Machine Learning Solution Design

Date: 17 May, 18 May, 19 May 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. Machine Learning models are tested and developed in isolated experimental systems. MLOps is about orchestrating the steps in the ML pipeline, then automating the execution of the pipeline for continuous training (CT) of the models. This course provides a high-level understanding of the processes required in the creation of Machine Learning solutions and design. Practical hands-on interactions with the tools forms a part of the learning process.

This module is part of Professional Certificate in Machine Learning Operations.

Course Objectives

This course will enable learners to:

  • Understand and execute the processes of MLOps from ML solution design of new model pipelines
  • Understand ML lifecycle management
  • Learn the tools and techniques in MLOps

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-2022014568 (Classroom Learning)
TGS-2022014576 (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