The specialisation in Data Engineering provides you with in-depth knowledge of data science and machine learning and focuses on both technical skills and practical application. You will gain skills to handle and analyse large amounts of data, as well as to build advanced data solutions that support decision-making.
The specialisation takes you through:
- Principles and technologies for data storage, data management, and data access in various database systems and platforms
- Models and techniques for collecting, integrating and quality assuring data from different sources
- Infrastructure and technologies to scalably handle large volumes of data and data flows
- Analysis and reporting of data with a focus on data science techniques
- Machine learning methods for pattern recognition and knowledge generation from data
- AI techniques such as Natural Language Processing (NLP), image recognition, and deep learning for advanced solutions
- Learn how to communicate data insights visually and create interactive visualizations with tools like Matplotlib and D3.js
The Data Engineering specialisation gives you the opportunity to choose electives according to your interests. Choice of electives may include:
BUI – Business Intelligence
The Business Intelligence course teaches you how to work with realistic data using professional tools in Business Intelligence, such as Microsoft SSIS, SSRS, SSAS and PowerBi.
MAL2 - Machine Learning for Artificial Intelligence
An in-depth course in deep learning for AI, where you work with neural networks, including convolutional and recurrent networks, as well as advanced techniques such as generative adversarial networks (GANs), large language models, and reinforcement learning.
NSQ – No-SQL versus relational databases
This elective gives you knowledge of the strengths and weaknesses of two fundamentally different approaches to database management systems (DBMS). The purpose of the subject is to support matching system requirements and DBMS technologies rather than a one-size-fits-all approach.
DAI - Data Analysis Infrastructure
You will be introduced to various tools and techniques for data acquisition, cleansing, quality assurance and integration as well as to data modelling for analytics and basic visualization.
ERP – ERP Systems SAP ABAP/4 programming
This course introduces the fundamental aspects of analysis, design, coding and testing of programs in the SAP ABAP environment, and you will have the opportunity to work further with a selected part of the SAP system.
SMP - Stochastic modelling and processes
The course provides a basic introduction to the theory behind stochastic processes with a focus on probability theory, statistics, hypothesis testing, regression and Markov chains. Special emphasis is placed on the application of the theory in practice, where you learn to model and analyse complex stochastic situations. Examples and applications will be drawn from various engineering fields, such as information technology, communication, and signal processing.
VIZ - Data Visualisation
Get a thorough introduction to data visualisation, including how data is transformed into graphical representations and how to convey data insights to both technical and non-technical audiences. Learn how to create interactive visualisations and apply techniques from data reporting and Gestalt theory to strengthen visual communication.