Overview
In this dynamic landscape, we can position ourselves by staying up to date with emerging technologies and continuously improving our data-driven decision-making abilities.
The NUS School of Computing (SOC) offers the Data Intelligence & Business Analytics Programme as a suite of short courses to prepare trainees for job roles such as Business Analyst, Data Analyst, Data Architect, or Associate Data Engineer. Throughout the programme, students will gain an understanding of the analytical techniques and tools used in data science and learn how to apply these tools to projects. By the end of the programme, students will have the ability to interpret business specifications, turn insights into creating business value for organisations, and contribute to their organisation’s growth and success.
The Data Analytics Programme consists of 8 modules:
Using Business Analytics to Answer Business Questions (Synchronous e-learning)
Descriptive Analytics
Applied Analytics using Predictive Modelling
Python Programming
Prescriptive Analytics – From data to optimal course of action
Trisector Strategy and Innovation for Transformation (Problem Setting)
Trisector Strategy and Innovation for Transformation (Data Collection and Analysis)
Trisector Strategy and Innovation for Transformation (Idea Generation and Strategy Consolidation)
Course Description & Learning Outcomes
This programme will equip the participants with the following skills:
Understand Business Intelligence
Understand the functionalities of PowerBI for Business Intelligence
Learn the tools and techniques to perform data preparation
Understand how to make use of tools to perform data exploratory analysis
Understand how to embark on a data mining project
Understand the fundamental key concepts of various predictive analytics techniques
Acquire basic proficiency in popular data analytics tools such as R
Build a strong foundation in the fundamentals of Python programming
Learn to use libraries such as Numpy and pandas in the Python API
Understand how to model business problems for optimisation, interpret sensitivity analysis and shadow prices
Problem Setting, Data Collection and Analysis and Idea Generation and Consolidated Strategy
Recommended Prerequisites
General Diploma
Schedule
End Date: 30 Nov 2026, Monday
Subject to date
Location: 11 Research Link, COM 3, Singapore , 119391 and OnlinePricing
Skills Covered
PROFICIENCY LEVEL GUIDE
Beginner: Introduce the subject matter without the need to have any prerequisites.
Proficient: Requires learners to have prior knowledge of the subject.
Expert: Involves advanced and more complex understanding of the subject.
- Business Analytics (Proficiency level: Beginner)
