Business Intelligentization Using
Machine Learning and Rapidminer

Date: 20 Apr, 21 Apr 2023 | 9am-5.30pm | Online

Duration: 2 Days

Course Overview

Machine Learning (ML) operates on the basis of algorithms that enable computers to learn, mostly from data. ML algorithms attempt to be trained directly by data samples without relying vastly on a predetermined design and coding. ML systems can also adapt to the new situation and enhance their performance over the time. The course will introduce some of the algorithms in the field of ML, such as neural networks, deep learning, support vector machines, K nearest neighbours, and c-means clustering to name but a few. Rapidminer is a popular data mining and machine learning software platform that provides an integrated environment for realization of almost all known machine learning algorithms, and is accessible to the public as a free desktop application. Organisations can leverage on Rapidminer for many real-world ML applications including data preparation, results visualisation, model validation and optimisation.

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

Course Objectives

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

  • Understand a wide spectrum of ML algorithms, their parameters, and applications
  • Know how to use Rapidminer to implement ML algorithms
  • Understand how to develop machine learning models and how to evaluate them
  • How to represent the machine learning results using Rapidminer visualization facilities

Who Should Attend

Machine Learning Developers, Python Developers


Basic AI and Machine Learning knowledge

Course Convener

(Click their photos to view their short biographies)

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

Course Code:
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.

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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