Advanced Certificate in Applied Data Science and Analytics (II) Module 4: Ethical and Sustainable Data Science
- Analytics & Tech
- Innovation & Business Improvement
This module is conducted in-person.
3 Full Days (Weekdays)
Who Should Attend
- Ideal for non-data analysts in various industries using Excel for data work. Requires basic Tableau/Power BI skills or similar data handling exposure.
- Enhances digital literacy for competent business or data analyst roles.
PREREQUISITES
This programme is structured to provide a comprehensive learning experience. Participants are required to complete the modules in the designated sequence to ensure a solid understanding of each topic before moving on to the next.
Overview
This module emphasises the ethical and sustainability aspects of Data Science. While Data Science provides significant advantages in extracting knowledge from data for business and operational benefits, it also entails ethical responsibilities. Data-driven predictions and decision-making can profoundly impact individuals and communities. Despite the vast potential of data science for problem-solving and insight generation, ethical considerations have only recently gained widespread attention, particularly since 2015. Ethics can be defined as the science of morals or the moral evaluation of choices. Ethics in data science involves evaluating the moral implications and ensuring socially acceptable practices in research and analysis.
In this module, participants will delve into various aspects of data science ethics. They will explore the broad spectrum of data science ethics and the impact of ethics across different fields of data science. The module will highlight the risks associated with overlooking ethical considerations and present strategies for mitigating ethical issues. Additionally, the module addresses sustainability concerns in data science. As Data Science/Artificial Intelligence (DS/AI) tools are increasingly utilised for efficiency, Chief Technology Officers are increasingly concerned about the potential rise in energy consumption. The module will also cover best practices and guidelines to ensure sustainable practices in data science.
Learning Objectives
At the end of the 3-day module, participants will be able to:
- Gain an understanding of the spectrum of Data Science Ethics
- Learn how ethics influence Data Science/Artificial Intelligence (DS/AI) in various fields and understand pitfalls of ignoring ethics
- Know how to mitigate ethical issues
- Learn how to undertake green DS/AI projects
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
Fee Table
| COMPANY-SPONSORED | |||
|
PARTICIPANT PROFILE |
SELF-SPONSORED |
SME |
NON-SME |
|
Singapore Citizen < 40 years old Permanent Resident LTVP+
|
$981 (After SSG Funding 70%) |
$381 (After SSG Funding 70% |
$981 (After SSG Funding 70%) |
|
Singapore Citizen ≥ 40 years old |
$381 (After SSG Funding 70% |
$381 (After SSG Funding 70% |
$381 (After SSG Funding 70% |
|
International Participant |
$3,270 (No Funding) |
$3,270 (No Funding) |
$3,270 (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)
Intake Information
This module is conducted in-person.
| Course | Dates |
|---|---|
| INTAKE 1 | [To Be Advised] |
*Online registration will close 5 calendar days before the course start date
