AI Lifecycle: The course begins with a refresher on core concepts in AI and more specifically Machine Learning (ML), as well as the ML development lifecycle. We will focus on the critical stages of data preprocessing, including cleaning, transforming, and formatting data, followed by an overview of model development—how AI models are designed, trained, and evaluated. 

ML Applications Walkthrough: We will guide participants through diverse practical Machine Learning applications, including: 

• Classification models, e.g. with Fraud Detection
• Regression Models, e.g. with Real Estate Price Prediction
• GenAI Large Language Models, e.g. talk-to-your-data application
• Clustering, e.g. with Customer Segmentation 

Hands On Experimentation: Working in groups or individually, participants will explore, modify, and customize pre-built AI models, with their own data or use cases. 

Reflection and Discussion: We will conclude by reflecting on the day's experimentation and outcomes, as well as addressing the limitations, risks, and challenges associated with AI development.

This course is aimed at professionals, employees and decision-makers, seeking to deepen their understanding of AI development through practical examples and hands-on experimentation. It is especially suited to those currently involved or potentially engaged in AI/ML projects, professionals working in data-driven sectors, or anyone curious about the 'behind the scene’ of AI development.

Pre-requisites:

• Participants are expected to have a basic understanding of AI/ML concepts, such as classification, regression, clustering, and machine learning, or basic familiarity with Large Language Models/Generative AI. Note this course is initially designed as a follow-up to our 2-day introductory AI course, which we recommend you take if you have not followed another prior course.
• No prior coding experience is required, as the code examples will be guided and commented on.
• No specific technical background is required yet a certain familiarity with reading 

Curves and graphs will be helpful, as the examples will involve some visualization to interpret the results. 

Disclaimer: This course is not designed to create fully developed solutions or deployment-ready prototypes in just one day. Instead, it offers a glimpse into AI model development through simple, practical and guided code exercises, helping participants gain a better understanding of the key concepts and processes involved.

Time and Location
See the dates for the next course in the information box at the top of the page. The course will be held at the IT University, Rued Langgardsvej 7.

Entry Requirements
The course has no specific prerequisites and is open to everyone.

Details
The course will be conducted in Danish. It does not confer ECTS points and is not linked to the IT University’s other programmes. There is no examination, but all participants will receive a course certificate upon completion. Participants must bring their own laptop. This laptop does not need to be particularly new, powerful, or of a specific type (Windows, Mac, and Linux are all acceptable).

Participant Fee
The course costs 6,100 DKK, including catering. The price is exclusive of VAT.

Limited Places
There are a limited number of places available on the course. Places will be allocated on a first-come, first-served basis.

Contact Course Director

If you have any questions regarding the course content, please feel free to contact the course director 

Claire Glanois

E: clgl@itu.dk

 
Contact ITU Professional Courses

If you have any practical questions regarding registration, course delivery, waiting lists, or similar matters, please contact us at:

itupc@itu.dk
 
For further contact options click here.