Advanced Certificate in Artificial Intelligence in the Digital Economy
- Analytics & Tech
- Innovation & Business Improvement
12 Full Days (Weekdays)
Who Should Attend
- Professionals across technology, data science, business development, and other sectors seeking foundational knowledge and strategic application of artificial intelligence (AI) within their organisations.
Overview
As the importance of AI continues to rise in today's digital landscape, professionals are seeking to equip themselves with the necessary skills and knowledge to thrive in this rapidly evolving field. This certificate programme is designed to do just that. It covers a wide range of topics related to artificial intelligence (AI), including machine learning, data analytics, natural language processing, and computer vision. The programme offers participants a comprehensive understanding of AI's impact across industries, providing hands-on experience in AI application development alongside modules focusing on ethical considerations and governance to promote responsible utilisation of the technology. Upon completion, participants will be equipped to effectively utilise AI in their fields, fostering meaningful contributions to the digital economy, addressing the demand for AI professionals, and empowering individuals to stay competitive amidst technological shifts.
Topic/Structure
To achieve the Advanced Certificate in Artificial Intelligence in the Digital Economy, participants will need to complete the following modules offered by SMU Academy:
Module 1: Introduction to Artificial Intelligence in the Digital Economy
Module 2: Machine Learning and Data Analytics for Business Applications
Module 3: Natural Language Processing and Sentiment Analysis
Module 4: Computer Vision and Image Recognition Technologies
Module 5: Artificial Intelligence Ethics, Governance and Regulatory Compliance
Module 6: Implementing Artificial Intelligence Solutions in the Digital Economy
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 6 modules within 3 years in order to be awarded the digital Advanced Certificate in Artificial Intelligence in the Digital Economy 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+
|
$3,924 (After SSG Funding 70%) |
$1,524 (After SSG Funding 70% |
$3,924 (After SSG Funding 70%) |
|
Singapore Citizen ≥ 40 years old |
$1,524 (After SSG Funding 70% |
$1,524 (After SSG Funding 70% |
$1,524 (After SSG Funding 70% |
|
International Participant |
$13,080 (No Funding) |
$13,080 (No Funding) |
$13,080 (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: Introduction to Artificial Intelligence in the Digital Economy | 4 - 5 Aug 2025 [Open for Registration] |
| Module 2: Machine Learning and Data Analytics for Business Applications | 1- 2 Sep 2025 [Open for Registration] |
| Module 3: Natural Language Processing and Sentiment Analysis | 29 - 30 Sep 2025 [Open for Registration] |
| Module 4: Computer Vision and Image Recognition Technologies | 27 - 28 Oct 2025 [Open for Registration] |
| Module 5: Artificial Intelligence Ethics, Governance and Regulatory Compliance | 24 - 25 Nov 2025 [Open for Registration] |
| Module 6: Implementing Artificial Intelligence Solutions in the Digital Economy | 12 - 13 Jan 2026 [Open for Registration] |
*Online registration will close 5 calendar days before the course start date
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