Date: On Demand
Duration: 6 Days
Course Objectives
This Professional Certificate will equip learners with the following competencies:
- Understand Machine Learning Operations (MLOps) as a set of practices that aims to deploy and maintain Machine Learning (ML) models in production reliably and efficiently.
- Understand Machine Learning models are tested and developed in isolated experimental systems.
- Understand the MLOps steps in the ML pipeline to automate the execution of the pipeline for continuous training (CT) of the models.
- Learn how to iteratively and continuously cater to changing business needs, as the Continuous Integration / Continuous Delivery (CI/CD) practices are adopted to create and implement new model pipelines.
Job Role Readiness
This Professional Certificate will prepare learners in the following job roles to perform their responsibilities more effectively:
- Data Engineers
- Data Analysts
- Software Engineers
Who Should Attend
Any professionals involved in Machine Language lifecycle management.
Prerequisites
At least a polytechnic diploma
Course Convener
(Click their photos to view their short biographies)
Assoc Prof Danny Poo
Assoc Prof Danny Poo
Assoc Prof Danny Poo brings with him 35 years of Software Engineering and Information Technology and Management experience. A graduate from the University of Manchester Institute of Science and Technology (UMIST), England, Dr Poo is currently an Associate Professor at the Department of Information Systems and Analytics, National University of Singapore. Prior to joining the University, Dr Poo was with the System Operations at DBSBank, Singapore.
A Steering Committee member of the Asia-Pacific Software Engineering Conference, Dr Poo is actively involved in Information Management and Healthcare Analytics research. A well-known speaker in seminars, Dr Poo has conducted numerous in-house training and consultancy for organizations, both locally and regionally. Dr Poo is the author of 5 books on Object-Oriented Software Engineering, Java Programming language and Enterprise JavaBeans.
Dr Poo notable teaching credentials include:
- Data Strategy
- Data StoryTelling
- Data Visualisation
- Data Analytics
- Machine Learning
- Data Management
- Data Governance
- Data Architecture
- Capstone Projects for Business Analytics
- Software Engineering
- Server-side Systems Design and Development
- Information Technology Project Management
- Health Informatics
- Healthcare Analytics
- Health Informatics Leadership.
Industry Credentials
- Deutsche Bank
- Gemplus
- Micron
- NCR
- PIL
- PSA
- Rhode-Schwarz
- Standard Chartered Bank
- ST Electronic
- Monetary Authority of Singapore
- Infocomm Development Authority
- National Library Board
- Ministry of Manpower
- Nanyang Technological University
- Nanyang Polytechnic
- National University Hospital.
Dr Lu Weiquan
Dr Lu Weiquan
Dr Lu Weiquan is a Senior Lecturer at the School of Computing in NUS who examines the User Experience (UX) Design of technologically-empowered learning environments. He designs and utilizes experiential learning technology (such as simulations, Augmented and Virtual Reality) in the courses he teaches, and his education research interests include figuring out how all this technology tangibly and measurably affects human learning using Machine Learning and Artificial Intelligence. He also advises the government in the fields of UX design and experiential learning, and he develops Metaverse applications for industry clients. He holds a B.Comp. in Computing and a Ph.D. in Electrical and Computer Engineering from NUS.
Course Fees
Total Nett Programme Fee Payable, Including GST, after additional funding from the various funding schemes
Participants must fulfill at least 75% attendance and pass all assessment components to be eligible for SSG funding.
To enquire, email soc-ace@nus.edu.sg
To register, click Register
Course Code:
Machine Learning Solution Design: TGS-2022014568 (Classroom Learning) / TGS-2022014576 (Synchronous e-learning)
Production, Deployment and Sustainment of Machine Learning Solutions: TGS-2022014570 (Classroom Learning) / TGS-2022014574 (Synchronous e-learning)
For members of public and NUS Alumnus (without R&G Voucher), please follow the steps below:
Select Short Course / Modular Course -> Apply for Myself -> Browse Academic Modules / Short Courses-> Module/Course Category -> Short Courses -> Browse Courses-> Strategic Tech Mgt Institute (Faculty/Department / Unit)
Please download the user guide for NUS Online Application Portal after you click ‘Apply for Myself’ if you need assistance.