Capstone Project Developing a Data Analytics Model

Course Reference No: CRS-N-0047038


Course Objectives

This course aims to help participants apply data analytics knowledge and skills to understand and solve business problems, prepare and analyze data, communicate results, and subsequently create business values for their organisations.

At the end of the course, you should have a working knowledge of how to solve data science problems with R and the following:

  • Create a detailed problem statement to address real-world business problems
  • Use appropriate data and the technical skills they have/will learn to solve such problems
  • Use data visualization to communicate the deliverables


Day 1
  • How is Analytics Used Across the World
  • Reflection on Potential Projects
  • Initial Data Analysis & Insights
  • Data Science Essentials
  • Project Case Study
  • Capstone Project
    • Project Scoping
    • Initial Data Understanding
Day 2
  • Data Analysis Walkthrough (Part 1) – Data Analytics Tools Recap
  • Data Analysis Walkthrough (Part 2)
  • Data Preparation and Analysis using R (Programming Fundamentals)
  • Predictive Modelling using R (Linear Regression demo)
Day 3
  • Data Visualisation Using Qlik Sense (Part 1) – Various Chart Types (Bar, Line, Pie, Area, etc)
  • Data Visualisation using Qlik Sense (Part 2) – Various Chart Types (Scatter, Bubble, Heatmap, Map etc)
  • Data Visualisation and Communication Storyline
  • Project Presentation


R and Qlik Sense


Participants should have some basic project management knowledge, data analytics and/or programming experience.

Who Should Attend

Managers and Engineers in the ICT sector

Mode of Training



Dr Julian Lin

Dr. Julian Lin is a Senior Lecturer in Cybersecurity and Data Analytics with School of Continuing and Lifelong Education (SCALE) at the National University of Singapore (NUS).  He is a Certified Information Systems Security Professional (CISSP) and has a dozen other IT certifications. Recently, Julian was ranked 6th in the Microsoft Data Science Capstone Competition. He has been conducting text-analytics research since 2010 and teaching  visualization since 2007. 

During his IT consultancy career, he oversaw the application and infrastructure projects in Amoseas,  Mannesmann Dematic Colby (Sydney), Alcatel (Sydney), and the University of New South Wales (UNSW) Faculty of Commerce and Economics. Julian has taught programming and data management for business at UNSW.  At NUS, he had mentored student software development projects and taught visual communications, designing new media content, and research methods. He was given a  teaching award for visualization class and research award for user acceptance research in NUS. 

Julian obtained a PhD degree in Information Systems from NUS.  He was a recipient of two scholarships from the Overseas Chinese Association in Taiwan while pursuing his Bachelor degree and another scholarship while pursuing a Master degree in Australia.

Dr Guo Lei

Dr Guo Lei is an active educator and researcher in data science, behavioural study and design thinking, with extensive experience in delivering practice-based learning programmes and applied research projects with successful results.

Starting her career in Singapore as a marketing practitioner, Dr Guo worked across manufacturing, entertainment and education industries. She was the Chief Representative in China for a Singapore listed company. She was also responsible for setting up Shanghai Office and promoting executive education programmes for NUS Business School in Greater China market.

With the aspiration of bridging the gap between research and practice, Dr Guo pursued her PhD in the UK, where she worked on large-scale research projects with Cambridge University Service Alliance, BAE Systems and China Mobile.

Dr Guo returned to Singapore and joined NUS as a faculty member in 2011. She has particular experience in tackling complex challenges through applied research and education. She was the Principal Investigator for a series of research projects to inform better public transport policy decisions. She consults local and overseas corporate clients on data analytics, user experience design and service innovation. Dr Guo teaches executive programmes of Data Analytics and Design Thinking at NUS. She has a passion for engaging and inspiring working professionals at all levels by applying the theory to real world business applications.

Dr Guo holds a PhD in Marketing from University of Exeter, an MBA from University of Adelaide and a BA in Literature from Beijing Normal University.


Mr Koo Ping Shung

Mr Koo Ping Shung is an experienced Data Scientist with more than 13 years of relevant experience. He is also currently a Adjunct Senior Faculty with the Singapore University of Social Sciences (SUSS) and a SAS Trainer as well. To date, he has conducted over 1,600 man-hours of data science training. He is also the mentor to the trainees accepted into the IMDA-SAS BIA Programme for 5 intakes.

Ping Shung was a guest lecturer at NUS Institute of Systems Science and previously held an adjunct position in School of Information Systems, Singapore Management University.

