Data Science Training
For several years, we have been conducting an extensive and multilingual data science training initiative for our client at multiple international locations. In doing so, we impart foundational knowledge, programming skills, and methodological content directly related to banking and finance topics.
Challenge
A few years ago, our client decided to proactively address the data revolution by upskilling their employees. The goal was to enable them to recognize the potential of data science technologies and methods, as well as to optimize or automate existing work processes using modern programming languages.
Approach
Through both code-based and no-code training sessions at various experience levels, participants from diverse functions and areas learn to understand and apply the benefits of data science to their daily work. After an introduction to the basics of programming with R or Python, code-based training allows participants to independently work on use cases from the banking and finance sectors.
The focus of the code-based training is on topics such as data wrangling, visualization, and machine learning. In no-code training, the emphasis is on organizational challenges and value creation through data. By combining theory and practical application of data analysis using visual and menu-driven data science tools, participants gain a practical understanding of the possibilities and limitations of the discipline.
Result
As part of a multi-year and internationally scaled training initiative, we have trained over 900 participants in programming, data manipulation, data visualization, and machine learning—through both technical and non-technical training sessions for different experience levels.
Download the entire case study for free now
