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WSQ - Data Analytics and Visualization with Python

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.

TSC Title: Research Data Analysis
TSC Code: SSC-DAT-4013-1.1

Funding for this course is valid from 26 Jun 2020 to 25 Jun 2027. Register and complete the course within this period to qualify for funding support.

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 - Data Analytics and Visualization with Python

Course Code: TGS-2020504082

WSQ
SFC
PSEA
UTAP
SFEC
Absentee Payroll
MCES

102 Review(s) | Add Your Review

Expand your knowledge in data analytics and visualization with our WSQ-endorsed course focused on Python. Dive into key topics like data manipulation, statistical analysis, and visualization techniques using Python's powerful libraries. Through practical exercises and real-world examples, you'll learn to transform raw data into actionable insights and visual narratives that are compelling and easy to understand.

By the end of this course, you'll be adept at leveraging Python for advanced data analytics and visualization tasks. Whether you're a data scientist, business analyst, or someone interested in generating insights from data, this course will provide you with the tools and skills to make impactful, data-driven decisions.

Course Objective

Learners will be able to prepare data, perform data analysis and data visualization to gain insights into data.

Course Learning Outcomes

After the end of this WSQ Python course, learners will be able to :

LO1: Prepare data for analysis
LO2: Transform data for analysis
LO3: Gain insights from data visualization
LO4: Perform statistical data analysis and time series analysis
LO5: Perform advanced data analysis to interpret results

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: Data Preparation

Data Analytics with Pandas
Pandas DataFrame and Series
Import and Export Data
Filter and Slice Data
Clean Data

Topic 2: Data Transformation

Join Data
Transform Data
Aggregate Data

Topic 3: Data Visualization

Data Visualization with Matplotlib and Seaborn
Visualize Statistical Relationships with Scatter Plot
Visualize Categorical Data with Bar Plot
Visualize Correlation with Pair Plot and Heatmap
Visualize Linear Relationships with Regression

Topic 4: Data Analysis

Statistical Data Analysis
Time Series Analysis

Topic 5: Advanced Data Analytics

Data Piping
Groupby and Apply Custom Functions
Linear Regression

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 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)
Basic Python prog language knowledge

Attitude

Positive Learning Attitude
Enthusiastic Learner

Experience

Minimum of 1 year of working experience.
Minimum 18 years old

Minimum Software/Hardware Requirement

Software:

Download and Install the following software

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 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 Scientist
Data Analyst
Business Intelligence Developer
Research Scientist
Machine Learning Engineer
Financial Analyst
Data Visualization Specialist
Marketing Analytics Specialist
Quantitative Researcher
Data Engineer
Bioinformatics Analyst
Operations Research Analyst
Economic Analyst
Predictive Modeler
Sports Analytics Specialist

Trainers

Dr Alvin Ang is an ACLP-certified trainer with a Ph.D. in Operations Research from Nanyang Technological University and over a decade of academic and industry experience. He has taught at NTU, SUSS, Curtin University, and as an IBM Data Science Instructor, specializing in Python, data analytics, machine learning, and data visualization. As the founder of DataFrens.sg, an open-source data science community, he actively contributes to promoting applied data science and analytics in Singapore.
In his training, Dr Ang focuses on equipping learners with practical skills in Python for data analysis and visualization, using libraries such as Pandas, Matplotlib, and Seaborn. His courses integrate real-world case studies, enabling participants to apply analytical methods to business and research problems. With his structured, learner-centered approach, he ensures learners gain confidence in turning data into actionable insights.

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.

is a results-driven data scientist and financial services professional with over two decades of experience in data analytics, visualization, and business intelligence. As a Senior Partner and Lead Data Scientist at Big Data Venture Capital, he has led consulting projects, curriculum development, and training operations for blue-chip firms, equipping professionals with practical skills in Microsoft Power BI, Python, and advanced data analytics. His expertise in data acquisition, cleaning, feature engineering, ETL, and visualization ensures that organizations can harness Power BI to transform raw data into actionable insights for strategic decision-making. In addition to his industry leadership, Mr. Peh is a certified adult educator with the WSQ Advanced Certificate in Learning and Performance (ACLP) and has delivered numerous Power BI and data science courses through NTUC LearningHub and other training providers. His ability to merge technical expertise with pedagogy has made him a trusted trainer, empowering professionals to build interactive dashboards, automate reporting workflows, and adopt data-driven cultures. With a unique blend of hands-on technical mastery and proven teaching experience, Mr. Peh has established himself as a credible authority in Power BI and business intelligence solutions

Solomon Soh is a data scientist and AI trainer with extensive experience in Python, data analytics, and visualization. At IBM Singapore, he supervised 24 machine learning and deep learning projects, coaching teams in feature engineering, data cleansing, and ensemble modeling. His professional background includes roles at Workforce Optimizer and Certis Cisco, where he applied predictive analytics and optimization to real-world challenges, delivering measurable business impact.
As a trainer, Solomon has served as lead instructor for data science bootcamps and corporate programs, covering Python, Tableau, and advanced visualization tools. He emphasizes storytelling with data, teaching learners how to transform complex datasets into actionable visual insights. His project-based approach ensures participants not only master technical skills but also develop the ability to present findings effectively to stakeholders.

Shahul Hameed Maricar is a certified ACLP trainer and MOE instructor with over a decade of experience in systems integration, product design, and technical training. His career spans multidisciplinary expertise in 3D art, mechatronics, embedded systems, and industrial design, where he has delivered impactful solutions in both academic and corporate settings. With deep technical skills in 3D design software such as Blender and Fusion 360, as well as programming in Python, JavaScript, and C++, Shahul integrates both digital and physical product development in his teaching.

Review

Customer Reviews (102)

Average Rating: 5.0/5 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

dont really like the materials the fact that is talking all about cars making me confused:/ (Posted on 8/11/2026)

Explains things clearly and patiently 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 would like to express my sincere appreciation to Dr. Alvin for being such a wonderful and dedicated teacher. He explains things clearly and patiently, making even difficult topics much easier to understand. Highly recommended! (Posted on 8/9/2026)

Clear concepts, easy to follow for a beginner 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 had the pleasure of learning Data Analysis with Python under Dr. Alvin Ang. He explained the concepts clearly and made the lessons easy to follow, even for someone who was still new to Python and data analysis. His practical examples and step-by-step teaching approach helped me better understand how Python can be used to analyse data. Dr. Alvin was also patient, encouraging and always willing to clarify our questions. I would highly recommend him to anyone who wants to build a strong foundation in Python and data analysis. (Posted on 8/1/2026)

Average Rating: 5.0/5 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

thanks Terrance shifu for equipping me with python fundamental and pandas knowledge. class was well paced and properly structured. trainer is knowledgeable (Posted on 6/21/2026)

Average Rating: 4.0/5 Review by Course Participant/Trainee