Professional Certificate in Machine Learning (Python): Module 5 - Practical Concepts in Supervised Machine Learning (Synchronous e-learning)
- Analytics & Tech
- Artificial Intelligence
- Innovation & Business Improvement
This programme is conducted online.
3 days
Weeknights (7pm - 10.30pm)
Saturdays (9am - 6pm)
Who Should Attend
- Data science professionals
- Professionals interested in data science programming, machine learning and artificial intelligence
- Managers looking into costs and performance hurdles in predictive modelling
PREREQUISITES
- Diploma with at least 3 years of working experience and/ or start-up experience
- Basic programming knowledge is recommended to enrol for this programme
SYSTEM REQUIREMENTS
- Functional Laptop: (1) CPU must be of at least intel core I3, (2) GPU must have an integrated graphics card and (3) RAM must be of at least 4GB
Overview
'Supervised' refers to the fact that each sample within the data being used to build the system contains an associated label. The goal is to build a model that can accurately predict the value of the label when presented with new data. Participants will also learn how to choose an appropriate model and about the general trade-off between model accuracy and interpretability.
This module is not available on a standalone basis.
Learning Objectives
- Get introduced to supervised learning processes and algorithms
- Implement classification models including logistic regression, decision trees and K-Nearest Neighbours with SKLearn
- Evaluate model fit using loss functions such as Area Under (ROC) Curve, absolute error, root mean squared error
Topic/Structure
- Fundamentals of Supervised Learning with SKLearn
- Classification and Predictive Algorithms
- Logistic Regression
- Decision and Regression Trees
- KNN Algorithm
- Feature Selection and Engineering
- Model Explainability
- Model Fit and Metric Evaluation
Assessment
- Classroom exercises
- Group assignments
Individual assignment
CERTIFICATION
Upon meeting the attendance and assessment criteria, participants will be awarded a digital certificate for participating in each module. Please refer to our course policies to view the attendance and assessment criteria.
Upon completion of all modules required for this programme within a maximum duration of 3 years, participants will be awarded a digital certificate.
Calculate Programme Fee
Fee Table
| COMPANY-SPONSORED | |||
|
PARTICIPANT PROFILE |
SELF-SPONSORED |
SME |
NON-SME |
|
Singapore Citizen < 40 years old Permanent Resident LTVP+
|
$523.20 (After SSG Funding 70%) |
$203.20 (After SSG Funding 70% |
$523.20 (After SSG Funding 70%) |
|
Singapore Citizen ≥ 40 years old |
$203.20 (After SSG Funding 70% |
$203.20 (After SSG Funding 70% |
$203.20 (After SSG Funding 70% |
|
International Participant |
$1,744 (No Funding) |
$1,744 (No Funding) |
$1,744 (No Funding) |
All prices include 9% GST
Post Secondary Education Account (PSEA)
PSEA can be utilised for subsidised programmes eligible for SkillsFuture Credit support. Click here to find out more.
Self Sponsored
SkillsFuture Credit
Singapore Citizens aged 25 and above may use their SkillsFuture Credits to pay for the course fees. The credits may be used on top of existing course fee funding.
This is only applicable to self-sponsored participants. Application to utilise SkillsFuture Credits can be submitted when making payment for the course via the SMU Academy TMS Portal, and can only be made within 60 days of course start date.
Please click here for more information on the SkillsFuture Credit. For help in submitting an SFC claim, you may wish to refer to our step-by-step guide on claiming SkillsFuture Credits (Individual).Workfare Skills Support Scheme
From 1 July 2023, the Workfare Skills Support (WSS) scheme has been enhanced. Please click here for more details.
Company Sponsored
Enhanced Training Support for SMEs (ETSS)
- Organisation must be registered or incorporated in Singapore
- Employment size of not more than 200 or with annual sales turnover of not more than $100 million
- Trainees must be hired in accordance with the Employment Act and fully sponsored by their employers for the course
- Trainees must be Singapore Citizens or Singapore Permanent Residents
- Trainees must not be a full-time national serviceman
- Trainees will be able to enjoy ETSS funding only if the company's SME's status has been approved. To verify your SME's status, please click here.
Please click here for more information on ETSS.
Absentee Payroll
Companies who sponsor their employees for the course may apply for Absentee Payroll here. For more information, please refer to:
AP Guide (Non-SME Companies)
Declaration Guide (SME Companies)
Intake Information
Intake 22: 1, 3 & 5 Oct 2024 [Registration Closed]
Intake 23: 4, 6 & 8 Feb 2025 [Open for Registration]
