ST-LE-2023-10
Curriculum: Starter TrackComputer science basics for data science
Motivation
Computer science is a key component for data science applications and
research data management as methods and procedures rely on it. For instance, to
enable fast access to information, data sets must be stored efficiently in data
structures. Clever modelling and algorithmic processing hereby guarantee a fast
search and selection of information of even big data sets. This course will
provide insights into computer science basics and gives an overview about
relevant topics for data science.
Learning contents
- Computer science and its subdisciplines: applied, technical, practical, theoretical
- Programming languages
- Data storage and -processing
- Data structures
- Example: Sorting (Bubble Sort, Merge Sort, Quicksort)
Learning objectives- Basic overview about computer sciences and its subdisciplines; basics in system engineering
- Computer science and its subdisciplines: applied, technical, practical, theoretical
- Programming languages
- Data storage and -processing
- Data structures
- Example: Sorting (Bubble Sort, Merge Sort, Quicksort)
Prior knowledge
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Further reading
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Motivation
Computer science is a key component for data science applications and research data management as methods and procedures rely on it. For instance, to enable fast access to information, data sets must be stored efficiently in data structures. Clever modelling and algorithmic processing hereby guarantee a fast search and selection of information of even big data sets. This course will provide insights into computer science basics and gives an overview about relevant topics for data science.
Learning contents
- Computer science and its subdisciplines: applied, technical, practical, theoretical
- Programming languages
- Data storage and -processing
- Data structures
- Example: Sorting (Bubble Sort, Merge Sort, Quicksort)
Learning objectives
- Basic overview about computer sciences and its subdisciplines; basics in system engineering
- Computer science and its subdisciplines: applied, technical, practical, theoretical
- Programming languages
- Data storage and -processing
- Data structures
- Example: Sorting (Bubble Sort, Merge Sort, Quicksort)
Prior knowledge
---
Further reading
---
When?
April 25, 2023, 2:00 PM - 4:00 PM
Where?
DFKI Bremen
Robert-Hooke-Straße 1
28359 Bremen
and
Online via Zoom
Register until:
April 22, 2023
Drechsler, Prof. Dr. Rolf
German Research Center for Artificial Intelligence (DFKI) in Bremen, Director of the Cyber-Physical Systems Group
Institute of Computer Science at the University of Bremen, Full Professor and Head of the Group of Computer Architecture
Email: drechsler@uni-bremen.de
Cooperating in U Bremen Research Alliance:
