Teaching

With the current advances in the data collection process, we collect vast amount of data that comes from different sources and follows different structures. The volume, variety and velocity of collecting the data pose extra challenges on maintaining the quality of the data, which influences any data analytics and decision-making task. In order to prepare the data for the different tasks, data wrangling steps ensure the transformation of raw unstructured data into clean, organized and suitable formats.

The course is designed to balance conceptual understanding with practical implementations (applied & real-world data), using both SQL and Python for data extraction, integration, preparation and validation.

This course is one day training for the government employees. The course consists of 3 main parts. The first is an introduction to NoSQL databases.The reasons behind the development of the NoSQL systems is explained, alongside the most characteristic types and systems that are classified under the noSQL category. The second part of the course talks about the novel programming model of Map Reduce. After the explanation of the model some examples on how it can be used are performed. The Map Reduce system constitutes the basis of the Hadoop ecosystem. A more modern system is the one of Apache Spark. In the third part of the course, after a short introduction to Apache Spark, the learners will have the opportunity to perform a number of examples in a Spark environment and understand the way it works and the benefits it offers.

Data do not fall from heaven, but are created, manipulated, transformed, and cleaned - in any data analysis, therefore, the treatment of the data itself is just as important as the modeling techniques applied to them. In this course, you will get acquainted with and implement a variety of techniques to go from raw data to analyses, visualizations and insights for science and business applications. This is an overview course designed to give you the tools and skills to use and evaluate data science methods.

The course consists of two parts, data wrangling and data analysis, which are intertwined.

This is the starting and obligatory course for the Business Informatics (MBI) programme as well as the Applied Data Science profile. As such, its primary objective is to inspire and introduce you to the exciting domain of Applied Data Science. At the end of this course, you will be able to:

• Understand the role of data science and its societal impact
• Recognise the knowledge discovery processes in applied data science
• Identify trends and developments in big data technologies
• Apply selected big data technologies to solve real-world problems
• Analyse unstructured data using natural language processing techniques
• Understand the need for self-service data science

Applied data analytics is a multidisciplinary field where students learn insights needed to make sense of data, research, and observations from everyday life. Students learn how to apply a data-driven approaches to problem solving. They do not only learn about tools, methods, and techniques, or the latest trends, but also more generic insights: why do certain approaches work, why the field is so popular, what common mistakes are made, and so on. Students also learn that data analytics is of two parts: science part and art part. This is because applying methods and searching for findings is a creative component.

This course is one day training for the government employees on big data technologies. It has been offered in September 2021, July 2022, July 2024, July 2025, June 2026.