Professional Certificate in Machine Learning (Python)
- Analytics & Tech
- Artificial Intelligence
- Innovation & Business Improvement
This programme is conducted on-campus.
Please refer to respective modules for dates.
Singapore Management University
Who Should Attend
- Professionals and managers in data science, engineering, or IT seeking to upskill in machine learning and AI
- Individuals transitioning into machine learning roles who have basic Python or programming experience
- Industry practitioners looking to understand and implement AI-driven solutions for business challenges
- Analysts or researchers aiming to apply ML/ AI techniques to data-driven decision-making processes
PREREQUISITE
- Basic programming knowledge is recommended to enrol for this programme
SYSTEM REQUIREMENTS
- Functional Laptop: (1) CPU must be of at least intel core I3, (2) GPU must have an integrated graphics card and (3) RAM must be of at least 4GB
Overview
Designed for working professionals, the programme focuses on practical implementation over theoretical concepts, enabling learners to work with advanced Python tools, explore supervised and unsupervised learning techniques, and leverage state-of-the-art AI technologies such as deep learning and large language models. By the end of the course, participants will be proficient in creating end-to-end machine learning pipelines, performing data analysis, and applying cutting-edge AI applications in their industries.
With a modular structure, participants can progressively develop their skills while balancing learning with their work commitments. Practical exercises, case studies, and hands-on projects ensure applicability in professional settings.
Learning Objectives
- Build and deploy machine learning pipelines efficiently using Python
- Apply supervised and unsupervised learning techniques for various business applications
- Understand and implement deep learning models for computer vision and transfer learning tasks
- Leverage language models and multi-agent AI workflows for automation and innovation
- Solve real-world problems using scalable, production-ready ML solutions
Topic/Structure
To achieve the Professional Certificate in Machine Learning (Python), participants need to complete the following modules offered by SMU Academy in sequential order:
Module 1: Machine Learning Data Pipelines and Visualisation Mastery with Python
Module 2: Statistical Mastery for Machine Learning and Artificial intelligence (AI) Success
Module 3: Supervised Machine Learning for Building and Deploying Models
Module 4: Unsupervised Machine Learning and Advanced Techniques for Insights
Module 5: Deep Learning and Machine Learning Mastery in Vision and Transfer Learning
Module 6: Machine Learning with Language Models and Agentic Workflows for Organisational Transformation
This course is also a part of the Industry Graduate Diploma in Python Programming and Machine Learning.
Assessment
- Classroom exercises
- Group assignments
- Individual assignment
CERTIFICATION
Upon completion of all 6 modules within a maximum duration of 3 years, participants will be awarded a digital Professional Certificate in Machine Learning (Python).
Calculate Programme Fee
Fee Table
| COMPANY-SPONSORED | |||
|
PARTICIPANT PROFILE |
SELF-SPONSORED |
SME |
NON-SME |
|
Singapore Citizen < 40 years old Permanent Resident LTVP+
|
$4,708.80 (After SSG Funding 70%) |
$1,828.80 (After SSG Funding 70% |
$4,708.80 (After SSG Funding 70%) |
|
Singapore Citizen ≥ 40 years old |
$1,828.80 (After SSG Funding 70% |
$1,828.80 (After SSG Funding 70% |
$1,828.80 (After SSG Funding 70% |
|
International Participant |
$15,696 (No Funding) |
$15,696 (No Funding) |
$15,696 (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
| Modules | Next Intake |
|---|---|
| Module 1 - Machine Learning Data Pipelines and Visualisation Mastery with Python | 2, 4 & 6 Sep 2025 [Open for Registration] |
| Module 2 - Statistical Mastery for Machine Learning and Artificial Intelligence (AI) Success | 23, 25 & 27 Sep 2025 [Open for Registration] |
| Module 3 - Supervised Machine Learning for Building and Deploying Models | 14, 16 & 18 Oct 2025 [Open for Registration] |
| Module 4 - Unsupervised Machine Learning and Advanced Techniques for Insights | 5, 6 & 8 Nov 2025 [Open for Registration] |
| Module 5 - Deep Learning and Machine Learning Mastery in Vision and Transfer Learning | 26, 27 & 29 Nov 2025 [Open for Registration] |
| Module 6 - Machine Learning with Language Models and Agentic Workflows for Organisational Transformation | 17, 18 & 20 Dec 2025 [Open for Registration] |
