Management of AI Projects


This course presents a process for developing AI-based systems in a structured way. You will learn about the phases of AI projects that employ machine learning (ML). In particular, we discuss methods and techniques for AI engineering, i.e. implementing continuous training and continuous delivery of ML-based systems.
The lectures explain the life cycle of ML systems, including methods for ML model development, testing, deployment and monitoring. In-class computer demonstrations will provide practical examples of ML model training and deployment. The exercises do not require pre-existing knowledge of machine learning but assume that you have a technical and programming background.

The course will be delivered online using the Zoom platform.

Course dates 
Target group 

This two-day course is intended for software developers, engineers and project managers working in R&D from different application domains.

Total scope 
2 days
No. of seats 
Course language 
Course brochure 
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Entry requirements 

Basic knowledge in mathematics and programming. Experience in software development is an advantage.


Overview of AI and machine learning
Introduction to supervised learning, unsupervised learning and deep learning
Overview of machine learning system development process lifecycle
Modelling and optimization
Data management and continuous training
Continuous delivery of machine learning systems
Organisational aspects: Project planning, development teams and non-technical issues
Current trends and advanced topics in managing complex AI systems

Modelling, optimization and management of machine learning model experiments - Supervised learning using deep learning
Data management and continuous training
Data management processes and feature engineering
Continuous delivery - Testing, deployment and serving infrastructure
A real-life use case within text processing will be used to demonstrate an AI development project

After the course, you will have acquired state-of-the-art knowledge of ML development processes and how to apply machine learning to tackle problems in your own organization. They will also have an understanding of how to organize ML-based development projects.

Education partner 
Cancellation policy: 

Full refund of educational program/course fees will be made for reservations cancelled no later than eight weeks prior to the start of the program/course. Later cancellations incur a cancellation fee as follows:

  • 2 weeks or less prior to program start 100% of the educational program/course fee
  • 2-4 weeks prior to program start 50% of the educational program/course fee
  • 4-8 weeks prior to program start 25% of the educational program/course fee, for educations in the Shipping area: 0% of the educational program/course fee

We are always willing to consider a colleague as a substitute for the original applicant. Cancellation and postponement must be made in writing. Cancellation of accommodation is subject to the cancellation policies of the hotels.