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IUBH University of Applied Sciences

Master Data Science

IUBH University of Applied Sciences
Online

Price on request
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Important information

Typology Master
Methodology Online
Duration 12 Months
  • Master
  • Online
  • Duration:
    12 Months
Description

Data is becoming the most important asset of data-driven enterprises and plays a pivotal role in tackling the challenges of tomorrow. From the optimisation of existing production lines to the creation of new business models, data-driven decisions are at the centre of digital businesses.

To take into account

· What are the objectives of this course?

Innovation springs from bright minds - our international Master programme puts you into the driver seat of your future career in Data Science. Graduates from our courses go to become technical gurus, team-leaders of successful data-science teams or value-driven masterminds who turn data into action.

· Requirements

Prerequisites for admission to the Data Science Master programme: Completed undergraduate study from a public or officially recognised university/higher education institution; Degree certification of at least “Befriedigend” [lower second equivalent]; Proof of min. one year of relevant work experience; Proof of English skills.

· Qualification

TOEFL (min. 80 points) or IELTS (min. Level 6) or Duolingo English test (min. 51%) or Cambridge Certificate (min. B grade overall) or Equivalent proof The proof must be provided before the start of the study and must not be older than two years. If English is your native language or you graduated from an English-speaking school/university, you do not have to prove your English skills.

· What marks this course apart?

The Master in Data Science opens the door for your career in data-driven businesses.

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What you'll learn on the course

Data science
Mathematics
Data analysis
Data Protection
Data Collection
Data Management
Statistics
Society
Machine Learning
Big Data Management
Big Data Technologies
IT Security
Model Engineering
Software Engineering
Advanced Mathematics
Management Information Systems
Advanced Statistics
Project
Project Control
Project Management

Course programme

1st semester
  • Data Science
  • Advanced Mathematics
  • Seminar: Data Science and Society
  • Advanced Statistics
  • Use Case and Evaluation
  • Project: Data Science Use Case

2nd semester
  • Programming with Python
  • Machine Learning
  • Deep Learning
  • Big Data Technologies
  • Electives A (Selection of one module)

3rd semester
  • IT Security and Data Protection
  • Model Engineering
  • Software Engineering for Data Intensive Sciences
  • Electives B (Selection of one course)
  • Seminar: Current Topics in Data Science

4th semester
  • Master Thesis & Colloquium

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