- Getting a quick snapshot of the evolution of AI and IOT.
- Demystifying AI / IOT and familiarisation with associated terminology.
- Learning what are the business and societal implications of this technology.
- Preparing yourself for the future in which AI co-exists with humans.
- Harnessing the power of AI to do your job better and to propel your organisation forward.
Programme Code: CRS-N-0044319
|Admission Period||Before programme commencement date|
Before programme commencement date
|Areas of Study||
Internet of Things (IOT)
Artificial Intelligence (AI)
Machine Learning Technologies
|Exclusively Designed For||
|Schedule||INTAKE 2 > 2 Nov 2018 (9.00am – 6.00pm) - Confirmed to Commence|
1. An Introduction to Artificial Intelligence and Internet of Things
• Evolution of Key AI technologies
• IOT – What’s in a sensor and how did we get here?
• The relationship between AI and IOT
• Implications for businesses and for society
• Discussion: The angry truck driver
2. How businesses are using Machine Learning
• Core concepts of Machine Learning
• How computers can learn from experience
• Why this, why now?
• How Machine Learning can be successfully integrated into business functions
3. Processing human language
• How natural language processing is deployed in business contexts
• Machine translation and RNNs
• Case studies: Sentiment analysis
4. Computer Vision
• Applications of Computer Vision
• How robotics can benefit an organisation
• Why robots are not yet everywhere
• Discussion: The trolley experiment for Autonomous Vehicles
6. Al in Business and Society
• The human-machine relationship
• Game: Can a machine do your job?
• Ethical and social implications of AI integration
7. The Future of AI and IOT
• Imagining the future and potential uses in different industries
• What human skills will remain important
• Group work: Creating a roadmap for AI implementation for your organisation
|Related Topics||Innovation and Entrepreneurship, Law, Business, Social Sciences & Humanities, Strategy and Growth, Technology and Change, Management Insights|
Fee payable to SMU:
Fee payable to SMU after 70% SSG Funding
Fee payable to SMU after 70% SSG Funding & 20% SkillsFuture Mid-Career Enhanced Subsidy
Fee payable to SMU after 70% SSG Funding & 25% Workfare Training Support Scheme
Fee payable to SMU after 70% SSG Funding & 20% Enhanced Training Support for SMEs
* SMEs must meet all of the following criteria:
|Who Should Attend||
This programme is suitable for business professionals who are interested to learn more about AI and Machine Learning and how they could potentially use AI to help them do their jobs better or gain additional insights to business issues and opportunities.
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Last updated on 11 May 2018.
SMU Academy | Human Capital, Management & Leadership
Singapore Management University
School of Accountancy Building
60 Stamford Road, Level 6
Mr Tan Kim Guan /
Ms Caren Chiang /
Mr Damone Teo
+65 6828 1966 /
+65 6808 5361 /
+65 6828 0071