Semester: 1
ECTS: 5
Lectures: 15
Practice sessions: 30
Independent work: 105
Module Code: 24-132-0459
Semester: 1
ECTS: 5
Lectures: 15
Practice sessions: 30
Independent work: 105
Module Code: 24-132-0459
Module title:
Data engineering
Module overview:
For the data analysis to have high quality results, it is necessary to make the preparation of the input data. The aim of the course is to demonstrate basic methods of data preparation that includes methods of cleaning, transforming, introverting, normalizing and aggregating data, time series transformation, work with missing values as well as basic data reduction methods such as feature reduction, sample reduction, and discretization.
Literature:
Essential reading:
1. Crickard, P (2020) Data Engineering with Python: Work with massive datasets to design data models and automate data pipelines using Python, Birmingham: Packt Publishing,