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
- One 2-hour lecture
- One 2-hour lecture each week for 15 weeks
- One 1-hour laboratory each week for 8 weeks
15 two-hours lectures, 1 two-hour revision and 8 one-hour computer labs
Assessment
- 40% Coursework 1: Eight one-hour computer lab assessments
- 60% Coursework 2: One 2500 words individual project
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:
- The development, management, application and implementation of information systems and their impact upon organisations.
- Relevant quantitative techniques, including mathematical and statistical methods and the use of softwares to estimate models using actual data.
Intellectual skills
This module develops:
- The ability to analyse facts and circumstances to determine the cause of a problem and identifying and selecting appropriate solutions.
- The ability to analyse and evaluate a range of business data, sources of information and appropriate methodologies, which includes the need for strong digital literacy, and to use that research for evidence-based decision-making.
- Conceptual and critical thinking, analysis, synthesis and evaluation.
Professional practical skills
This module develops:
- Numeracy and quantitative skills to manipulate data, evaluate, estimate and model business problems, functions and phenomena.
Transferable (key) skills
This module develops:
- Communication and listening including the ability to produce clear, structured business communications in a variety of media.
- Articulating and effectively explaining information.
Conveners
- Dr Sok Gee Chan