Date: TBA
Duration: 3 Days
Course Overview
Machine Learning Operations (MLOps) is a set of practices that aims to deploy and maintain Machine Learning (ML) models in production reliably and efficiently. It is about orchestrating the steps in the ML pipeline, then automating the execution of the pipeline for continuous training (CT) of the models. To iteratively and continuously cater to changing business needs, the Continuous Integration / Continuous Delivery (CI/CD) practices are adopted to create and implement new model pipelines. This course covers the construction, deployment, maintenance, and continuous delivery of new model pipelines. It provides practical hands-on interactions to understand the actual deployment considerations.
This module is part of Professional Certificate in Machine Learning Operations.
Course Objectives
This course will enable learners to:
- Understand the processes of MLOps from construction, deployment, maintenance, and continuous delivery of new model pipelines
- Learn the tools and techniques in MLOps
- Deploy and maintain ML models in production reliably and efficiently
Who Should Attend
- Data Engineers
- Data Analysts
- Software Engineers
- Any professionals involved in Machine Language lifecycle management
Prerequisite
At least a polytechnic diploma.
Course Conveners
(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:
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-> Advanced Computing for Exe (Faculty/Department / Unit)
Please download the user guide for NUS Online Application Portal after you click ‘Apply for Myself’ if you need assistance.
Course Fee Breakdown
Singapore Citizens
39 years old or youngerSingapore Citizen
40 years old or older