Foundational Business Analytics
| Code | School | Level | Credits | Semesters |
| BUSI4390 | Nottingham University Business School China | 4 | 20 | Autumn China |
- Code
- BUSI4390
- School
- Nottingham University Business School China
- Level
- 4
- Credits
- 20
- Semesters
- Autumn China
Summary
This module introduces fundamental statistical concepts and key descriptive modelling techniques in data science, while laying a foundation for the general programming skills required by any top modern business analyst (e.g. Python / R). A range of descriptive modelling concepts will be covered (such as feature engineering, clustering techniques, rule mining, topic modelling and dimensionality reduction) against a background of real world datasets (predominantly based on consumer data). Students will learn not only how to successfully implement foundational descriptive techniques, but also how to evaluate and communicate results in order to make them effective in actual business environments.
Target Students
MSc Business Analytics students
Classes
- Two 1-hour lectures each week for 11 weeks
- One 2-hour computing each week for 11 weeks
Total Contact Hours 44 hours (4/week over 11 weeks) 200 hours in Total. Background study 56 hours Coursework: 50 hours Revision: 50 hours
Assessment
- 20% In-class quizzes: Four 30-minute in-class quizzes (3 out of 4)
- 30% In-class Computer-based test: A Python scripting test
- 50% Individual Coursework: An 3000-word (8-page) applied analytics coursework
Educational Aims
To develop understanding and practical skills in core descriptive analytic techniques. This will cover fundamental statistical knowledge, general programming skills and approaches to common problems within business analytics. Students will also complete the module with appropriate evaluation and communication skills to produce results that are effective in real-world situations.Learning Outcomes
• Marketing and sales – different approaches for segmentation, targeting, positioning, generating sales, and the need for innovation in product and service design
• Customers and stakeholders - customer expectations, service and orientation
• The management of projects
• Tools and techniques for transforming (big) data into useful information for business analysis and decision support
• Communications – the comprehension and use of relevant communications for application in business and management, including the use of digital tools
• Digital business – the development of strategic priorities to deliver business at speed in an environment where digital technology is reshaping traditional revenue and business models, associated risk management
Conveners
- Dr Jenny Pu