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WSQ - AI Vibe Coding for Data Analytics

Sessions 2 days
Duration 16 hrs
Level Beginner to Intermediate
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.

TSC Title: Analytics and Computational Modelling
TSC Code: ICT-DIT-3001-1.1

Funding for this course is valid from 15 Oct 2019 to 14 Oct 2027. Register and complete the course within this period to qualify for funding support.

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

LO1 - understand and apply machine learning concepts
LO2 - understand and apply classification methods
LO3 - understand and apply regression methods
LO4 - understand and apply clustering methods
LO5 - understand and apply PCA methods

Download Course Brochure

Certificate of Achievement from Tertiary Infotech Academy Pte Ltd - Upon meeting at least 75% attendance and passing the assessment(s), participants will receive a Certificate of Achievement from Tertiary Infotech Academy Pte Ltd.
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 - AI Vibe Coding for Data Analytics

Course Code: TGS-2019504643

WSQ
SFC
PSEA
UTAP
SFEC
Absentee Payroll
MCES

27 Review(s) | Add Your Review

This course equips participants with practical skills to use AI vibe coding and Python for data analytics. Learners will use natural-language instructions and AI coding assistants to generate, explain, test, debug, and refine Python code, making data analysis faster and more accessible without requiring them to write every line of code manually.

Participants will learn how to import, clean, transform, and organise data from common sources such as spreadsheets, CSV files, databases, and business reports. They will apply exploratory data analysis techniques to identify patterns, trends, relationships, anomalies, and performance gaps within datasets.

The course covers descriptive statistics, data aggregation, segmentation, correlation analysis, and effective data visualisation. Learners will use AI-assisted workflows to select suitable analytical methods, create charts and dashboards, interpret results, and communicate findings clearly to stakeholders. Introductory predictive techniques will also be explored to support forecasting and data-driven decision-making.

Through hands-on business projects, participants will develop end-to-end analytics workflows, from defining analytical questions and preparing data to producing visual reports and actionable recommendations. Emphasis is placed on validating AI-generated code, maintaining data quality, protecting sensitive information, and avoiding misleading interpretations.

By the end of the course, learners will be able to use AI vibe coding with Python to analyse datasets, automate repetitive analytical tasks, visualise findings, and transform raw data into meaningful business insights.

Full Fee $750.00 Before GST

GST $67.50 9% of fee

Baseline Nett $442.50 SG/PR age 21+ · 50% funded

MCES / SME Nett $292.50 SG age 40+ · 70% funded

SkillsFuture Enterprise Credit (SFEC)

Eligible Singapore-registered companies can tap on $10000 SFEC to cover out-of-pocket expenses.

View on SkillsFuture for Business

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.

Direct Application on SkillsFuture Portal

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.

Submit UTAP Claim

PSEA

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

Check PSEA Eligibility

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, then submit the completed form to us:

PSEA Withdrawal Form Submit PSEA Form

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

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.

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

Topic 1: AI Vibe Coding and Machine Learning Fundamentals for Data Analytics

Topic 2: Data Classification and Performance Evaluation

Topic 3: Regression Analysis and Predictive Modelling

Topic 4: Clustering and Customer or Data Segmentation

Topic 5: Principal Component Analysis and Dimensionality Reduction

Written Exam
Case Study
Oral Questioning

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 with minimum Computer Literacy Level 2 based on ICAS Computer Skills Assessment Framework
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 18 years old

Minimum Software/Hardware Requirement

Software:

You can download and install the following software:

Python

Hardware: Windows and 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 SWDA's (formerly 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 SWDA's (formerly 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), SWDA 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

Note

SWDA 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

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

Job Roles

Data Analyst
Business Analyst
Data Scientist
Business Intelligence Specialist
Reporting Analyst
Operations Analyst
Finance Analyst
Marketing Analyst
Data Engineer
Research Analyst
Data Visualization Specialist
Analytics Consultant
Product Manager (focused on data products)
Innovation Specialist
Business Owner or Manager working with data

Trainers

CY Quah is an ACLP-certified trainer and data science professional with extensive experience in Python, NLP, and machine learning. He has led AI training programs for SAP, Temasek Polytechnic, and IMDA under the SGUnited Mid-Career Pathways initiative, and has delivered corporate workshops on text analytics, recommender systems, and chatbot development. His expertise includes applying NLP tools such as NLTK, spaCy, and Gensim for sentiment analysis, topic modeling, and text classification.

