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Data Analytics for Managers

  • Analytics & Tech
  • Innovation & Business Improvement
  • Intermediate
  • SkillsFuture
  • Short Courses

This module is conducted in-person.

Next course starts on
To be advised
Fee
SGD1,744* (as low as SGD203.20 after maximum funding) Learn More
Duration

2 days
Weekdays (9am - 5pm)

Level
Intermediate

Who Should Attend

Managers covering/ leading analytics functions

PREREQUISITES

  • Participants should have at least a diploma to benefit from the training
  • Participants should have some knowledge of statistics, and be very comfortable with software tools

Overview

Data analytics have been touted as the most important technology which will bring organizations to their next frontier.

Many success stories have been shared on how data analytics can help organisations make better decisions, including understanding their customers better, predicting outcomes, understanding public sentiments on social media, and optimising resources to achieve the best results.

Managers who are leading their organisations have to play the lead role in shaping the direction and planning the strategies on who, what, when, where and how should data analytics be applied in the different parts of the organisation.

The proposed training is designed for managers covering several topics in the Data Analytics area. The training will be conducted by the senior faculty members from the School of Information Systems, who are experts in their respective areas.

Learning Objectives

  • Gain a quick overview of data analytics
  • Understand the solution flow to solve data analytics problems
  • Acquire data analytics techniques and learn how to use related tools through hands-on sessions
  • Gain insights into data visualisation, predictive modelling, and optimisation

Topic/Structure

S/NTopicsSample Data and Problem SetsSoftware Tools
1Introduction to Data Analytics  
2

Visual Analytics for Data Discovery

  • Principles and concepts of visual analytics
  • Interactive data exploration and analysis approach (IDEA)
  • Designing interactive graphics for data discovery
  • Visualising and analysing geospatial data
  • data.gov
  • Geospace
  • REALIS
  • MyTransport.SG Data Mall
  • Kaggle
Tableau 2018
3

Data Analytics Techniques

  • Data analytics lifecycle
  • Supervised vs Unsupervised learning
  • Predictive analytics
  • Pros and cons of each technique
  • Select the best technique
  • Train, test and validate model
  • Results assessment and interpretation
  • Data analytics technologies: commercial off-the-shelf (COTS) vs open source
 JMP Pro
Weka
4

Prescriptive Analytics - Optimisation

  • Optimisation theory
  • LP, IP, MIP, BIP
  • Model formulation
  • Solver definition
  • Police patrol problem
  • Road lamps problem
  • School allocation problem
MS Excel with Solver add-in

Assessment

As part of the requirement for SkillsFuture Singapore, there will be an assessment conducted at the end of the course. The mode of assessment, which is up to the trainer’s discretion, may be an online quiz, a presentation or based on classroom exercises.

Participants are required to attain a minimum of 75% attendance and pass the associated assessment in order to receive a digital Certificate of Completion issued by Singapore Management University.

Calculate Programme Fee

Click here for more infomation about SkillsFuture Credits (Not applicable for Company-sponsored participants)
For PSEA - Available only for Singapore Citizen below 31 (Not applicable for Company-sponsored participants)

Total Program Fee: SGD0.00

Fee Table

COMPANY-SPONSORED

PARTICIPANT PROFILE

SELF-SPONSORED

SME

NON-SME

Singapore Citizen < 40 years old

Permanent Resident

LTVP+

$523.20

(After SSG Funding 70%)

$203.20

(After SSG Funding 70%
+ ETSS Funding 20%)

$523.20

(After SSG Funding 70%)

Singapore Citizen ≥ 40 years old

$203.20

(After SSG Funding 70%
+ MCES Funding 20%)

$203.20

(After SSG Funding 70%
+ ETSS Funding 20%)

$203.20

(After SSG Funding 70%
+ MCES Funding 20%)

International Participant

$1,744

(No Funding)

$1,744

(No Funding)

$1,744

(No Funding)

All prices include 9% GST

Please note that the programme fees are subject to change without prior notice.

Post Secondary Education Account (PSEA)
PSEA can be utilised for subsidised programmes eligible for SkillsFuture Credit support. Click here to find out more.

Self Sponsored

SkillsFuture Credit

Singapore Citizens aged 25 and above may use their SkillsFuture Credits to pay for the course fees. The credits may be used on top of existing course fee funding.

This is only applicable to self-sponsored participants. Application to utilise SkillsFuture Credits can be submitted when making payment for the course via the SMU Academy TMS Portal, and can only be made within 60 days of course start date.

Please click here for more information on the SkillsFuture Credit. For help in submitting an SFC claim, you may wish to refer to our step-by-step guide on claiming SkillsFuture Credits (Individual).

Workfare Skills Support Scheme

From 1 July 2023, the Workfare Skills Support (WSS) scheme has been enhanced. Please click here for more details.

Company Sponsored

Enhanced Training Support for SMEs (ETSS)

  • Organisation must be registered or incorporated in Singapore
  • Employment size of not more than 200 or with annual sales turnover of not more than $100 million
  • Trainees must be hired in accordance with the Employment Act and fully sponsored by their employers for the course
  • Trainees must be Singapore Citizens or Singapore Permanent Residents
  • Trainees must not be a full-time national serviceman
  • Trainees are eligible for ETSS funding only if their company's SME status is approved prior to the course commencement date. To verify your SME's status, please click here. 

Please click here for more information on ETSS.

Absentee Payroll

Companies who sponsor their employees for the course may apply for Absentee Payroll here. For more information, please refer to:

AP Guide (Non-SME Companies)
Declaration Guide (SME Companies)

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Trainers

Dr Kam Tin Seong
Associate Professor of Information Systems (Practice)
Singapore Management University
Dr Kam Tin Seong
Associate Professor of Information Systems (Practice)
Singapore Management University
Dr Kam is an Associate Professor of Information Systems (Practice) at Singapore Management University's School of Computing and Information Systems. He contributes to the Master of IT in Business (Analytics) programme, focusing on data analytics for professionals in various fields. With over twenty years of experience in analytics and academia, his interests lie in data analytics, customer analytics, data visualisation, interactive analytics, and geospatial analytics. Dr. Kam is actively involved in consulting and executive training, offering expertise in data visualisation, analytics, and GIS for numerous government agencies and companies, including P&G, Citibank, and the United Nations Centre for Regional Development. He has worked with organisations such as DBS, OCBC, and various government ministries, showcasing his broad expertise in the field.
Dr Michelle Cheong
Professor of Information Systems

Associate Dean, SIS Post-Graduate Professional Education

Director, Doctor of Engineering
Singapore Management University
Dr Michelle Cheong
Professor of Information Systems

Associate Dean, SIS Post-Graduate Professional Education

Director, Doctor of Engineering
Singapore Management University
Dr Cheong, Professor of Information Systems and Associate Dean at Singapore Management University, brings 8 years of industry leadership experience in developing enterprise-wide IT systems. Since 2005, she has taught Business Modeling with Spreadsheets and co-authored a related book. Dr Cheong spearheaded the Master of IT in Business (Analytics) programme in 2011, the first of its kind in Asia, and continues to shape it. Additionally, she designed and instructs the Operations Analytics course within the program, along with executive courses in Data Analytics for various programmes including Master of Science in Communication Management, IE-SMU MBA, and Master of Science in Innovation.

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