Lehrstuhl für Wirtschaftsinformatik und Informationsmanagement

    Practical Data Science (Master)

    Please note: While the course material is provided in english, the lecture as well as the exercise are held in german language.

    Contents & Objectives

    • The foundations, frameworks and applications of the emerging field of data science
    • Design, implement, and evaluate the core algorithms underlying an end-to-end data science workflow, including data import, analysis, and presentation of information
    • Leverage Jupyter Notebook application and data infrastructure that supports data acquisition, storage, retrieval and analysis
    • Application of a data-based analytical approach to identify and solve problems
    • Implementation and execution skills for data-driven business Analytics

    Course Structure

    1. Basics 
    2. Exploratory Data Analysis
    3. Recap Machine Learning
    4. Modeling
    5. Feature Engineering
    6. Ensembling


    Lecture and Exercise:
    Tuesday, 10.00 – 12:00, Room 409 (Neue Universität)
    First appointment: 15.10.2018

    Additional documents on WueCampus:

    • Jupyter Notebooks
    • Data sets and assignments
    • Submission of solutions

    Test: Group project