Informationssysteme (Infosys 18), Bachelor

Semester: SS 2018
Study Courses: Wirtschaftsinformatik (Bachelor), Informatik (Bachelor), Medieninformatik (Bachelor), Cybersicherheit (Bachelor), Mathematik und Informatik (Bachelor)
Credit Points: 6 CP
Contact person: Iaroslav Shcherbatyi

Description

Companies like Facebook and Twitter have recognized the value that data can have if their information content is correctly interpreted and understood. But data science, the extraction of knowledge from data, is also playing an increasingly important role in other areas, such as medicine, health care and the automotive industry. In this lecture we will deal with the basics of data processing and analysis and data management. We also look at concepts of machine learning and deep learning that can be used to calculate predictive models from data.

Data preparation

  • Data acquisition, cleaning & transformation
  • Visualisation methods

Database systems

  • Relational model
  • SQL
  • Warehousing/OLAP
  • Map Reduce
  • NoSQL
  • Key-Value-Stores
  • Cloud Computing

Statistics

  • Distributions
  • Rescaling
  • Error evaluation

Machine Learning

  • Regression
  • Classification

Deep Learning

  • Artificial and Convolutional Neural Networks
  • Recurrent Neural Networks and LSTMs
  • Deep Reinforcement Learning

Modeling

  • Hidden Markov Models

Dates and Rooms

Organization

The lecture will be conducted in cooperation with Prof. Dr. Jens Dittrich. For more information about the lecture click here.