Course Details
Topic 1: Get Started on Python
- Overview of Python
- Install Python
- Install Python IDE
- Code Your First Python Script
- Comment
Topic 2: Data Types
- Number
- String
- List
- Tuple
- Dictionary
- Set
Topic 3: Operators
- Arithmetic Operators
- Compound Operators
- Comparison Operators
- Membership Operators
- Logical Operators
Topic 4: Control Structure, Loop and Comprehension
- Conditional
- Loop
- Iterating Over Multiple Sequences
- Comprehension
Topic 5: Function
- Function Syntax
- Return Values
- Default Arguments
- Variable Arguments
- Lambda, Map, Filter
Topic 6: Modules & Packages
- Import Modules and Packages
- Python Standard Packages
- Third Party Packages
Final Assessment
- Written Assessment - Short Answer Questions (WA-SAQ)
- Case Study (CS)
- Oral Questioning (OQ)
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:
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 |
|
|
|
SkillsFuture Credit:
PSEA:
|
Absentee Payroll (AP) Funding:
SFEC:
|
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
- 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
- Aspiring Software Developer
- Data Analyst
- Web Developer
- Automation Engineer
- Data Scientist
- System Administrator
- Bioinformatics Specialist
- Research Scientist
- Finance Professional
- Machine Learning Enthusiast
- GIS (Geographic Information System) Specialist
- IT Consultant
- Network Engineer
- Database Administrator
- Tech Entrepreneur.
Trainers
Dr Alvin Ang - Dr Alvin Ang is a highly experienced data science and AI educator with a Ph.D. in Operations Research and over 15 years of teaching and research experience. He has taught at leading institutions including Nanyang Technological University, Singapore University of Social Sciences, Curtin University, and SP Jain School of Global Management, where he earned recognition as Mathematics Professor of the Year. Currently serving as a Data Science and AI Trainer at Tertiary Infotech, Dr Ang has successfully delivered Python and analytics training to diverse learners, ranging from university students to working professionals. He is also the founder of the Open Source Data Science Community (DataFrens.sg), where he actively promotes knowledge sharing and practical applications of Python in real-world problem solving.
With professional certifications such as the Advanced Certificate in Learning and Performance (ACLP) and multiple IBM badges in Python, Data Science, and Machine Learning, Dr Ang combines technical expertise with proven pedagogy. He has trained learners in Python fundamentals, data analysis, and visualization, using hands-on exercises to ensure strong conceptual understanding and practical proficiency. Known for his engaging teaching style and learner-focused approach, Dr Ang leverages his academic publications, industry consultancy, and training experience to guide beginners in building a solid foundation in Python programming, preparing them to advance confidently into data analytics and AI domains.
Terence Ee - Terence Ee is an experienced IT leader and trainer with more than 25 years of expertise in technology management, government systems planning, and enterprise IT strategy. He holds a Master of Science in Technology Management from Staffordshire University and a Bachelor of Science in Computer and Information Sciences from the National University of Singapore. Over the course of his career, Terence has held senior leadership roles, including Chief Information Officer at the Supreme Court of Singapore and Vice President of Information Systems at Senoko Energy, where he successfully oversaw large-scale digital transformation and system integration projects.
Since 2017, Terence has served as an independent consultant and professional trainer, delivering technology and data-related courses to diverse learners. Drawing on his deep experience in IT governance, systems planning, and applied computing, he specializes in guiding beginners through Python fundamentals with a focus on practical problem-solving and clear conceptual grounding. His teaching emphasizes building coding confidence step by step, ensuring learners acquire not only the technical skills but also the analytical mindset required to apply Python effectively in business, government, and industry contexts.
Bernard Peh - Bernard Peh is a seasoned Data Scientist and Principal Trainer with over 25 years of expertise in data science, finance, and investments. Since 2018, he has designed and delivered WSQ courses across major Accredited Training Organizations (ATOs) in Singapore, mentoring more than 1,000 learners in Python programming, data analytics, and applied AI. His deep technical proficiency spans Python, SQL, C/C++, and advanced Excel, making him well-positioned to guide beginners through foundational Python concepts with clarity and practical relevance. Bernard has also served as a keynote speaker and author in data science and investments, underscoring his ability to simplify complex ideas for diverse audiences.
With extensive experience training professionals across industries—including blue-chip companies such as Singtel, NCS, and Capital Land—Bernard combines technical rigor with a learner-centric approach. He emphasizes hands-on practice, step-by-step coding exercises, and real-world examples to ensure strong learner retention. His teaching philosophy is rooted in equipping participants with essential problem-solving and analytical skills that serve as a foundation for advanced data analytics and AI applications. Consistently receiving high learner satisfaction ratings, Bernard is committed to empowering beginners with the confidence and skills to embark on their Python programming journey.
