Upskilling: Data

In the ’Data’ area, we provide in-depth knowledge and practical skills in dealing with data. We focus on teaching participants how to collect, analyze and interpret data effectively. We focus on learning skills in data analysis, data management and data-driven decision-making. Through our courses and seminars, participants learn how to use data to gain new insights, make decisions and initiate strategic actions.

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Machine Learning

This workshop is aimed at beginners who want to learn more about machine learning. Participants gain insights into the basic concepts and methods of machine learning and their practical applications. Hands-on exercises consolidate understanding and make it easier for participants to get started in machine learning.

Python for data analysis and visualization

This training provides an introduction to using Python for data analysis and visualization. Participants will learn Python programming to analyze data effectively and create beautiful visualizations.

Python for beginners

This training focuses on programming with Python, a widely used programming language worldwide. Participants learn the essential elements of Python, including variables, data structures, loops, and functions. The course aims to create a basic understanding of programming and enable participants to develop simple Python programs independently.

SQL for Data Analysis

This training provides a comprehensive insight into SQL. It is specifically designed for data analysts who want to expand or refresh their SQL skills. The course covers the basics of SQL, including data query, data manipulation and analysis. By the end, participants will be well-equipped to use SQL effectively for data analysis and reporting.

Tableau for beginners

This training offers an introduction to the world of Tableau. Together, we’ll explore the basics of this powerful data visualization tool, including importing data, creating beautiful dashboards, and designing powerful visualizations.

How to break into Big Data?

This training will explain why different roles are critical in Big Data. The tasks of a data engineer, data analyst, and data scientist and their everyday work are described. There are also answers: How can you get started on this topic without prior knowledge, and what resources are needed?

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