Advanced Certificate in Business Analytics for Data-Driven Decision Making (with Python) Module 5: Natural Language Processing Customer/ Employee Reviews
- Analytics & Tech
- Innovation & Business Improvement
This programme is conducted online.
3 days
Weeknights (7pm - 10:30pm)
Saturday (9am - 6pm)
Who Should Attend
Executives, managers, and working professionals who wish to learn how to link, bridge, and translate Python programming of business analytics to the solving of problems in marketing, HR, finance, and policy.
PREREQUISITES
- 1 year of working experience preferred
- Basic experience in Python programming (does NOT necessarily need to complete any certification, diploma, or degree programs beforehand)
Overview
In this module, participants will learn how to deal with such text data, with a particular focus on customer and employee reviews. The module will provide lessons on pre-processing text data, natural language features, and feeding features developed from text mining into modelling processes. Participants will run sentiment analysis and execute unsupervised learning on text data with topic modelling to discover hidden clusters within them.
This module is part of a sequential programme and is not available on a standalone basis.
Learning Objectives
- Extract natural language features from text data
- Implement sentiment analysis
- Run text classification
- Execute topic modeling
Topic/Structure
- Types of Natural Language Features
- Sentiment Analysis
- Use Machine Learning algorithms for Text Classification
- Topic Modeling
- Structural Topic Model (STM)
- Applying Topic Models to Employee Reviews
- Applying Topic Models to Customer Reviews
Assessment
- Group Assignment
Participants are required to attain a minimum of 75% attendance and pass the associated assessment in order to receive a digital Certificate of Completion issued by Singapore Management University.
Calculate Programme Fee
Fee Table
| COMPANY-SPONSORED | |||
|
PARTICIPANT PROFILE |
SELF-SPONSORED |
SME |
NON-SME |
|
Singapore Citizen < 40 years old Permanent Resident LTVP+
|
$654 (After SSG Funding 70%) |
$254 (After SSG Funding 70% |
$654 (After SSG Funding 70%) |
|
Singapore Citizen ≥ 40 years old |
$254 (After SSG Funding 70% |
$254 (After SSG Funding 70% |
$254 (After SSG Funding 70% |
|
International Participant |
$2,180 (No Funding) |
$2,180 (No Funding) |
$2,180 (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 5: 17, 18 & 20 Jul 2024 [Registration Closed]
Intake 6: 27, 28 & 30 Nov 2024 [Open for Registration]
This module is part of a sequential programme and is not available on a standalone basis.
