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Customer Feedback Analysis – A Natural Language Processing Approach

Topic:Data Analytics & Visualisation

Course Type:Short & Modular Courses, SkillsFuture Series - Digital Economy

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Overview

  • Course Date:

    23 Mar 2023 to 24 Mar 2023
  • Registration Period:

    01 Dec 2022 to 02 Mar 2023
  • Time:

    09:00 AM to 06:00 PM,
    16 hours / 2 Days
  • Mode of Training:

    Facilitated Learning (F2F)
  • Venue:

    Singapore Polytechnic
  • Funding:

    Eligible for SkillsFuture Credit

*Please note that once the maximum class size is reached, the online registration will be closed. You may register your interest, and would be notified if there is a new run.

Course Objective

Customer feedback serves as important sources of information for the businesses and organisations to reassess, re-plan and refine their products and services. 

The proposed course aims to impart essential ideas, concepts and skillsets in Natural Language Processing with an aim to applying these skills to analyse customer feedback data.



In this course, participants will learn to apply Natural Language Processing (NLP) techniques and tools in Python to derive useful insights from text-based customer feedback data. They will learn basic text pre-processing and apply this to recognize patterns in customer reviews and derive actionable insights through sentiment analysis and text summarization. The participants will also have the opportunity to apply the skillsets to a real data set, through a mini-project, towards the end of the course.

Course Outline

By the end of the course, participants will be able to: 
• Apply NLP techniques such as n-gram analysis, text visualisation using word cloud, and topic-modelling to identify key topics and derive hidden patterns from customer reviews
• Apply sentiment analysis and text summarisation to extract actionable insights from customer reviews

Topics to be covered

1. Introduction to Customer Feedback Analysis with NLP
2. Basics of NLP – Text Pre-processing with Python
3. Recognizing Patterns in Customer Reviews
4. Actionable Insights through Sentiment Analysis and Text Summarization

Minimum Requirements

Basic knowledge about statistics and programming

Certification / Accreditation

• Certificate of Attendance (electronic Certificate will be issued)
A Certificate of Attendance will be awarded to participants who meet at least 75% attendance rate

• Certificate of Performance (electronic Certificate will be issued)
A Certificate of Performance will be awarded to participants who pass the examination and meet at least 75% attendance rate

Suitable for

Data Analyst / Associate Data Engineer / Business Intelligence Manager / Business Intelligence Director

Course Fees

Full Fees (before GST): $670.00

Applicants/Eligibility SkillsFuture Funding GST* Subsidised Fee (after GST)
Singapore Citizens aged 40 and above¹ $603.00 $16.08 $83.08
Singapore Citizens aged below 40 $469.00 $16.08 $217.08
Singapore Permanent Residents and LTVP+ Holders $469.00 $16.08 $217.08
SME-sponsored Singapore Citizens, Permanent Residents and LTVP+ Holders² $603.00 $16.08 $83.08
Others (Full fees payable) $0.00 $53.60 $723.60

*As announced at Budget 2022, there will be no increase in government fees and charges for Singaporeans from 1 Jan 2023 to 31 Dec 2023. Also, as per SSG’s policy, the GST payable for all funding-eligible applicants is calculated based on prevailing GST rate after baseline funding subsidy of 70%

Singaporeans aged 25 years and above may use **SkillsFuture Credit balance to offset respective course fees.

¹ Under the SkillsFuture Mid-career Enhanced Subsidy. For more information, visit the SkillsFuture website here
² Under the Enhanced Training Support for Small & Medium Enterprises (SMEs) Scheme. For more information of the scheme, click here. To view SP’s list of similar funded courses, click here. Please submit the attached “Declaration Form for Enhanced Training Support Scheme for SME” together with your online application.


Funding Incentives

Please click here for more information on funding incentives.


Application Procedure

1. All applications must be made via Online Registration at www.pace.sp.edu.sg
Course fees can be paid by the following payment modes:

a) Credit Cards, Internet Banking, NETS (Not Applicable for company sponsored)
For e-payment using Visa/Master cards and Internet Banking, please click on the ‘Make e-Payment’ button on the acknowledgement page to proceed.

b) For NETS payment, you can pay at:
Singapore Polytechnic
One-Stop Service Centre

c) For payment via PayNow, please enter the UEN No. T08GB0056ACET and indicate the invoice/registration number. 

*With effect from 1 August 2021, cheque payment will not be available.

2. All successful applicants will be notified with a letter of confirmation via email.
 

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