Advanced Certificate in Applied Data Science and Analytics (II)
- Analytics & Tech
- Innovation & Business Improvement
15 Days
Who Should Attend
- Ideal for analysts in various industries who has familiarity in data work using Excel and proficient in Python. Familiarity with Tableau/Power BI skills or similar data handling exposure is an added advantage.
- Enhances Data Science capability for competent business or data analyst roles.
PREREQUISITES
This programme is structured to provide a comprehensive learning experience. Participants are required to sign-up for all five (5) modules and complete the modules in the designated sequence to ensure a solid understanding of each topic before moving on to the next.
It is ideal for participants who has completed Advanced Certificate in Applied Data Science and Analytics (I). Participants who has familiarity with fundamental Data Science concepts and proficient in Python can also attend.
Overview
The Advanced Certificate in Applied Data Science and Analytics (II) is a hands-on, five-module programme designed to enhance practical data science capabilities for the workplace.
Participants will begin with advanced machine learning techniques using Python, then progress to Generative AI and its applications, followed by data science project and model management. They will then understand nuances of ethical & sustainable Data Science, and finally, apply their skills in a capstone practicum that simulates real-world data projects.
The programme equips professionals with the advanced Data Science techniques, leverage Generative AI and learn how to manage and maintain Data Science solutions in an ethical & sustainable manner in a professional environment. Thus helping increase organisational value.
Topic/Structure
To achieve the Advanced Certificate in Applied Data Science and Analytics (II), participants will need to complete the following modules offered by SMU Academy:
Module 1: Advanced Machine Learning
Module 2: Generative AI and its Applications
Module 3: Data Science Project and Model Management
Module 4: Ethical and Sustainable Data Science
Module 5: Practicum Using Machine Learning and Generative AI Models and Tools
Assessment
As part of the requirement for SkillsFuture Singapore, there will be an assessment conducted at the end of every module. 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 for each of the 5 modules within 3 years in order to be awarded the digital Advanced Certificate in Applied Data Science and Analytics (II) 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+
|
$4,905 (After SSG Funding 70%) |
$1,905 (After SSG Funding 70% |
$4,905 (After SSG Funding 70%) |
|
Singapore Citizen ≥ 40 years old |
$1,905 (After SSG Funding 70% |
$1,905 (After SSG Funding 70% |
$1,905 (After SSG Funding 70% |
|
International Participant |
$16,350 (No Funding) |
$16,350 (No Funding) |
$16,350 (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.
Intake Information
| MODULES | DATES |
|---|---|
| Module 1: Advanced Machine Learning | 3 - 6 Feb 2026 [Upcoming Schedule] |
| Module 2: Generative AI and its Applications | 9 - 11 Mar 2026 [Upcoming Schedule] |
| Module 3: Data Science Project and Model Management | 6 - 8 Apr 2026 [Upcoming Schedule] |
| Module 4: Ethical and Sustainable Data Science | 27 - 29 Apr 2026 [Upcoming Schedule] |
| Module 5: Practicum Using Machine Learning and Generative AI Models and Tools | Session 1: 2 May 2026 (9am-11am) |
*Online registration will close 5 calendar days before the course start date
