Difference between the qualification "Data Analyst (IHK)" and "Data Science Foundation"
Data is the basis of digitalization and is becoming the most important asset for companies. Employees who understand data processes and analysis methods and can apply them even without in-depth computer science training, have new opportunities to make their work processes more efficient and creative. The CITT already offers two qualifications in the field of "Data". Since both qualifications included the programming language "Python", but in different scopes, we would like to discuss the differences below:
What is the difference between the two training courses "Data Analyst (IHK)" and "Data Science Foundation"?
The main difference between the two training courses is that they relate to different job roles or areas of responsibility.
- As the name suggests, "Data Analyst (IHK)" prepares students for a job as a data analyst. The main task is the evaluation of existing, structured data.
- "Data Science Foundation" aims to become a data scientist. The main focus is on solving or optimising problems with the help of statistical methods. This means that, in contrast to the field of activity of the data analyst, no data is yet available. As a data scientist, you recognize the need for data within a situation and create the data basis yourself by applying statistical methods.
What are the focal points of the training offerings?
In the "Data Analyst (IHK)" training course, you will learn the basics of data processing and data analysis. You understand how data processes work, can plan them and efficiently turn them into reality. In addition, you can visualize complex data and facts clearly and interactively and thus provide a maximum of information. You will also learn how to work with Python and Power BI.
In the "Data Science Foundation" training offer, you will also learn the programming basics of Python and Power BI and how you can use them for data science applications in a productive corporate environment. The focus is particularly on the areas of data management and machine learning. As a prospective data scientist, you will go beyond the mere evaluation and analysis of data and also learn about statistical methods for data creation.
For which target group are the training offers suitable?
Both courses are suitable for all subject areas. Both training courses provide basic knowledge, so no previous experience is necessary. However, you should have a certain affinity for IT and an interest in programming languages such as Python.
Data analytics and data science applications can be used across a wide range of departments, from production to marketing.
