Data Science
In this age of digitalisation, data science plays an increasingly important role in the media landscape and our social discourse. Exciting use cases, technological innovations, or controversial discussions: it’s not always easy to keep track.
As a result of the field`s vitality, data scientists are in great demand. In many organisations, data literacy, and therefore, the number of “Citizen Data Scientists” – people who create models based on advanced diagnostic analytics, although their actual jobs are outside this area of competence – is increasing. Against this background, data science experts are indispensable when it comes to developing and testing hypotheses, as they are the ones who help companies make sense of the data they collect.
Our online Master in Data Science focuses primarily on current developments in software and infrastructure engineering, as well as on Big Data technology. You’ll learn to fully develop your problem-solving skills, and how to take a methodical, focused, and logical approach to data science problems.
In your Master’s degree in Data Science, you’ll primarily study current developments in software and infrastructure engineering, as well as Big Data technology. As you work through each of these individual topics, the key focus will be on practical problem-solving skills. The aim of this course is to prepare you to work as a specialist, who can develop challenging data science applications and systems, in both the private and public sectors.
The order of courses presented below is for the online studies model of this programme.
Course Overview (FI-MADS-60)
- Module DLMDSAS: Advanced Statistics
- Module DLMDSUCE: Use Case and Evaluation
- Module DLMDSSCTDS: Seminar: Current Topics in Data Science
- Module DLMDSML: Machine Learning
- Module DLMDSDL: Deep Learning
- Module DLMDSME: Case Study: Model Engineering
- Module DLMDSEBDSE: Big Data and Software Engineering
- Module DLMDSESMMI: Smart Manufacturing Methods and Industrial Automation
- Module DLMDSEAAD: Applied Autonomous Driving
- Module DLMMTHE: Master Thesis
Course Overview (FI-MADS-120)
- Module DLMBDSA1: Data Science
- Module DLMDSAM: Advanced Mathematics
- Module DLMDSSDSS: Seminar: Data Science and Society
- Module DLMDSAS: Advanced Statistics
- Module DLMDSUCE: Use Case and Evaluation
- Module DLMDSPDSUC: Project: Data Science Use Case
- Module DLMDSPWP: Programming with Python
- Module DLMDSML: Machine Learning
- Module DLMDSDL: Deep Learning
- Module DLMDSBDT: Big Data Technologies
- Module DLMDSEDSS: Data Science Specialist
- Module DLMDSETPL: Technical Project Lead
- Module DLMDSEDE: Data Engineer
- Module DLMDSEBA: Business Analyst
- Module DLMCSITSDP: Cyber Security and Data Protection
- Module DLMDSME: Case Study: Model Engineering
- Module DLMDSSEDIS: Software Engineering for Data Intensive Sciences
- Module DLMMANE: Management
- Module DLMBSPBE: Sales, Pricing and Brand Management
- Module DLMBCBR: Consumer Behavior and Research
- Module DLMBCF: Corporate Finance
- Module DLMDSEIAC-01: Innovate and Change
- Module DLMDSECC: Cognitive Computing
- Module DLMDSEAAD: Applied Autonomous Driving
- Module DLMDSESLS: Self Learning Systems
- Module DLMDSEIAAIT: Industrial Automation and Internet of Thing
- Module DLMDSSCTDS: Seminar: Current Topics in Data Science
- Module MMTHE: Master Thesis