Machine Learning Solution Design

Dates: To be advised 
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 course 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.


  • At least a polytechnic diploma
  • Basic Python programming knowledge

Course Convener

(Click photo to view biography)

ddddd Ai Xin

Dr Ai XinDr Ai Xin

What Our Participants Say

“The course is well-structured to understand how machine learning models work in details. The professor explained the concepts clearly.”
– Ho Gui Ying

“This course is quite in-depth in the logic behind machine learning algorithms, where the professor is quite detailed and clear in her explanations, making it easy for people to understand. It would be advisable for those who have some knowledge as it can be tough for those with zero knowledge in coding and data science.”
– Lim Jiahui

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

To register, click Register

Course Codes
TGS-2022014568 (Classroom Learning)
TGS-2022014576 (Synchronous e-learning))

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