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Professional Master Study Programme in Applied Computer Engineering

Data Science

This study programme is validated by Goldsmiths, University of London. Seize the unique opportunity to study in English and earn a Dual Degree from Algebra University and Goldsmiths, University of London!

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  • 96% of alumni employed 3 months after graduation

The Data science sub-specialization is one of four Professional Master Study Programme in the field of applied computer engineering.

When you delve into the curriculum of this course, you will see that it encompasses the area of data analysis, social network analysis, affective computing, machine learning of statistics analysis, quantitative analytical methods, data visualization, and also fundamental business concepts suitable for master level.

Apart from the fundamentals, you will learn how to use those skills to create a “story” based on data (“data driven business”. Contextualizing based on data, also called “storytelling” is considered to be one of the most important skills today. It is recommended as a universal skill each of us should strive to perfect. Our society is based on stories that form the base for our way of communicating, living and dreaming.

Upon receiving our diploma, you’ll become a true specialist for data science. This is an inter-disciplinary field, which the industry calls the ‘Fourth Paradigm’ of science. You’ll learn how to analyze and process large amounts of data and to extrapolate information required for sound business operations.

Student guide

What are the takeaways from the data science master computer engineering course?


Master studies allow you to further perfect your know-how of your favorite field. We’ll transfer the latest industry trends, insights and skills that employers demand onto to you. Here is a snapshot of some of them:


The master study programme has been conceived based on recommendations from the European SOCRATES network and satisfies the criteria based on ASIIN accreditation agency recommendations, which are applicable in the field of computer engineering.

Impact of Disruptive Technologies

Learn how to critically analyze the impact of disruptive technologies on the business environment and learn to spot new emerging ones.

Evaluating Complex Problems

You’ll hone your skills for using applied mathematics and information theory for analyzing and evaluating complex and insufficiently defined problems.

Work with Data

You’ll learn how to apply appropriate methodology, recommend and select best solutions for queries in data integration, normalization and discretization.

Data Privacy

You’ll adopt an analytical approach to provisions of ethical codes that protect rights to privacy.

Social Networks Analysis

Understand what social network analysis is and what its goals are and how to rank the basic functionalities of social network analysis software.

Cloud Analytics

Understand its advantages and disadvantages as well how to apply cloud analytics to solving business problems.

Big Data

Find out how to rate product quality through analyzing big data chunks and re-evaluating its potential.

Examples of jobs we’re preparing you for

  • Data Analyst
    A wide array of tasks awaits you, from developing IT support, accessing data from various sources and preparing databases.
  • Specialist for Business Intelligence (BI)
    You’ll be implementing analytical and integrated data storage and business decision support systems.
  • Data Specialist
    A true expert for discovering and extracting knowledge from hidden data and their interpretation and visualization.
  • Data Engineer
    A very dynamic job, depending on the specialization, it can include anything from data preparation and effective data architecture, all the way to its interpretation and sophisticated analysis.
  • Project Manager
    A responsible position overseeing planning and execution of projects involving implementation of database for analytical systems.

Example Class

Affective Computing

Interaction between a human being and a computer, in which the computer recognizes, interprets and reacts to a person’s emotions and expressions. The course will introduce you to the basics of analyzing and recognizing affective states. We’ll explore the characteristics of affective expressions and find out all the ways that computers can gather data on the user (facial expressions, posture, gestures, voice and temperature changes). We’ll also be looking at practical applications and development of models for recognizing affective states in industries.

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Learn all about the study programme

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