Solomon Soh - Solomon Soh is an experienced Data Scientist and AI Trainer with a strong record of teaching and mentoring in Python programming, data analytics, and machine learning. Currently a Data Science Trainer with IBM Singapore, he has coached teams on projects involving natural language processing, computer vision, and chatbots, achieving a 96% learner satisfaction rating for his communication and technical expertise. His career spans roles at Workforce Optimizer, Certis Cisco, Ernst & Young, and IQVIA, where he applied Python-driven analytics to improve operations, optimize staffing, and deliver actionable insights. His academic background includes a double degree in Economics and Psychology from Singapore Management University (Summa Cum Laude, triple major in Analytics), an MBA, and a Master’s in Financial Engineering.
Solomon’s teaching approach blends technical depth with practical application, making Python fundamentals accessible to beginners while building a foundation for advanced data science skills. As a lead instructor for bootcamps and academies such as Le Wagon, Think Cloud Academy, and AWS Educate, he has guided learners through programming basics, data analysis, and real-world problem-solving. He brings hands-on experience from Kaggle competitions and industry projects, ensuring learners are exposed to relevant case studies and coding exercises. Passionate about empowering learners of all backgrounds, Solomon emphasizes clarity, applied practice, and confidence-building, making him highly effective in equipping beginners to succeed in the WSQ Python Fundamental Course for Beginners.
Shahul H. Maricar - Shahul H. Maricar is a certified ACLP and MOE instructor with over a decade of experience in software systems integration, coding, and adult training. With strong technical expertise spanning Python, JavaScript, HTML/CSS, and embedded systems, he has conducted WSQ and corporate training programs in areas such as Python programming, product design, and web development. Shahul’s career includes roles at the National University of Singapore, where he supported research through systems integration and data analysis, and later as a curriculum lead and trainer for organizations such as Tertiary Infotech, Marshall Cavendish Education, and Sustainable Living Lab. His background demonstrates both technical depth and a proven ability to deliver engaging, hands-on learning experiences.
Passionate about simplifying technical concepts for learners, Shahul emphasizes practical application and solution-based teaching. He has designed and delivered curricula that blend coding with real-world problem solving, from introductory Python and JavaScript to robotics and data visualization. His training approach ensures learners gain confidence in programming fundamentals while developing a mindset for continuous learning and adaptability. With a track record of empowering students across corporate, academic, and public learning environments, Shahul is committed to equipping beginners with the skills they need to succeed in the WSQ Python Fundamental Course for Beginners.
Customer Reviews (536)
- Average Rating: 4.7/5 Review by Course Participant/Trainee
-
N/A (Posted on 3/12/2026)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 - Average Rating: 3.0/5 Review by Course Participant/Trainee
-
New knowledge learned! (Posted on 3/12/2026)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 - Average Rating: 4.0/5 Review by Course Participant/Trainee
-
N/A (Posted on 3/12/2026)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 - Average Rating: 4.0/5 Review by Course Participant/Trainee
-
N/A (Posted on 3/12/2026)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 - Average Rating: 4.3/5 Review by Course Participant/Trainee
-
N/A (Posted on 3/12/2026)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 - Average Rating: 4.0/5 Review by Course Participant/Trainee
-
N/A (Posted on 3/12/2026)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 - Average Rating: 4.0/5 Review by Course Participant/Trainee
-
N/A (Posted on 3/12/2026)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 - Average Rating: 5.0/5 Review by Course Participant/Trainee
-
N/A (Posted on 3/12/2026)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 - Average Rating: 5.0/5 Review by Course Participant/Trainee
-
N/A (Posted on 3/12/2026)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 - Average Rating: 5.0/5 Review by Course Participant/Trainee
-
N/A (Posted on 3/12/2026)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 - Average Rating: 4.3/5 Review by Course Participant/Trainee
-
N/A (Posted on 3/12/2026)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 - Average Rating: 5.0/5 Review by Course Participant/Trainee
-
N/A (Posted on 3/12/2026)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 - Average Rating: 5.0/5 Review by Course Participant/Trainee
-
N/A (Posted on 3/12/2026)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 - Average Rating: 5.0/5 Review by Course Participant/Trainee
-
Good (Posted on 3/12/2026)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 - Average Rating: 5.0/5 Review by Course Participant/Trainee
-
N/A (Posted on 3/12/2026)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 - Average Rating: 3.7/5 Review by Course Participant/Trainee
-
N/A (Posted on 3/12/2026)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 - Average Rating: 4.3/5 Review by Course Participant/Trainee
-
The pace is a little bit fast as there were many new concepts to learn but a lot of good takeaways from the course. There are plenty of practical real life applications. (Posted on 3/12/2026)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 - Average Rating: 5.0/5 Review by Course Participant/Trainee
-
N/A (Posted on 3/12/2026)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 - Average Rating: 5.0/5 Review by Course Participant/Trainee
-
Good (Posted on 3/12/2026)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 - Average Rating: 5.0/5 Review by Course Participant/Trainee
-
N/A (Posted on 3/12/2026)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








