Introduction to Data Analytics II

Code School Level Credits Semesters
BUSI1127 Nottingham University Business School 1 20 Spring Malaysia
Code
BUSI1127
School
Nottingham University Business School
Level
1
Credits
20
Semesters
Spring Malaysia

Summary

This module covers topics such as, Statistics for Data Science, Exploratory Data Analysis, Data Visualisation, Linear Regression, Basic Machine learning methods such as Clustering and Classification. Students will also learn how to implement basic data analysis algorithms to extract business insights from data.

Target Students

Available to all Business School students with the required pre-requisite BUSI1125 Softwares and Tools for Data Analytics.

Co-requisites

Modules you must take in the same academic year, or have taken in a previous year, to enrol in this module:

Classes

15 two-hours lectures, 1 two-hour revision and 8 one-hour computer labs

Assessment

Assessed by end of spring semester

Educational Aims

The aim of this module is to equip students to be abreast with common tools used for Data Analytics. The primary goal of this course is for students to learn data analysis concepts and techniques that extract insights from data and make decisions. This course will provide students with introductory knowledge of several data science techniques that can be used for data analysis. After successfully completion, this course will help students understand how to use data analysis tools, and especially, provide an opportunity to utilize an open source data analysis tool for data manipulation, analysis, and visualization.

Learning Outcomes

Knowledge and understanding

This module develops a knowledge and understanding of:

 

Intellectual skills

This module develops:

 

Professional practical skills

This module develops:

 

Transferable (key) skills

This module develops:

 

Conveners

View in Curriculum Catalogue
Last updated 09/01/2025.