Course ObjectiveThe course is geared toward getting data ready for its end purpose.
After this course, the student should be able to:
1. acquire data from different online and offline sources,
2. understand how to clean and pre-process data,
3. transform data for analytics purposes,
4. perform feature engineering,
5. visualize data.
Course ContentData wrangling is the process of gathering data in its raw form and
molding it into a form that is suitable for its end use. This course is
about how to gather the data that is available and produce an output
that is ready to be used. There are a number of common steps in the data
wrangling process that will be discussed: acquiring, cleaning, shaping
and structuring the data, as well as feature engineering and
Teaching MethodsLectures (6 x 2 hours) and Q&A sessions (3 x 2 hours).
Method of AssessmentThe final grade is determined by hand-in assignments (30% of the final
grade), a presentation
and a report (70% of the final grade). Both parts have to be passed with
a grade that is at least 5.5. There are no resit options for this
Target Audience3BA, 3LI, 3CS, 3IMM
Recommended background knowledgeProgramming experience in Python.
|Language of Tuition||English|
|Faculty||Faculty of Science|
|Course Coordinator||prof. dr. S. Bhulai|
|Examiner||dr. R. Bekker|
prof. dr. S. Bhulai
You need to register for this course yourself
Last-minute registration is available for this course.
|Teaching Methods||Seminar, Lecture|
This course is also available as: