This module covers basic concepts in machine learning and the use of various open source libraries like scikit-learn, Tensorflow, and Keras to build basic machine learning application with Linear regression, K nearest neighbors, SVMs, decision trees and unsupervised learning.
Upon completing the module, you will be able to explain the essential principles of machine learning, with hands-on experience in building, validating and deploying machine learning models using Python.
Machine Learning Fundamentals is a module selected from the Specialist Diploma in Applied Artificial Intelligence. It enables you to acquire new skills or deepen relevant skills without the need to pursue a full specialist diploma. As this is a stackable course, you may choose to complete the remaining modules within the validity period, of 2 years, to be awarded the full Specialist Diploma qualification
Click here for more information on the Entry Requirements.
Fees for Jan 2023 intake
| Full Course Fees (with GST) |
Singapore Citizens aged 39 & below |
Singapore Citizens aged 40 & above |
Singapore PR |
SME-sponsored Singapore Citizens |
SME-sponsored Singapore PR |
| $741.51 |
$222.45 |
$74.15 |
$222.45 |
$83.85 |
$83.85 |
Fees for Apr to Oct 2023 intakes
| Full Course Fees (with GST) |
Singapore Citizens aged 39 & below |
Singapore Citizens aged 40 & above |
Singapore PR |
SME-sponsored Singapore Citizens |
SME-sponsored Singapore PR |
| $761.40 |
$222.45 |
$74.15 |
$228.42 |
$83.85 |
$87.42 |
Notes:
- Payment may be made using SkillsFuture Credit.
- Fees reflected are inclusive of Goods and Services Tax (GST). In line with the government fee freeze directive from 1 Jan to 31 Dec 2023, the fees in 2023 for Singapore Citizen will remain the same as 2022. RP will absorb the additional 1% GST for Singapore Citizen in 2023 only.
Republic Polytechnic reserves the right to make changes to the course fee and application closing dates without prior notice. The commencement of each course is subject to sufficient number of participants.
All information is accurate at time of publishing.