Advanced Certificate in Applied Data Science and Analytics (II) Module 3: Data Science Project and Model Management
- 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 focuses on practical skills for project and model management in real-life data science projects. Participants will gain essential skills in understanding analytics processes and best practices, managing data sources and required resources, upholding data governance, and comprehending the structure of analytics solutions. Additionally, they will have the opportunity to either perform data visualisation, present insights through compelling data storytelling, conduct predictive modelling or forecasting, implement advanced machine learning models, or develop generative artificial intelligence solutions. The module emphasises planning and managing projects to ensure successful delivery and implementation of final solutions within a proper framework.
Moreover, in today’s world, organisations often rely on numerous data-driven Data Science/Artificial Intelligence models for day-to-day operations. Given that these models' performance can change with shifts in data patterns, ongoing validation and maintenance are essential. Participants will also learn about the critical aspects of model maintenance in Data Science.
Learning Objectives
At the end of the 3-day module, participants will be able to:
- Learn the key characteristics of a data driven organisation and key stakeholders
- Understand the challenges of data collection
- Learn analytics lifecycle and technology consideration for rapid deployment
- Learn Data Science (DS) and Artificial Intelligence (AI) project management aspects (which is different from IT project management)
- Learn model management, maintenance and documentation
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
