Fraunhofer Institute for Experimental Software Engineering IESE
KI Sicherheit in sicherheitskritischen Bereichen.
Seminar: Certified Data Scientist
Data Scientist Basic Level (certified)
More and more companies are realizing the potential of the huge amounts of data available today. Data scientists with special skills are in high demand. They are true artists when it comes to processing and analyzing data.
The Fraunhofer Big Data Alliance offers a three-stage certification program for data scientists. The first stage, the basic certificate "Data Scientist Basic Level," is currently available for booking. The training provides you with a broad range of knowledge that will enable you to work efficiently in data science teams.
Information and details about the seminar
Data Scientist - Interview with Dr. Andreas Jedlitschka
What actually distinguishes a data scientist, what qualifications do they need, and what tasks do they perform? We asked our expert Dr. Andreas Jedlitschka, Head of the Data Science Department at Fraunhofer IESE and member of the Data Science Technical Committee of the Personnel Certification Body at the Fraunhofer Institute FIT in Sankt Augustin, in an interview.
Read the interview on our Fraunhofer IESE blog.
To the blog article: "DATA SCIENTIST – In hot demand thanks to Big Data!"
Tabbed contents
Target group
Target Group
- Managers
- Project managers
- Specialists
Prerequisites
- Basic knowledge of statistics and data analysis is required.
- Basic knowledge of programming and working with databases is an advantage.
Admission requirements for certification
- University degree or equivalent qualification with individual proof
Certification
Certification is carried out by the Fraunhofer Personnel Certification Body. The certificate attests to the graduates' relevant innovative practical knowledge and proven competence.
Learning objectives
After the seminar, you will know...
- ... how business developers tap into the potential of big data in their companies.
- ... how data engineers describe and integrate data.
- ... how analysts use machine learning methods to identify patterns and trends.
- ... how software engineers develop robust and scalable big data systems using modern databases and distributed computing methods.
The seminar offers you...
- ... how business developers tap into the potential of big data in their companies.
- ... how data engineers describe and integrate data.
- ... how analysts use machine learning methods to identify patterns and trends.
- ... how software engineers develop robust and scalable big data systems using modern databases and distributed computing methods.
Methodology
The seminar was designed by experts and specialists from the Fraunhofer Society and has already been successfully held several times. Seminar participants receive personal support from the Fraunhofer team and gain direct access to expertise from research and practice.
Become a data scientist—certified and highly sought after!
More and more companies are realizing the potential of the huge amounts of data available today. Data scientists with special skills are in high demand. They are true artists when it comes to processing and analyzing data.
The Fraunhofer Big Data Alliance offers a three-stage certification program for data scientists. The first stage, the basic certificate "Data Scientist Basic Level," is currently available for booking. The training provides you with a broad range of knowledge that will enable you to work efficiently in data science teams.
You will learn:
- how business developers tap into the potential of big data in their companies
- how data engineers describe and integrate data how analysts use machine learning methods to identify patterns and trends, and
- how software engineers develop robust and scalable big data systems using modern databases and distributed computing methods.
What does Paul Bocuse (French three-star-decorated chef) have to do with Data Science?
IESE blog -What has Paul Bocuse got to do with data science?
Read on our blog how author Julien Siebert explains that the data science process is lik a cook preparing a new menu. He draws comparisons with the ingredients (data), some preexisting intuition (domain and technical/professional expertise), and the right equipment (tools).
To the article "What does Paul Bocuese have to do with Data Sciene?"