Master 2025/2026

Data Analytics and Mining

Type: Elective course (Master of Business Analytics)

Delivered by: Master's Programmes Curriculum Support

When: 2 year, 3 module

Open to: students of one campus

Language: English

Contact hours: 16

Course Syllabus

Abstract

The course provides a comprehensive foundation in data processing, visualization, and fundamental analytical techniques. Covers essential methods for supervised and unsupervised learning, including data pre-processing, dimensionality reduction, and prediction models. Students will gain hands-on experience with data mining techniques and explore key concepts in machine learning, from classical approaches to an introduction to deep neural networks. The course also emphasizes practical applications, equipping students with the skills needed to analyze data effectively and extract meaningful insights across various domains. The students will gain different skills: use Python in data analysis applications;filter/sort/process data/create new variables.;calculate descriptive statistics and interpret the results; convert feature values to z-scores.; handle missing values and outliers; implement exploratory data analysis. apply parametric statistical tests to test hypotheses; mplement deep neural networks for prediction tasks. implement machine learning models for prediction. Students will visualize data using the charts: line, scatter, heat map, box plot, and others.