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.
Prerequisite
- At least a polytechnic diploma
- Basic Python programming knowledge
Course Convener
(Click photo to view biography)
Dr Ai Xin
Dr Ai Xin
Dr Ai Xin is currently a Lecturer with the School of Computing at the National University of Singapore (NUS). She has many years’ experience on teaching Artificial Intelligence and Data Science courses, e.g. machine learning, deep learning, data mining and etc.
She graduated from NUS with a PhD degree on Electrical and Computer Engineering. Her research focused on Game Theoretical Modelling, Optimization Methods, Algorithm Design and Wireless Networks.
She worked in BHP Billiton Marketing Asia for eight years and gained a lot of industry experience through different functions, e.g. risk management, supply chain management, sales and marketing planning and etc.
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
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 Codes
TGS-2022014568 (Classroom Learning)
TGS-2022014576 (Synchronous e-learning))
Course Fee Breakdown
Singapore Citizens
39 years old or youngerSingapore Citizen
40 years old or older