Dr Alvin Ang holds a Ph.D. in Operations Research from NTU and has more than a decade of teaching and research experience in data science and machine learning. As a data science and AI trainer, he has taught courses at institutions such as NTU, SUSS, and Curtin University, as well as in professional settings with IBM and Tertiary Infotech. His expertise covers Python, scikit-learn, machine learning, and applied statistics, supported by numerous IBM certifications in data science and machine learning.
An ACLP-certified trainer, Dr Ang has trained professionals in Python programming, machine learning model development, and AI applications across industries. He emphasizes practical learning with AI vibe coding, guiding learners through data preprocessing, exploratory analysis, visualisation, and interpretation of results. His engaging and structured approach ensures learners gain both theoretical knowledge and the confidence to implement machine learning in real-world projects.

Solomon Soh is an accomplished data scientist and AI trainer with extensive experience in applying machine learning to natural language processing, computer vision, and optimization problems. At IBM Singapore, he supervised 24 machine and deep learning projects, coaching teams in feature engineering, data cleansing, and ensemble modeling. His work at Workforce Optimizer and Certis Cisco focused on predictive analytics, reinforcement learning, and operational optimization, where he successfully applied scikit-learn and other frameworks to real-world problems.
As a certified AI engineer and experienced trainer, Solomon has taught data science bootcamps and corporate workshops covering Python, AI-assisted coding, and applied data analytics. He emphasizes project-based learning, helping participants gain practical experience in model development, from regression and classification to clustering and optimization. His teaching style blends technical rigor with clear communication, ensuring learners can effectively apply machine learning techniques to diverse business and research challenges.

Terence Ee is an experienced IT leader and consultant with more than 25 years of expertise in technology management, information systems, and digital transformation. He has served as Chief Information Officer at the Supreme Court of Singapore and Vice President of Information Systems at Senoko Energy, where he led major IT modernization projects. Since 2017, he has worked as an independent consultant and ACLP-certified trainer, specializing in guiding SMEs and enterprises in adopting future-ready digital platforms. As a WSQ-accredited trainer, Terence delivers programs in digital collaboration, IT governance, and productivity tools. His facilitation emphasizes case studies, simulations, and hands-on practice, enabling learners to apply modern IT systems such as Microsoft 365 and Google Workspace to improve collaboration and business efficiency. With his leadership background and deep IT expertise, Terence prepares learners to thrive in digitally transforming environments.

Truman Ng is an ACTA-certified trainer and PMP-certified project manager with extensive experience in IT, networking, and applied data science. He has conducted training in machine learning, Python programming, and cybersecurity, with a focus on practical applications. His expertise includes using scikit-learn, TensorFlow, and related frameworks to teach supervised and unsupervised learning, covering areas such as classification, clustering, and regression.
With a strong background in enterprise systems and certifications across Cisco, Huawei, and cloud platforms, Truman blends technical depth with practical training delivery. He has trained professionals in applying AI vibe coding for data analytics, ensuring they understand not only the tools but also data preparation, quality checks, and visual reporting. His structured and hands-on teaching style empowers learners to confidently apply machine learning to solve business and technical challenges

Review

Customer Reviews (27)

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

If there were less than 3 people signing up, instead of cancelling the class, can consider doing one-to-one virtual lessons

Trainer is dedicated despite I'm the only one who signed up. (Posted on 5/21/2020)

Excellent trainer 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

I am actually the only person who signed up for the course for the May 20/21.
Trainer Mr Truman was very dedicated to teaching, I am very grateful that the class was not cancelled. (Posted on 5/21/2020)

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

More notes and some further coaching on the python codes (Posted on 5/4/2020)

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

The Trainer Mr Truman Ng is very patient, helpful and polite. This is very important for older students like me who needs more help to cope with the course. (Posted on 4/8/2020)

Trainer is good. He makes sure we understand Review by Course Participant/Trainee