The course gives an introduction into applications of data science in the field of sensory data collected by everyday devices like smartphones.

The following topics will be covered:  Basics of sensory data, Handling noise and missing values, feature engineering, learning based on sensory data.

Practical examples will be done in R language.

After completing this course students will have knowledge about different areas of application for data science. Students will have a basic understanding of area-specific challenges and algorithms. Besides an understanding of the problem structure, students will learn to apply mathematical and statistical tools to support decision making. Apart from that, completing this course will contribute to the students’ ability to efficiently work and communicate in a team, work on solutions for complex practical problems by using modern statistical software.

The rules on the attendance of a Continuous Assessment Course (PI) apply. See the dedicated page on the WU portal for further information.

The final grade will be computed on the basis of three assignments. Bonus points may be earned by active participation.

First assignment: 30%

Second assignment: 20%

Third assignment: 50%

Grades:

1: =>90%

2: =>80%

3: =>70%

4: =>60%

Successful conclusion of the course 1 of SBWL Data Science.

Please be aware that, for all courses in this SBWL, registration is only possibly for students who successfully have completed the entry course (Einstieg in die SBWL: Data Science).