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M.Sc. Data Science (Online)

M.Sc. Data Science (Online)

IU International University of Applied Sciences

Máster online


547 /mes

Duración : 12 Meses

The IU online Master Data Science program equips you with comprehensive theoretical knowledge essential for becoming an expert in the field. From machine learning to big data systems, you'll delve into a diverse array of topics poised to drive any company forward. Your ideal data science role is within reach – seize the opportunity to invest in your future and reap the rewards.

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

1. SEMESTER

  • Advanced Statistics
  • Use Case and Evaluation
  • Seminar: Current Topics in Data Science
  • Machine Learning
  • Deep Learning
  • Case Study: Model Engineering


2. SEMESTER

  • Electives:
  • Big Data and Software Engineering
  • Smart Manufacturing Methods and Industrial Automation
  • Applied Autonomous Driving
  • Master Thesis


1. SEMESTER

Modules

  • Data Science
  • Advanced Mathematics
  • Seminar: Data Science and Society
  • Advanced Statistics
  • Use Case and Evaluation
  • Project: Data Science Use Case


2. SEMESTER

Modules

  • Programming with Python
  • Machine Learning
  • Deep Learning
  • Big Data Technologies
  • Electives A


3. SEMESTER
Modules

  • Cyber Security and Data Protection
  • Case Study: Model Engineering
  • Software Engineering for Data Intensive Sciences
  • Electives B
  • Seminar: Current Topics in Data Science


4. SEMESTER
Modules

  • Master Thesis & Colloquium
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