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  1. Technik & Architektur Technik & Architektur
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  5. Microcredentials Microcredentials

Deep Tech Microcredentials Short courses on the Application of Artificial Intelligence

If you are looking for a brief and practical introduction to AI applications in Medical Science and Engineering, Data Science and Engineering, and Material Science and Engineering, these fully online, self-paced courses are perfect for you. The courses are funded by the EIT Deep Tech Talent initiative of the European Institute of Innovation and Technology (EIT) and are available as part of a pilot project.

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General Course Information

Start Date

Anytime (rolling admission)

Workload

20-50 hours (depending on prior knowledge)

Format

Fully online, self-paced and asynchronous

Learning format

Video lectures, practical hands-on experiments, final multiple-choice exam

Cost

Free of charge

Certificate

Certificate of completion upon passing the exam (quality-checked by EIT)

Language

English

Note: 

Developed within the research project "AI for ALL" and originally for students of the Warsaw School of Computer Science. Now also accessible to other learners, but without ECTS and without liability.

Target Group

Students enrolled at European universities with an interest in AI applications

Admission Requirements
 
  • English proficiency at least of B2
  • No prior AI knowledge required
  • Basic familiarity with technology is beneficial
  • Elementary coding skills are helpful but not mandatory
Course Options

Participants may take one, two, or all three of the following courses:

  • AI Applications in Medical Science and Engineering
    Content Highlights: Deep learning for medical image analysis, clinical decision-making, telemedicine applications, patient recommendation systems, conversational systems, AI diagnostics.
  • AI Applications in Data Science and Engineering
    Content Highlights: Data processing with AI, predictive analytics, data-driven decision-making, pattern recognition, model evaluation.
  • AI Applications in Material Science and Engineering
    Content Highlights: AI-driven material property prediction, process optimization, quality control, and material defect analysis.
Disclaimer

The content and delivery of these online courses were created within a research project and were originally designed for students of the Warsaw School of Computer Science. They are now also accessible to other students – though without any guarantee of completeness or reliability.

Quick Links

  • Registration
  • All course descriptions 
  • Project AI for ALL
  • Quality Check
  • HSLU@DTTI
  • HSLU Deep Tech

Prof. Dr. Stephen Wittkopf

Project manager

+41 41 349 36 25

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Prof. Dr. Marc Pouly

Co-Head Applied AI Research Lab

+41 41 757 68 25

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Prof. Dr. Umberto Michelucci

Subject area manager for continuing education Applied Data Intelligence

+41 41 349 31 44

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Priska Büeler

Lecturer

+41 41 349 39 21

E-Mail anzeigen

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