Production, Deployment and Sustainment of Machine Learning Solutions

Date: 7 Jun, 8 Jun, 9 Jun 2023 | 9am-5.30pm | Classroom Learning

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)

ccccc Danny Poo

Assoc Prof Danny PooAssoc Prof Danny Poo

ddddd Lu Weiquan

Dr Lu WeiquanDr Lu Weiquan

Course Fees

Singapore Citizens
39 years old or younger
40 years old or older
Singapore PRs
Enhanced Training Support for SMEs
International Participants

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

Singapore Citizens

39 years old or younger

Singapore Citizen

40 years old or older
Singapore PRs
Enhanced Training Support for SMEs
International Participants