Data Analytics with Python (5cr)

Evaluation scale

H-5

Objective

The student acquires basic knowledge regarding data analysis libraries in programming. The student knows how to use data analysis libraries and statistical analysis to prepare data for machine learning algorithms.

Basic programming skills are required for this course.

Content

- Data preparation: loading, filtering, combination, classification
- Data visualization, exploration and analysis
- Using appropriate data analysis libraries in programming

Materials

Lecture material
- Web naterial
- Examples and live coding
- Exercises
- Web learning environments

Teaching methods

The development environment of the course is Python (version 3) and especially additional modules in the Python Analysis Stack. The lectures will be held according to the timetable. The student will produce exercises independently.
Basic programming knowledge is required in the course.

Completion alternatives

Collections in Python
Python Analysis Stack -modules, especially NumPy, Pandas and Seaborn
Other useful modules
Loading data
Data exploration and analysis
Data manipulation and transformations
Preparing data for other modules

Assessment criteria, satisfactory (1)

The student is able to prepare and modify a simple data set under instruction for machine learning algorithms or a cloud computing service.

Assessment criteria, good (3)

The student is able to choose appropriate data preparation methods independently to produce data for machine learning algorithms or a cloud computing service.

Assessment criteria, excellent (5)

The student is able to choose the most suitable data preparation methods independently to produce data for machine learning algorithms or a cloud computing service.