Professional Certificate in Applied Machine Learning


Business Intelligentisation Using Machine Learning and Rapidminer: 20 Apr, 21 Apr 2023 | 9am-5.30pm | Online
Python Programming:
19 May, 22 May, 24 May 2023 | 9am-5.30pm | Online
Applied Machine Learning: 22 Jun, 23 Jun 2023 | 9am – 5.30pm | Online

Duration: 7 Days

Course Objectives

This PC will equip learners with the following competencies:

  • Understanding a wide spectrum of ML algorithms, their parameters, and their applications.
  • Knowing how to use Rapidminer to implement ML algorithms.
  • Understand how to develop machine learning models and how to evaluate them.
  • Gathering basic and machine learning Python programming skills.
  • Practicing how to represent the machine learning results using Rapidminer visualization facilities.
  • Understanding different machine learning approaches and how to implement them.

Job Role Readiness

It will prepare learners in the following job roles to perform their responsibilities more effectively/ It will prepare learners for the following job roles:

  • ICT engineers and technicians
  • ICT executives
  • Data analysts / business analysts
  • Advisors and data service providers

Who Should Attend

Mid-career PMETs looking to pivot into roles requiring machine learning competencies.


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 Ai Xin

Dr Ai XinDr Ai Xin

ddddd Amirhassan Monajemi

Dr Amirhassan MonajemiDr Amirhassan Monajemi

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

Python Programming Course Code: TGS – 2022011018 (Classroom Learning) / TGS – 2022011046 (Synchronous e-learning)

Applied Machine Learning Course Code: TGS-2020504368 (Classroom Learning) / TGS-2020504368 (Synchronous e-learning)

Business Intelligentisation Using Machine Learning and Rapidminer Course Code: TGS-2022011495 (Classroom Learning) / TGS-2022011576 (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.