MSc in Industrial Automation & Machine Learning
Programme Details
Type of Programme
Post-graduate taught degree, face-to-face lessons.
Programme Duration
- Full time: 12 months
- Part-time: 24 months
Minimum Entry Requirements
- Second class lower (2.2) in relevant engineering, science or other relevant degree qualification.
- Candidates without a Bachelor Degree with at least 8 years of working experience and is at least 30 years old will also be considered on a case by case basis
- English Language Entry Requirements : IELTS overall 6.5 or equivalent
Application Fees per programme (non-refundable), subject to prevailing GST
- Singapore Citizens and/or Permanent Residents: SGD90
- Singapore Employment and/or Dependant's Pass Holders: SGD135
For more information on Fees & Funding, please refer to Fees & Funding AY2021/2022 (Singapore)
Applicant Eligibility
The course is only available to Singapore Citizens, Singapore Permanent Residents, Singapore Employment Pass holders, Singapore Dependant's Pass* holders.
*subject to approval by the respective pass-issuing authority.
Learning Outcomes
The programme aims to produce graduates who have developed well-grounded knowledge and skills in industrial automation and machine learning so that they are able to bridge gaps that exist while building cyber-physical systems.
A successful student will gain and be able to demonstrate:
- Readiness for the digital industrial revolution (Industry 4.0) and are readily employable.
- Bridging the gap in the industry that exists between Engineers who understand the physical systems and Data Scientists.
- Meeting the needs of the local industry and to enable the local work force to upskill and/or reskill so that they can make better decisions by analysing data for better business and technological decisions.
- Appropriate transferable and practical skills in computer programming, data collection and analysis, problem formulation and solving skills, project management and communication skills.
- Collaboration with fellow students via dissertation from other domains so as to carry out large inter-disciplinary projects by integrating individual components/modules.
Modules
The table below shows all the modules covered in the degree, all of which are core units of the programme.
| SN | Module Code | Module Title |
| 1 | NUS8301 | Industrial Control Systems |
| 2 | NUS8302 | Electro-Mechanical Systems and Systems Safety |
| 3 | NUS8303 | Embedded Systems and IIoT |
| 4 | NUS8304 | Programming for Automation |
| 5 | NUS8305 | Mathematical Foundations of Machine Learning |
| 6 | NUS8306 | Data Analytics using Machine Learning |
| 7 | NUS8307 | Project Dissertation – I |
| 8 | NUS8308 | Project Dissertation – II |