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  • WSQ - Python Text Mining and Analytics: Transforming Text into Insights

WSQ Text Analytics with Python

Course Information

  • Sessions 2 days
  • Duration 16 hrs
  • Level Beginner
  • Assessment 2 hrs

Venue

12 Woodlands Square #07-85/86/87 Woods Square Tower 1, Singapore 737715. 5 mins walk from Woodlands (NS9) MRT station.

The venue is disabled-friendly.

Skills Framework

TSC Title
Text Analytics and Processing
TSC Code
ICT-DIT-4029-1.1 TSC
Download Course Brochure

Certification

  • Certificate of Completion from Tertiary Courses - Upon meeting at least 75% attendance and passing the assessment(s), participants will receive a Certificate of Completion from Tertiary Courses.
  • OpenCerts from SkillsFuture Singapore - After passing the assessment(s) and achieving at least 75% attendance, participants will receive a OpenCert (aka Statement of Achievement) from SkillsFuture Singapore, certifying that they have achieved the Competency Standard(s) in the above Skills Framework.

WSQ - Python Text Mining and Analytics: Transforming Text into Insights

Course Code: TGS-2022014977
  • WSQ
  • SkillsFuture Credit
  • PSEA
  • UTAP
  • SFEC
  • Absentee Payroll
  • MCES

3 Review(s) | Add Your Review

What's This Course About

Immerse yourself in the world of text analytics with our WSQ-endorsed Text Analytics with Python course. This comprehensive program will cover essential techniques such as text mining, sentiment analysis, and natural language processing (NLP). Through hands-on exercises and real-world case studies, you'll learn how to use Python to analyze and interpret large sets of text data, deriving actionable insights that can be applied across industries.

By the completion of the course, you’ll possess a robust set of skills in text analytics, capable of leveraging Python's powerful libraries for tasks like sentiment analysis, topic modeling, and text classification. Ideal for professionals in data science, marketing, or any field requiring text analysis, this course equips you with the necessary tools to make data-informed decisions.

Course Outcomes

By the end of the course, learners will be able to 

    • LO1: Identify and develop text analytics solutions using Cross-Industry Standard Process for Data Mining (CRISP-DM).
    • LO2: Read in text corpus and perform text pre-processing using Python.
    • LO3: Perform text analytics and modify the data using Python with feature engineering.
    • LO4: Perform sentimental analysis using Python from social media data.
    • LO5: Perform sentiment summarization and visualization using Python.

    WSQ Funding

    Full Fee $720.00 Before GST
    GST $64.80 9% of fee
    Baseline Nett $424.80 SG/PR age 21+ · 50% funded
    MCES / SME Nett $280.80 SG age 40+ · 70% funded
    SkillsFuture Enterprise Credit (SFEC)

    Eligible Singapore-registered companies can tap on $10000 SFEC to cover up out-of-pocket expenses.Click here to submit SkillsFuture Enterprise Credit

    SkillsFuture Credit (SFC)

    Eligible Singapore Citizens can use their SFC to offset course fee payable after funding but the $4,000 Additional SFC (Mid-Career Support) cannot be used. Click here for SkillsFuture Credit submission

    UTAP

    Eligible NTUC members can apply for 50% of the unfunded fee from UTAP, capped up to $250/year and for members aged 40 and above, capped up to $500/year. Click here to submit UTAP

    PSEA

    Eligible Singapore Citizens can use their PSEA funds to offset course fee payable after funding.

    To check for Post-Secondary Education Account (PSEA) eligibility for this course, Visit SkillsFuture (course code: TGS-2022014977)
    • Scroll down to “Keyword Tags” to verify for PSEA eligibility.
    • If there is “PSEA” under keyword tags, the course is eligible for PSEA.

    Once you are eligible for PSEA, please download and fill up the PSEA Withdrawal Form and email to us. 

    Course FeeBefore Funding

    $720.00 (GST-exclusive)
    $784.80 (GST-inclusive)

    Course Date

    * Required Fields

    Additional Note

    Please bring your own laptop for hands-on training. If you don't have laptop, we can provide spare laptop for training use.

    Post-Course Support

    • We provide free consultation related to the subject matter after the course.
    • Please email your queries to enquiry@tertiaryinfotech.com and we will forward your queries to the subject matter experts.

    Cancellation & Reschedule Policy

    • You can register your interest without upfront payment. There is no penalty for withdrawal of the course before the class commences.
    • We reserve the right to cancel or re-schedule the course due to unforeseen circumstances. If the course is cancelled, we will refund 100% for any paid amount.
    • Note the venue of the training is subject to changes due to availability of the classroom.

