Data Science Modelling with Excel
In the 21st century, we continue to see a rising trend in the applications of Data Science (DS) from the use of GrabPay to the example of Siri. The applications of Data Science encompass all walks of life and indirectly every aspect of the business - from how business acquires data to how data contributes and complements with the traditional intuitive decision-making approach. Data Science will not only continue to shape how industries operate in the near future but also revolutionise how firms harness Data to its full potential. Data Scientist has been hailed the "sexiest career in the 21st Century", however, not only are firms competing to hire good data scientists, but are also starting to see the need to groom their in-house Subject Matter Experts into a functional-hybrid kind.
We will focus on how Data Science is being used across a wide spectrum of industries. We will also explore various use cases and applications of Data Science and its potential for improving our daily lives. Participants will be able to leverage on Data Science to complement with their Domain Expertise to contribute within the Data Science Pipeline. Participants will be equipped with the Basics of Data Science Modelling and Algorithm with Excel.
This course is designed to introduce the general concepts of Data Science to anyone, regardless of their computing or math background.
At the end of this course, participants will be able to apply the basic Predictive Analytics, basic Machine Learning and basic Statistical Model based on a prescribed project.
Plan your learning path
This course can be taken as a module on its own or as part of the Graduate Certificate in Data Analytics (Non-Programming) stack and participants will earn 12 subject credits which can also be used towards completing the ModularMaster in Data Science.
Past Intakes
7 Jun - 26 Jul 2021
Who Should Attend
- Learners especially those working in an industry or role dealing with data, who would benefit from data science modelling with the use of ready tools, applications, plugins and Microsoft Excel.
Prerequisites
- Some literacy and competency in basic mathematics and computers
- Participants are encouraged to complete Data Wrangling and Preparation with Excel and Data Validation and Statistical Analysis with Excel before enrolling for this course
Course Fees and Funding
SkillsFuture Course Fee Subsidy
(70%)
Fee after subsidy
$1,350.00
GST on Fee after SSG Course Fee Subsidy
$94.50
You pay
$1,444.50
Mid-career Enhanced Subsidy (MCES)
(90%)
Fee after subsidy
$450.00
GST on Fee after SSG Course Fee Subsidy
$94.50
You pay
$544.50
Enhanced Training Support for SMEs (ETSS)
(90%)
Fee after subsidy
$450
GST on Fee after SSG Course Fee Subsidy
$94.50
You pay
$544.50
Full Course Fee (without subsidies): $4,815 (inclusive of prevailing GST)
Instructor
Assoc Prof Duan Lingjie
Singapore University of Technology and Design
Lingjie Duan is an Associate Professor (Tenured) in the Engineering Systems and Design Pillar at Singapore University of Technology and Design. He received Ph.D. degree in Information Engineering from The Chinese University of Hong Kong in 2012. During 2011, he was a visiting scholar in the Department of Electrical Engineering and Computer Sciences at University of California at Berkeley.
Lingjie Duan has been actively working and contributing to the interdisciplinary research field combining computer networks and game theory. He has used optimization and game theory extensively as both modeling languages and solution tools to study the cooperative or competitive interplay among various parties in communications and networking. He received 2016 SUTD Excellence in Research Award, and in 2015 he received the 10th IEEE ComSoc Asia-Pacific Outstanding Young Researcher Award. He was also the Finalist of Hong Kong Young Scientist Award 2014 under Engineering Science track. He has many highly-cited top engineering and business publications, and his works on network economics attract ever-increasing attention from academia and industry.
Thia Wei Soon
Instructor, SUTD Academy
Wei Soon has more than ten years of experience working in the manufacturing and IT sectors. He worked as a data scientist using data analytics and machine learning to deliver actionable insights and drive strategic marketing initiatives. In recent years, as a technology consultant, he successfully helped clients to streamline enterprise operations and achieved cost saving through the adoption of robotic process automation.
Wei Soon has a Master of IT in Business Artificial Intelligence from Singapore Management of University and a B.Eng in Mechanical Engineering from Nanyang Technological University. He is proficient with tools such as Tableau, Jupyter, RStudio, MS Visual Studio, Automation Anywhere, UiPath, and programming languages such as Python, R, C#, HTML5, and JavaScript.
ModularMaster Certificate in Data Science
Course Structure and Pathways
Two Tracks
We have designed two tracks to cater to participants with different learning preferences.
Participants who prefer to make use of programming can go for the modules under the Programming Track while participants who prefer to make use of readily available tools can embark on modules under the Non-Programming Track.
For participants who do not possess a programming background, you may also take on a Bridging pathway towards the Programming Track.

Policies and Financing Options