Nanyang Technological University

Nanyang Business School

Nanyang Business School - Undergraduate Programmes

Course Description

BC0401 Programming for Business Analytics

Acad Unit: 3
Pre-requisite: NIL

Course Description:

This is an introductory course designed for a business analytics student who has no programming background and is interested to learn how to conduct business analytics programmatically. It is oriented to enhance your technical skillset. The aim of this course is to provide a broad understanding on how to manage data, the process of preparing data for analysis, basics of analytics, and the means to communicate analytics outcome. This course will equip you with the ability to write customized solutions to inform business decision, integrate statistical libraries for data analysis, and construct visuals or reports for business understanding. This module will provide you with individual hands-on practices to hone your coding skillset and opportunity to develop coding solution in a team. We utilize Python language as the medium of learning because it is the most in-demand coding language and its user-friendly syntaxes are well suited for beginner level. You will utilise modern development tools to turn information into insights. In essence, this course exposes students to computational thinking so that they understand the possibilities of automation.

You will learn to understand the development environment of programming language. Then move on to pick up language semantics like coding syntax, variables, methods, functions, mathematical operators, Boolean operators, decisions, compound decision, control structures and iterations. These will help you to build a holistic understanding on programming basics and the ability to write code independently. The course will also cover foundation of business analytics including how to define problem statements in the business context, data preparation, data transformation, data consolidation, data analysis, and data visualization. The course will also cover the various analytics concepts like predictive analytics for categorical, quantitative and time series data. Lastly, machine learning for predictive analytics will also be introduced.