Reliable, Scalable, Maintainable, and Adaptable’ framework

Communicate designs clearly and make the proposed solution measurably work by writing proposals following the Software Design Doc template

Illustrate your designs and provide context by creating hierarchical architecture diagrams

Evaluate technical bottlenecks and trade-offs in design proposals


  • Introduction to system design and why it’s important 
  • ML System Design as part of the ML model life cycle 
  • Requirements engineering 
  • Walkthrough Step-by-step ML System Design framework 
  • Design real-world ML use case 

This training is for you if:

You want to improve your understanding of what makes a scalable machine learning application

You want to be better at identifying trade-offs when making design decisions for your machine learning application

You want to make more conscious decisions when working on machine learning applications

You want to improve your ability to communicate your design decisions

This training is not for you if:

You only want to write code. In that case, the MLOps training provides hands-on coding for the implementation of ML infrastructure

You don’t have experience with running a machine learning model in production. In that case, the Production Ready Machine Learning might be a better fit for you

You think building an ML model is your sole responsibility and do not care to communicate your design, not even to your stakeholders

Why should I
follow this training?

Learn from the best

During this training industry experts will deliver conceptual explanations of how to design ML systems and walk you through practical exercises in a very interactive setting

Comprehensive learning experience – learn today apply tomorrow!

You will expend two days thinking about what is important to consider when designing a ML system, what are common solutions to common problems, best practices, design patterns and anti-patterns

Interactive and personalized

Bring your own use case to the training and receive tailored feedback that focuses on your specific requirements

What else
should I know?

After registering for this training, you will receive a confirmation email with practical information. A week before the training, we will ask you about any dietary requirements and share literature if you need to prepare.

See you soon!

Course information

All literature and course materials are included in the price.

After registering for this course, you will receive a confirmation email with practical information.

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