Data Wrangling

2019-2020
Dit vak wordt in het Engels aangeboden. Omschrijvingen kunnen daardoor mogelijk alleen in het Engels worden weergegeven.

Doel vak

The 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.​

Inhoud vak

Data 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
visualization.​

Onderwijsvorm

Lectures (6 x 2 hours) and Q&A sessions (3 x 2 hours).

Toetsvorm

The 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
course.

Literatuur

Slides

Doelgroep

3BA, 3LI, 3CS, 3IMM

Aanbevolen voorkennis

Programming experience in Python.

Algemene informatie

Vakcode XB_0014
Studiepunten 6 EC
Periode P3
Vakniveau 300
Onderwijstaal Engels
Faculteit Faculteit der Bètawetenschappen
Vakcoördinator prof. dr. S. Bhulai
Examinator prof. dr. S. Bhulai
Docenten prof. dr. S. Bhulai

Praktische informatie

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Werkvormen Werkcollege, Hoorcollege
Doelgroepen

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