Lucerne School of Engineering and Architecture Lucerne School of Engineering and Architecture
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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: The courses are approved by deep tech and quality assurance experts of the European Institute of Innovation and Technology
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.