Intermediate Courses

  • Course Outline

Data Analytics and Visualisation Begins With Me

This course is eligible for SkillsFuture Singapore (SSG) funding.
Course Reference No: TGS-2020513790 (Classroom Learning), TGS-2020501910 (Synchronous e-Learning)

  • Course Objectives

We live in a world that revolves around data. Data is regarded as the key resource that powers the world in the 21st century. According to the International Data Corporation (IDC), many organizations still lack the data literacy skills to achieve business value. Organizations that have accumulated a large amount of data would not see many benefits until it is harnessed to work for your organization. Poor data literacy is one of the stumbling blocks and limits a company’s ability to reap value from data. To combat this, organizations will have to promote and develop their staff’s competencies in data.

Data literacy, as defined by MIT, is the ‘ability to read, work with, analyze, and argue with data’. It is a set of core essential skills everyone in an organization needs to use data effectively in their day-to-day activities and for decision-making. Used in the right way, data can help every employee achieve their objectives, perform their job better, and contribute to overall company performance. Employees who are data literate will also understand how to handle data appropriately, which will reduce the number of data breaches. Managers have to lead their organizations by setting the direction and the strategies on how data can be applied in the various parts of the organization. This course is designed for all professionals to gain the fundamental skills to understand and work with data for the organization.

 

This course aims to provide participants with a foundation in:

Overview of data and data analytics

  • How to read, work, analyze, and argue using data
  • Data as a language and common terminologies
  • Data analytics process and project life cycle
  • Tools and technology used for data analytics and visualization
  • Machine learning and data visualization techniques

At the end of the course, participants will be able to:

  • Apply data analytics techniques using tools through hands-on sessions
  • Apply data visualization techniques using tools through hands-on sessions
  • Gain insights from data using various machine learning techniques
  • Work with and communicate using data
  • Outline

This programme consists of 2 components, Asynchronous e-Learning modules and Synchronous Online / Classroom Learning facilitated workshops as shown in the diagram below.

Asynchronous e-Learning modules consists of the following 8 modules; World of Big Data, Data Literacy, Data Fluency, Data Analytics, Land of Statistics, Problem-solving with Data, Arguing with Data, Visualising Data.

Three Synchronous Online / Classroom Learning facilitated workshops will cover the following topics:

Workshop 1

  • Analytics Project Life Cycle
  • Hands-on practice using Orange: Supervised learning models

Workshop 2

  • Hands-on practice using Tableau: Data Visualisation

Workshop 1

  • Hands-on practice using Orange: Classification Models and Unsupervised Learning Models

Assessments may comprise of mini-projects, presentations, workshop assignments or quizzes, etc.

  • Who Should Attend

Professionals working with data

  • Pre-Requisites

Knowledge of fundamental statistics and mathematics

  • Software Tools

Orange and Tableau

  • Mode of Training

Blended (On-campus/Online)

  • Course Details
Dates:

No course intakes will be scheduled until further notice
Duration:

1.5 Days, 9.00am to 5.30pm (Daily) [Facilitated Learning: 10.5 hours, e-Learning: 4.4 hours, Assessment: 4.7 hours]
Venue:

Blk S16, 6 Science Drive 2, Level 2, Active Learning Room, Singapore 117546 / Online
Course Calendar:

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*Please note that registration will be closed 2 weeks before the course start date, or when the registration has reached maximum capacity, whichever earlier.

  • Course Fees
Course fee BreakdownInternational ParticipantSingapore Citizen 39 years old or youngerSingapore Citizen 40 years or older eligible for MCESSingapore PRsEnhanced Training Support for SMEs
Total Nett Programme Fee after 9% GST + additional funding from the various funding schemesS$2,180.00S$654.00S$254.00S$654.00S$254.00
  • Instructor Profiles

DR BENJAMIN LEE

MS CHUA BEE LUAN

  • Course Registration

NA

  • Contact Us

For all Short Courses and Professional Certificates related, please email us at fos.shortcourses@nus.edu.sg.

  • FAQs

Registration will close two weeks before commencement date or when the class is full, whichever earlier. If you wish to register after the registration closes, please email us and we may review on a case-by-case basis.

An acknowledgement email will be sent to you.

No. The acknowledgment email is to inform you that the registration is submitted successfully. Your registration is still required to be processed by the short course coordinator internally. Should you have any queries pertaining to your registration, or have any changes to be made, please email us.

