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M.Sc. Applied Artificial Intelligence in Healthcare (Online)

M.Sc. Applied Artificial Intelligence in Healthcare (Online)

IU International University of Applied Sciences

Máster online


547 /mes

Duración : 12 Meses

With IU's Master's in Applied Artificial Intelligence in Healthcare program, you'll gain exposure to a variety of AI solutions tailored to address healthcare challenges. This degree equips you with a robust understanding of computer science, machine learning, and healthcare, empowering you to forge innovative connections between AI and medicine. By bridging these disciplines, you'll propel both fields towards new frontiers, driving innovation and shaping the future of healthcare.

Why should you choose IU?

• Affordable: Enjoy tuition fee reduction

• Flexible: 24/7 access to IU’s digital learning materials, wherever you are

• 24/7 Assistance: IU’s AI-driven teaching assistant helps you prepare for exams, find materials in the virtual library, and clarify questions

• Career-oriented: Courses combine theory and practical application through real-world case studies

• International: All programmes are accredited according to German and EU standards in education

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Requisitos

Academic Requirements: - Completed degree from a public or officially recognised university/higher education institution in relevant field. - At least a “satisfactory” or Grade C equivalent earned in your previous degree. - Your undergraduate degree should be worth 240 ECTS credits. Professional Experience: For some 60-ECTS master programmes, you will need to have achieved one year of professional work experience before starting your studies. English Level: - Proof of English skills. - If you do not meet the English skills requirements, IU offers a free of charge English Language course. This is available to you if you meet the other admission requirements. - If English is your native language or you graduated from an English-speaking school/university, you do not have to prove your English skills.

Temario completo de este curso

SEMESTER 1

  • Machine Learning

  • Deep Learning

  • Reinforcement Learning

  • Inference and Causality

  • Seminar: Current Topics in AI

  • AI in Healthcare

SEMESTER 2

  • AI in Medical Imaging and Diagnostics

  • Medical NLP

  • Medical Robotics and Diagnostics

  • Master Thesis

Module guide

Course schedule

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