NICF- Text Analytics

Overview

Do you know how to analyse customer sentiments about your company, products and services? Or how to keep track of your company’s service & quality delivery so that you are able to act quickly to insights that drive your business?

About 80% of enterprise-relevant data is in unstructured or semi-structured format. These include emails, documents, surveys, feedback forms, warranty claims, contact-centre notes and transcripts, web pages, news, data from social media, audios, videos and many more. A predominant amount of such data is available as text.

In order to gain competitive edge in the market, businesses and organisations are finding a growing need to expand their analysis scope to cover text data, especially in regards to customer feedback and social media data. This is so that critical insights can be uncovered to support business decision making and process improvement.

This course aims to equip you with the knowledge and skills to effectively analyse large amounts of textual data such as customer feedback and social media conversations to discover themes, patterns and trends to aid in improving business process and decision making. In scenario-based case studies, you will be introduced to common text analytics tasks such as data pre-processing and preparation, linguistic/knowledge resources management, concept extraction, text categorisation, clustering, association and trend analysis. You will practise performing these tasks following a well-defined process in hands-on sessions.

This 3-day data mining course focuses on introducing the essential analytical skills in modelling unstructured textual data such as customer feedback, reviews or comments to business and IT professionals.

This course is part of the Analytics & Intelligent Systems Series offered by NUS-ISS.


Upcoming Classes

Class 1 07 Jan 2019 to 09 Jan 2019 ()

Duration: 3 days

When:
Jan:
07, 08, 09
Time:
9am - 5pm

Class 2 29 May 2019 to 31 May 2019 (Full Time)

Duration: 3 days

Time:
09:00am to 05:00pm

Class 3 17 Jul 2019 to 19 Jul 2019 (Full Time)

Duration: 3 days

Time:
09:00am to 05:00pm

Class 4 06 Nov 2019 to 08 Nov 2019 (Full Time)

Duration: 3 days

Time:
09:00am to 05:00pm

Class 5 03 Feb 2020 to 05 Feb 2020 (Full Time)

Duration: 3 days

Time:
09:00am to 05:00pm



Key Takeaways

At the end of the course, participants will be able to:

  • Identify main themes or topics in the collection of documents or textual data (e.g. the prominent issues customers are complaining about).
  • Discover relationships and patterns among topics (e.g. which issues tend to co-occur in complaints).
  • Categorise documents based on discovered topics and user-definable criteria, such as grouping complaints about similar issues for further investigation.
  • Perform sentiment analysis on customers’ comments, reviews, or other forms of opinions to gain a good sense about how customers feel about their company, products and services.
  • Extract useful information from text as structured data to enable integration into the traditional data mining process.
  • Incorporate business understanding and domain knowledge into the analysis through lexical and knowledge resources.
  • Perform the above tasks using the open-source language, R




Who Should Attend

This course is designed for both Business analytics and non-business analytics professionals. These include:

  • Business and IT professionals seeking analytical skills to handle large amounts of textual data (e.g. customer feedbacks, product reviews on social media, etc.) for insights to improve business process and decision making
  • Individuals who have no knowledge or experience in text analytics and would like to gain some knowledge in this area so that they may explore work opportunities in business analytics
  • Data analysts, business users and IT professionals who want to move from the structured data to large amounts of unstructured, text data

Pre-requisites

The course workshops will be conducted using R. Foundational knowledge in statistics at the level of "NICF - Statistics Bootcamp" is strongly recommended.



What Will Be Covered

  • Identify text analytics solution and platform requirements with IT team
  • Develop term-document frequency matrix to enable lookup of text and documents within the corpus
  • Define the metadata and corpus for the data to be imported into the text analytics repository
  • Develop a standardised set of text analytics artifacts with the relevant stakeholders
  • Modify the text analytics solution to ensure that it produces the expected results
  • Define the process to perform text analytics based on the business requirements and text analytics artifacts

Format

Lectures and workshops




Fees & Funding

Self-sponsored

International Participants

S'poreans and PRs 
(aged 21 and above)

SkillsFuture Mid-Career Enhanced Subsidy1 
(S’poreans aged 40 and above)

Workfare Training Support2
(S’poreans aged 35 and above, and earn ≤ $2,000 per month)

Full course fee

S$2700

S$2700

S$2700

S$2700

SSG grant

-

(S$1890)

(S$1890)

(S$1890)

Nett course fee

S$2700

S$810

S$810

S$810

7% GST on nett course fee

S$189

S$56.70

S$56.70

S$56.70

Total nett course fee payable, including GST

S$2889

S$866.70

S$866.70

S$866.70

Less additional funding if eligible under various schemes

-

-

(S$540)

(S$675)

Total nett course fee payable, including GST, after additional funding from the various funding schemes

S$2889

S$866.70

S$326.70

S$191.70


Singaporeans aged 25 and above can use their SkillsFuture Credit to pay for course fees, apart from government subsidies. For more information, click here.

Company-sponsored

International Participants

S'poreans and PRs 
(aged 21 and above)

SkillsFuture Mid-Career Enhanced Subsidy1 
(S’poreans aged 40 and above)

Workfare Training Support2
(S’poreans aged 35 and above, and earn ≤ $2,000 per month)

Enhanced Training Support for SMEs3

Notes

Full course fee

S$2700

S$2700

S$2700

S$2700

S$2700

SSG grant

-

(S$1890)

(S$1890)

(S$1890)

(S$1890)

Nett course fee

S$2700

S$810

S$810

S$810

S$810

7% GST on nett course fee

S$189

S$56.70

S$56.70

S$56.70

S$56.70

Total nett course fee payable, including GST

S$2889

S$866.70

S$866.70

S$866.70

S$866.70

Fee payable to NUS-ISS

Less additional funding if eligible under various schemes#
(company needs to submit training grant and claim via Skillsconnect)

-

-

(S$540)

(S$675)

(S$540)

Total nett course fee payable, including GST, after additional funding from the various funding schemes

-

-

S$326.70

S$191.70

S$326.70

Actual financial outlay by company

Various Funding Schemes

1Mid-Career Enhanced Subsidy

  • Singaporeans aged 40 and above may enjoy subsidies up to 90% of the course fees.


2
Workfare Training Support (WTS)

  • Singaporeans aged 35 and above (13 years and above for Persons With Disabilities) and earn not more than $2,000 per month, may enjoy subsidies up to 95% of the course fees.


3
Enhanced Training Support for SMEs (ETSS)

  • SME-sponsored employees (Singaporean Citizens and PRs) may enjoy subsidies up to 90% of the course fees. For more details, click on Enhanced Training Support for SMEs.


Course attendee is eligible for only one funding scheme.

#For company-sponsored participants, companies would need to pay upfront 30% of the course fee to NUS-ISS and submit a training grant application for the remaining eligible subsidies, and subsequently a claim in Skillsconnect. For details, please refer to Skillsconnect guide 4.1 & 5.1.

This course is aligned to the National Infocomm Competency Framework (NICF) and accredited by SSG. Absentee payroll and up to 70% SSG funding of the course fee is available for eligible participants (Singapore Citizens and Permanent Residents). Absentee payroll subsidy is available for eligible companies and companies on a short work week system will receive the absentee payroll subsidy based on their employees' current income. Please visit www.ssg.gov.sg for full details.




Certificate

Certificate of Completion

The ISS Certificate of Completion will be issued to participants who have attended at least 75% of the course.

WSQ Assessment

  • Broad Schedule of Assessment: During the course
  • Passing Criteria: Generally achieve above 50% for quizzes and achieve objectives in the workshops
  • Assessment Method: Workshops and open book quiz

Upon passing the assessment, Statement of Attainment (SOAs) will be issued to certify that the participant has passed the following Competency Units:

  • IT-TA-401S-1 Develop text analytics process

Participants may need to attend additional coaching sessions and re-assessments if they do not pass the required competency units. ISS reserves the right not to disclose any information on the course assessment process.




Preparing for Your Course

NUS-ISS Course Registration Terms and Conditions

Find out more.

NUS-ISS and Learner’s Commitment and Responsibilities

Find out more.

WIFI Access

WIFI access will be made available. User ID and password will be provided in the participant’s kit.

Venue

Institute of Systems Science, NUS
25 Heng Mui Keng Terrace
Singapore 119615 

Click here for directions to NUS-ISS.

In the event of a change of venue, participants are advised to refer to the acceptance email sent one week prior to the commencement date.

Course Confirmation

All classes are subject to confirmation and ISS will send an acceptance email to participants one week prior to the commencement date. Confirmed registrants are to attend and complete all lectures, class exercises, workshops and assessments (where applicable). Additionally, all responses to feedbacks and surveys conducted by ISS and its partners must be submitted. All training and assessments will be delivered as described in the course webpage.

General Enquiry

Please feel free to write to isstraining@nus.edu.sg or call 6516 2093 if you have any enquiry or feedback.




Instructors

Mr. Cai Yuhao

Associate Lecturer & Consultant, Analytics & Intelligent Systems Practice View Profile >

Ms. FAN Zhen Zhen

Senior Lecturer & Consultant, Analytics & Intelligent Systems Practice View Profile >

Dr. LEONG Mun Kew

Director, Graduate Programmes View Profile >

Course Resources

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