    Course Details

    Course Details

    What You'll Learn

    Topic 1: Overview of Text Mining and Text Analytics

    • Introduction to Natural Language Processing (NLP)
    • Applications of Text Analytics and Text Mining for Business Intelligence
    • Cross-Industry Standard Process for Data Mining (CRISP-DM)

    Topic 2: Text Cleaning and Pre-processing

    • Install Python NLTK Package
    • Read In Text Corpus
    • Remove Punctuation and Stop Words
    • Pre-process Text using Tokenization, Stemming, Lemmatization
    • Vectorize Text using Term Frequency (TF) Vectorization, N-gram and Inverse-Document Frequency (TF-IDF)

    Topic 3: Text Analytics

    • Part of Speech (POS) Tagging
    • Name Entity Recognition (NER)
    • Text Link Analysis and Feature Engineering

    Topic 4: Sentimental Analysis

    • Overview of Machine Learning
    • Install Python Scikit Learn Package
    • Build a Machine Learning Model for Sentimental Analysis
    • Model Evaluation

    Topic 5: Text Summarization

    • Summarize Sentiment Analysis
    • Visualize Text Summarization

    Final Assessment

    • Written Assessment - Short Answer Questions (WA-SAQ)
    • Practical Performance (PP)

    Assessment

    • Written Exam
    • Practical Exam

    Course Info

    Promotion Code

    Promo or discount cannot be applied to WSQ courses

    Minimum Entry Requirement

    Knowledge and Skills

    • Able to operate using computer functions
    • Minimum 3 GCE ‘O’ Levels Passes including English or WPL Level 5 (Average of Reading, Listening, Speaking & Writing Scores)

    Attitude

    • Positive Learning Attitude
    • Enthusiastic Learner

    Experience

    • Minimum of 1 year of working experience.

    Minimum Software/Hardware Requirement

    Software:

    Download and Install the following software

    Sign up free Google Colab account

    Hardware: Window or Mac Laptops

    About Progressive Wage Model (PWM)

    The Progressive Wage Model (PWM) helps to increase wages of workers through upgrading skills and improving productivity. 

    Employers must ensure that their Singapore citizen and PR workers meet the PWM training requirements of attaining at least 1 Workforce Skills Qualification (WSQ) Statement of Attainment, out of the list of approved WSQ training modules.

    For more information on PWM, please visit MOM site.

    Funding Eligility Criteria

    Individual Sponsored Trainee Employer Sponsored Trainee
    • Singapore Citizens or Singapore Permanent Residents of age 21 and above
    • From 1 October 2023, attendance-taking for SkillsFuture Singapore's (SSG) funded courses must be done digitally via the Singpass App. This applies to both physical and synchronous e-learning courses.​
    • Trainee must pass all prescribed tests / assessments and attain 100% competency.
    • We reserves the right to claw back the funded amount from trainee if he/she did not meet the eligibility criteria.
    • Singapore Citizens or Singapore Permanent Residents who are DIRECT EMPLOYEE of the sponsoring company.
    • From 1 October 2023, attendance-taking for SkillsFuture Singapore's (SSG) funded courses must be done digitally via the Singpass App. This applies to both physical and synchronous e-learning courses.​
    • Trainee must pass all prescribed tests / assessments and attain 100% competency.
    • We reserves the right to claw back the funded amount from the employer if trainee did not meet the eligibility criteria.

     SkillsFuture Credit: 

    • Eligible Singapore Citizens can use their SkillsFuture Credit to offset course fee payable after funding.

     PSEA:

    • To check for Post-Secondary Education Account (PSEA) eligibility, goto mySkillsFuture portal and search for this course code.
    • Scroll down to "Keyword Tags" to verify for PSEA eligibility.
    • If there is “PSEA” under keyword tags, the course is eligible for PSEA.  
    • And if there is no “PSEA” under keyword tags, the course is ineligible for PSEA. 
    • Not all courses are eligible for PSEA funding.

     Absentee Payroll (AP) Funding: 

    • $4.50 per hour, capped at $100,000 per enterprise per calendar year.
    • AP funding will be computed based on the actual number of training hours attended by the trainee.

