Professional Certificate in Machine Learning for Business

Introduction to Rapidminer:
13 Oct
2023 | 9am-5.30pm | Online

Business Applications Relying on Supervised Learning:
30 Oct, 31 Oct 2023 | 9am – 5.30pm | Classroom Learning

Business Applications Relying on Unsupervised & Reinforcement Learning:
29 Nov, 30 Nov, 1 Dec 2023 | 9am – 5.30pm | Classroom Learning

Duration: 6 Days

Course Objectives

This Professional Certificate will equip learners with the following competencies:

  • Design and implement machine learning systems using RapidMiner and to evaluate and test these systems.
  • Obtain in-depth knowledge on machine learning techniques, including supervised learning, unsupervised learning and reinforcement learning.
  • Apply machine learning techniques to solve real-life business problems.

Job Role Readiness

This Professional Certificate will prepare learners in the following job roles to perform their responsibilities more effectively:

  • Data Analysts
  • Business Analysts

Who Should Attend

The PC is designed to meet the needs of:

  • Executives, Developers, Designers and Managers in Information Technology related fields, business development, strategic planning and operations or roles that require solving data-related problems


At least a polytechnic diploma

Course Conveners

(Click their photos to view their short biographies)

ddddd Amirhassan Monajemi

Dr Amirhassan MonajemiDr Amirhassan Monajemi

ddddd Natarajan Prabhu

Dr Natarajan PrabhuDr Natarajan Prabhu

eeeee Mario Favaits

Mr Mario FavaitsMr Mario Favaits

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 Codes
Introduction to Rapidminer: TGS- TGS-2022012249 (Classroom Learning) / TGS-2022012285 (Synchronous e-learning)
Business Applications relying on Supervised Learning: TGS-2022015670 (Classroom Learning) / TGS-2022016044 (Synchronous e-learning)
Business Applications relying on Unsupervised & Reinforcement Learning: TGS-2022015668 (Classroom Learning) / TGS-2022015677 (Synchronous e-learning)