WSQ - Text Analytics with Python

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 (Q&A)
• Practical Performance

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

• Python
• Visual Studio Code
• Anacoda

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

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.

• 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.

Quah Chee Yong: Quah Chee Yong is a ACTA trainer. Chee Yong is an experienced professional who has held various Technical, Operations and Commercial positions across several industries A firm believer that AI can create a better world, he has equipped himself with the Knowledge and Skills in the fields of Data Science, Machine Learning, Deep Learning and Cloud Deployment He has a deep passion for training & facilitating and is currently a Singapore WSQ certified Adult Educator. He particularly enjoys the interactive engagements with his fellow trainers and learners.

Solomon Soh Zhe Hong: Solomon is ACTA certified and has trained and coached over 100 professionals in the area of data science, python programming and coding. Solomon is a Certified AI Engineer Associate by AI Singapore and holds certifications in Alibaba Cloud Architect and Alteryx respectively. Solomon interests include Reinforcement Learning, Natural Language Processing and Time-Series analysis.

Marcel Leng: Marcel Leng is a ACTA certified. Marcel graduated with majors in Applied Mathematics and Physics from the National University of Singapore.

His core specialisation skills are R, Python, Machine Learning, Statistical Analysis, and Data Visualisation in Tableau. His current interests include Machine Learning, Deep Learning, Artificial Intelligence, Internet of Things, Robotics and Programming.