This fast-paced class is intended for getting students interested in data science up to speed:

We start with an introduction to the field of "Data Science" and into the overall Data Science Process.

The primary focus of the rest of the course is on gaining fundamental knowledge for Data processing, that is, preparation, cleansing and storage of data, which typically takes the largest part of any data science project. We will learn how to deal with different data formats and how to use methods and tools to integrate data from various sources, plus how to resolve quality issues such as duplicates, encoding errors, missing values, etc. within raw data.

The integrated data can then be used for further data analytics tasks (cf. course 2 in this SBWL).

The students will practice approaches and techniques using the Python programming language in an interactive environment.

All course material will be available at: https://datascience.ai.wu.ac.at/

The attendance of at least 80% of the course units is a mandatory criterion.

Presence in the first lesson is required.

The assessment will be based on the following:

• 10% quizzes
• 85% homework assignments (individual as well as group assignments)
• 5% peer grading
• (up to 5% bonus points from entry exam)

The attendance of at least 80% of the course units is a mandatory criterion.