Prior to this, he was the Analytics Practicum Manager of the Master of IT in Business (Analytics) at the Singapore Management University School of Information Systems. He managed the industrial relationships through projects and attachments. He often advised companies on the type of data analytics projects they can work on with their data and is a co-supervisor for many Masters students on their data analytics capstone projects. He was an instructor for the DBS Graduate Associate Programme for 3 years, teaching over 200 Graduate Associates on data analytics and received positive ratings. He has also trained professionals from various companies on data analytics and the use of SAS software.

Ping Shung was a facilitator for the IDA Data Science MOOC programme for 2 cohorts (over 300 professionals) and participated in Singapore's first Data Literacy Bootcamp which was co-organised by the IDA Singapore and The World Bank.

Ping Shung through his career has gathered much experience on statistical modeling, from working in the banks, supervising Masters students and doing education research. His data analytics experience range from a wide variety of business functions and industries, gathered from talking to companies or working on data analytics projects.

His strong passion in data analytics and data science can be seen through his involvement in data analytics interest groups, being a Co-founder of DataScience.Sg and former Working Committee Chairman of SAS User Group Singapore and Data Ambassador for one of the DataKind SG project. He also read widely on the different topics related to data science and artificial intelligence, keeping himself up-to-date with their development.

His research interest lies in how data science can help organisations and businesses to be more efficient and effective.

Ping Shung holds an MBA from University of Adelaide. He obtained his bachelor degree in Economics from National University of Singapore, with a minor in Computational Finance.




3 Days
9.00am to 5.30pm 


National University of Singapore
University Town

International Participants


Incl. GST

Singapore Citizens
(39 yrs old or younger) 
or Singapore PRs


Incl. GST

Singapore Citizens
(40 yrs or older)


Incl. GST

Enhanced Training Support for SMEs


Incl. GST

Fees & Fundings

Singapore Citizen1
39 years old or younger
Singapore Citizen1
40 years or older eligible for MCES2
Singapore PRs Enhanced Training
Support for SMEs3
Full Programme Fee S$2,400.00 S$2,400.00 S$2,400.00 S$2,400.00 S$2,400.00
SkillsFuture Funding
Eligible for Claim Period
(25 May 2018 - 30 Sep 2020)
- (S$1,680.00) (S$1,680.00) (S$1,680.00) (S$1,680.00)
Nett Programme Fee S$2,400.00 S$720.00 S$720.00 S$720.00 S$720.00
7% GST on Nett
Programme Fee
S$168.00 S$50.40 S$50.40 S$50.40 S$50.40
Total Nett Programme
Fee Payable, Incl. GST
S$2,568.00 S$770.40 S$770.40 S$770.40 S$770.40
Less Additional Funding if
Eligible Under Various Scheme
- - (S$480.00) - (S$480.00)
Total Nett Programme Fee, Incl. GST,
after additional funding from the various funding schemes
S$2,568.00 S$770.40 S$290.40 S$770.40 S$290.40

  1. All self-sponsored Singaporeans aged 25 and above can use their $500 SkillsFuture Credit to pay for the programme. Visit to select the programme. 
  2. Mid-Career Enhanced Subsidy (MCES) - Singaporeans aged 40 and above may enjoy subsidies up to 90% of the programme fee. 
  3. Enhanced Training Support for SMEs (ETSS) - SME-sponsored employees (Singaporean Citizens and PRs) may enjoy subsidies up to 90% of the programme fee. For more information, visit
  4. Eligible organisations (excluding government entities) may apply for the absentee payroll funding via SkillsConnect at for Singaporean/permanent resident participants attending the programme during working hours. The absentee payroll funding is computed at 80% of hourly basic salary capped at $4.50 per hour or $7.50 per hour for SME. For more information, visit
  5. Eligible individuals may apply for training allowance capped at $6/hr under the WSS scheme, visit- for more information on WSS.
  6. NTUC Training Fund (SEPs) – All self-employed (i.e. freelancers and sole-proprietors-with-no-employee) Singaporeans and Permanent Residents are eligible to apply for the NTUC Training Fund (SEPs) from NTUC’s Employment and Employability Institute (e2i). Click here for more information.
NTUC members enjoy 50% of the unfunded course fee support for up to $250 each year for courses supported under UTAP (Union Training Assistance Programme). Terms and Conditions apply. Please visit
Sign Up Now
12 November 2020