Applied Machine Learning

Dates: 27 Nov, 28 Nov 2023 | 9am – 5.30pm | Online

Duration: 2 Days

Course Overview

This course will introduce participants to machine learning, focusing more on the practical and applied aspects rather than theory. The course will discuss machine learning concepts, and briefly introduce Python, PyCharm environment, Scikit-learn, Numpy, Anaconda, and Keras toolkits.

Regression as a basic machine learning method will be discussed and practised. Different models and examples of regression will be reviewed. Support Vector Machines (SVM) along with their applications in function estimation and classification will also be introduced. We will also discuss artificial neural networks and introduce deep learning. 

Participants will learn how to implement machine learning to solve real-life problems more productively and efficiently.

This course is part of Professional Certificate in Applied Machine Learning.

Course Objectives

At the end of this course, participants will be able to:

• Understand the way regression, support vector machines (SVM), and artificial neural networks (ANN) work
• Recognise the applications, advantages and disadvantages of regression, SVM, and ANN methods
• Design and implement basic regression, SVM-based, and ANN-based algorithms in clustering, classification, and function estimation applications

Who Should Attend

Data analysts, IT experts, Chief Technology Officers (CTOs), technical advisors and intermediate-level managers.


Basic AI knowledge and basic Python programming skills. Click to view the course detail of Python Programming.

Course Conveners

(Click their photos to view their short biographies)

ddddd Ai Xin

Dr Ai XinDr Ai Xin

ddddd Amirhassan Monajemi

Dr Amirhassan MonajemiDr Amirhassan Monajemi

ddddd Edmund Low

Dr Edmund LowDr Edmund Low

ddddd Manoranjan Dash

Dr Manoranjan DashDr Manoranjan Dash

What Our Participants Say

“This course really benefits me for my works. It provides many insights and information on the types of algorithms and how to apply them effectively. I really enjoyed this course.”
– Loh Yew Fatt

“Great course and the content is easily absorbed even for people with less expert knowledge.”
– Dang Thi Quynh Trang

“A good introduction to machine learning basics.”
– Teo Yu Fang Jennifer

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.

This course is eligible for Union Training Assistance Programme (UTAP).
NTUC members can enjoy up to 50% funding (capped at $250 per year) under UTAP. Please click here for more information.

To enquire, email

To register, click Register

Course Codes
TGS-2020506040 (Classroom)
TGS-2020504368 (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

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