     SFEC:

    • If the Training Provider has submitted an enrolment for course fee grant claim in Training Partners Gateway (TPGateway), SSG would be able to derive SFEC funding based on this record. There is no need for enterprise to submit any claim request and the SFEC claim will be automatically generated and disbursed.
    • Where there is no such record, eligible employers are required to submit an SFEC claim after course completion via the SFEC microsite.
    • SkillsFuture Enterprise Credit (SFEC) Microsite 

    Steps to Apply Skills Future Claim

    • The staff will send you an invoice with the fee breakdown.
    • Login to the MySkillsFuture portal, select the course you’re enrolling on and enter the course date and schedule.
    • Enter the course fee payable by you (including GST) and enter the amount of credit to claim.
    • Upload your invoice and click ‘Submit’

    SkillsFuture Level-Up Program

    The  SkillsFuture Level-Up Programme provides greater structural support for mid-career Singaporeans aged 40 years and above to pursue a substantive skills reboot and stay relevant in a changing economy. For more information, visit SkillsFuture Level-Up Programme

    Get Additional Course Fee Support Up to $500 under UTAP

    The Union Training Assistance Programme (UTAP) is a training benefit provided to NTUC Union Members with an objective of encouraging them to upgrade with skills training. It is provided to minimize the training cost. If you are a NTUC Union Member then you can get 50% funding (capped at $500 per year) under Union Training Assistance Programme (UTAP).

    For more information visit NTUC U Portal – Union Training Assistance Program (UTAP)

    Steps to Apply UTAP

    • Log in to your U Portal account to submit your UTAP application upon completion of the course.

    Note

    • SSG subsidy is available for Singapore Citizens, Permanent Residents, and Corporates.
    • All Singaporeans aged 25 and above can use their SkillsFuture Credit to pay. For more details, visit www.skillsfuture.gov.sg/credit
    • An unfunded course fee can be claimed via SkillsFuture Credit or paid in cash.
    • UTAP funding for NTUC Union Members is capped at $250 for 39 years and below and at $500 for 40 years and above.
    • UTAP support amount will be paid to training provider first and claimed after end of class by learner.

    Appeal Process

    1. The candidate has the right to disagree with the assessment decision made by the assessor.
    2. When giving feedback to the candidate, the assessor must check with the candidate if he agrees with the assessment outcome.
    3. If the candidate agrees with the assessment outcome, the assessor & the candidate must sign the Assessment Summary Record.
    4. If the candidate disagrees with the assessment outcome, he/she should not sign in the Assessment Summary Record.
    5. If the candidate intends to appeal the decision, he/she should first discuss the matter with the assessor/assessment manager.
    6. If the candidate is still not satisfied with the decision, the candidate must notify the assessor of the decision to appeal. The assessor will reflect the candidate’s intention in the Feedback Section of the Assessment Summary Record.
    7. The assessor will notify the assessor manager about the candidate’s intention to lodge an appeal.
    8. The candidate must lodge the appeal within 7 days, giving reasons for appeal 
    9. The assessor can help the candidate with writing and lodging the appeal.
    10. he assessment manager will collect information from the candidate & assessor and give a final decision.
    11. A record of the appeal and any subsequent actions and findings will be made.
    12. An Assessment Appeal Panel will be formed to review and give a decision.
    13. The outcome of the appeal will be made known to the candidate within 2 weeks from the date the appeal was lodged.
    14. The decision of the Assessment Appeal Panel is final and no further appeal will be entertained.
    15. Please click the link below to fill up the Candidates Appeal Form.

    Job Roles

    Job Roles

    • Data Scientist
    • Natural Language Processing Engineer
    • Text Mining Specialist
    • Machine Learning Engineer (focused on text data)
    • Content Analyst
    • Big Data Analyst
    • Sentiment Analysis Specialist
    • Information Retrieval Engineer
    • Computational Linguist
    • Data Journalist (with coding skills)
    • SEO Specialist (using text analytics for insights)
    • Digital Marketing Analyst
    • Knowledge Engineer
    • Chatbot Developer
    • Content Recommendation System Developer.

    Review

    Customer Reviews (3)

    will recommend Review by Course Participant/Trainee
    1. Do you find the course meet your expectation?
    2. Do you find the trainer knowledgeable in this subject?
    3. How do you find the training environment
    Maybe more real-life examples will be good
    good session. Very good introduction on the capabilities of Python to do text analytics (Posted on 3/19/2023)
    will recommend Review by Course Participant/Trainee
    1. Do you find the course meet your expectation?
    2. Do you find the trainer knowledgeable in this subject?
    3. How do you find the training environment

    On behalf of my team, we would like to thank the school, and especially Marcel for the informative course we had. Having gone for many data related courses over the past 8 years, this is one, if not the most enjoyable and informative course I attended. This is especially so because Marcel was very knowledgeable in this area and could address many of the technical queries we had. The team was most impressed by this.

    (Posted on 11/8/2022)
    will recommend Review by Course Participant/Trainee
    1. Do you find the course meet your expectation?
    2. Do you find the trainer knowledgeable in this subject?
    3. How do you find the training environment
    Marcel is one of the most excellent and knowledgeable lecturers i have encountered. Your company would do well to hold on to him (Posted on 11/7/2022)

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