AI Application in Medical Science and Engineering
AI Application in Material Science and Engineering
AI Application in Data Science and Engineering

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.

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.