Data-Driven Decisions Without Code: Analytics and Machine Learning with RapidMiner

Short Course

Data-Driven Decisions Without Code: Analytics and Machine Learning with RapidMiner

Course Schedule	Duration (days)	Mode of Delivery	TGS Reference Number
To be advised	2	Classroom Learning	TGS-2026065956

Course Overview

Organisations today increasingly rely on data to improve decision-making, optimise operations, identify trends, and gain a competitive advantage. At the same time, modern analytics and machine learning tools are becoming more accessible to non-technical professionals through visual no-code platforms. This course introduces participants to practical data analytics and machine learning concepts using RapidMiner, without requiring any programming background. Designed for adult learners and working professionals, the course focuses on developing practical understanding and hands-on experience in building analytics workflows through RapidMiner’s intuitive drag-and-drop environment. Participants will learn how data can be prepared, explored, visualised, and analysed to support data-driven decision making across a variety of business and organisational contexts. The course covers fundamental concepts in data analytics and machine learning, including data preparation, classification, prediction, clustering, and model evaluation. Through guided demonstrations and practical exercises, participants will develop simple machine learning workflows and learn how analytical models can be applied to real-world problems such as customer segmentation, sales forecasting, employee attrition analysis, and customer churn prediction. In addition to technical workflows, the course also discusses the opportunities, limitations, and ethical considerations associated with AI-driven analytics, including data quality, bias, interpretability, and responsible use of AI technologies. Several coursework and hands-on will help learners to experience decision-making based on data, using machine learning.

Course Objectives

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

Understand the fundamentals of data analytics and machine learning and explain how they support data-driven decision making in modern organisations.
Identify different types of analytical and machine learning tasks including classification, prediction, clustering, and trend analysis.
Prepare and preprocess datasets for analysis by handling missing values, cleaning data, and selecting relevant features.
Design no-code analytics workflows using RapidMiner through visual drag-and-drop processes and workflow-based analytics techniques.
Develop basic machine learning models without programming using common techniques such as decision trees, regression, and clustering.
Visualise, interpret, and communicate analytical results to support business insights and decision making.
Evaluate the performance of machine learning models using practical validation and performance measurement techniques.
Learn how to use RapidMiner for data analytics and machine learning.
Apply practical analytics and machine learning techniques to real-world business scenarios through guided hands-on exercises and case-based activities.

Prerequisites

A diploma or above
Basic computing skills (e.g. how to use Excel)

Enquire

Funding Available

SWDA Funding

Enhanced Training Support

SkillsFuture Credit

SFEC

Instructors

Dr Amirhassan Monajemi

Course Fees

	Singapore Citizens		Singapore PRs	Enhanced Training Support for SMEs	International Participants
	39 years old or younger	40 years old or older	Singapore PRs	Enhanced Training Support for SMEs	International Participants
Full Course Fee	S$1,700.00	S$1,700.00	S$1,700.00	S$1,700.00	S$1,700.00
Less: SWDA Grant Amount	S$1,190.00	S$1,190.00	S$1,190.00	S$1,190.00	-
Nett Course Fee	S$510.00	S$510.00	S$510.00	S$510.00	S$1,700.00
9% GST on Nett Course Fee	S$45.90	S$45.90	S$45.90	S$45.90	S$153.00
Total Nett Course Fee Payable, including GST	S$555.90	S$555.90	S$555.90	S$555.90	S$1,853.00
Less Additional Funding	-	S$340.00	-	S$340.00	-
Total Nett Course Fee Payable, including GST, after additional funding from the various funding schemes	S$555.90	S$215.90	S$555.90	S$215.90	S$1,853.00

Total nett course fee payable, including GST, after additional funding from various funding schemes.
Participants must fulfill at least 70% attendance and pass all assessment components to be eligible for SWDA funding.
The applicable funding is for Singaporeans and Singapore PRs. This is subject to change and in accordance with SWDA funding guidelines as of course commencement.
Please refer to our Terms and Conditions page for more information.

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