  • The short course coordinator must be notified in writing of all requests for withdrawals and deferment at least 7 days before the run.
  • If you have accepted the offer to a short course programme run, but find that you are unable to attend, you should notify us by writing to fos.shortcourses@nus.edu.sg.
  • Applicants may postpone participation and request for deferment to other course runs, subject to availability.
  • Requests for cancellation will be considered on a case-by-case basis, and refunds may be issued.
  • We are unable to process any refunds for NUS Alumni utilising R&G vouchers. More information on R&G Voucher can be found here.

Please refer to the ‘Course Fees’ section in the course brochure.

Yes. All Singapore Citizen/SPR attending SSG funded courses will be eligible for SSG Funding, provided you have not taken the same course before.

In addition, you must meet the criteria:

    • Achieve a ‘Competent’ grade in all assessment(s)

The course fees will automatically be tabulated with the relevant SSG funding based on your eligibility. No action is required from the participant/company except to ensure that the participant meets the two criteria stated above.

Yes. Once an offer of placement has been granted for your application, you will have to accept the offer via L3AP and make the payment via your SkillsFuture credits. Payment is not required upfront during registration.

  • Visa, Mastercard, Amex or Alipay
  • PayNow (a QR code will be displayed during payment)
  • SkillsFuture credits (you will be required to submit an SFC claim upon making payment, you will be redirected to an external link for you to authenticate using Singpass on SFC website)

Once your registration has been processed and an offer of placement has been granted to you, you will receive an automated email for you to accept the offer on L3AP.

Once you have accepted the offer, you will be directed to the payment page. 

Yes. The mode of assessment is up to the CET instructor’s discretion. It may be a reflection paper, quiz, presentation, or based on classroom activities. You will be required to achieve a ‘Competent’ grade for the assessment(s).

You will be notified by the short course coordinator if you did not achieve “Competent” for the short course. You may be offered for a deferment for the next available class.

An e-certificate will be issued upon successful completion within 20 working days.

The name on the e-certificate will be issued according to the full name as per registration.

DR BENJAMIN LEE

Senior Lecturer

Benjamin Lee is a Senior lecturer in Data Analytics and Visualization with the School of Continuing and Lifelong Education (SCALE) at NUS.
He has over 30 years’ experience in IT and information management. His career roles span CIO, Director of IT services, Strategy and Planning, Project management, Applications development, Systems engineering, Data management and IT outsourcing. Business and Industry experiences include electronic business development, implementation of business process re-engineering and functional support for Finance, HR, Manufacturing, Retail and mergers/acquisitions in Oil and Gas. He has been actively involved in data and information management since 2000 and has successfully implemented global projects covering data warehouses, management information systems, data analytics and e-business systems. In those projects, Ben had applied data analytics to improve resource management and sales profitability with better understanding of customers, products and services.
Ben has been teaching information & data management and business analytics classes since 2016. He holds a Doctorate in Business Administration from the University of Western Australia. He also has Masters in Business Research and Physics and a Bachelors in Law. He has a strong interest and passion for data analytics, visualization and e-business.

MS CHUA BEE LUAN

Senior Lecturer

Chua Bee Luan is a Senior Lecturer in Data Analytics and Visualization with the Department of Statistics and Data Science at the National University of Singapore, Faculty of Science.

Bee Luan is a passionate educator with nearly two decades of teaching experience in an institute of higher learning. She taught modules in Business Analytics, Data Visualization, Website Design, Business Software, Statistical Methods and Calculus. In her capacity as a lecturer, Bee Luan was involved in developing FutureReady certification courses and conducting SkillsFuture for Digital Workplace courses for the adult learners in the banking and aviation industries. In support of the NUS resilience and growth (R&G) initiative, she also provides training for fresh graduates so that they can continue to learn in the uncertain times of COVID-19. Prior to teaching, Bee Luan began her career in the IT industry in multiple roles, from project management to IT consulting in both MNC and SME companies. She had provided consulting services to her clients to streamline their business processes and had successfully rolled out numerous company-wide Enterprise Resource Planning (ERP) projects for companies mostly in trading and manufacturing industries.

Bee Luan graduated with a Bachelor of Science with Honours, double major in Computational Science and Mathematics from NUS. She also holds a Master in Business Administration in Strategic Management from the Nanyang Technological University and had obtained a Certificate in Teaching & Learning (Higher Education). Teaching has always been her passion and Data Analytics is her new area of interest.