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CASL - Python Programming for Finance

Sessions 3 days
Duration 24 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.

Funding for this course is valid from 9 Aug 2026 to 8 Aug 2027. Register and complete the course within this period to qualify for funding support.

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.

CASL - Python Programming for Finance

Course Code: TGS-2026065049

CASL
PSEA
UTAP
SFEC
Absentee Payroll
MCES

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Elevate your financial analysis capabilities with our specialized WSQ-endorsed course on Python Programming for Finance. This comprehensive course delves into the application of Python for various financial tasks including trading algorithms, portfolio management, and risk assessment. Through hands-on exercises and real-world financial case studies, you will learn how to utilize Python's powerful libraries to analyze financial data, forecast trends, and make data-driven decisions.

Upon completing the course, you’ll have a robust skill set in applying Python for financial analysis and strategy development. Whether you're a financial analyst, a portfolio manager, or someone keen on fintech, this course equips you with the computational tools and knowledge to optimize your financial operations and strategies effectively.

Full Fee $1,000.00 Before GST

GST $90.00 9% of fee

Baseline Nett $590.00 SG/PR age 21+ · 50% funded

MCES / SME Nett $390.00 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: Introduction to Python Programming

Business requirements and objectives

Applications of Python programming to meet business requirements

Install Python and Setup Python IDE

Topic 2: Data Types and Operators

Data Types

Operators

Topic 3: Problem Solving with Control Structures

Problem solving with conditional and loop techniques

Coding using comprehensions

Topic 4: Scripting with Function and Lambda

Create Python functions to meet business use cases

Lambda function and its applications

Topic 5: Import and Process Finance Data

Data analysis using Pandas package

DataFrame and Series data structures

Import finance data

Filter and slice finance data

Clean missing data

Topic 6: Aggregate and Visualize Finance Data

Join finance data with concat, append and merge

Aggregate data with groupby and pivot table

Assess codes to identify gaps

Test and visualize finance data

Topic 7: Analyze Finance Data

Improve codes with pipe and apply

Applications of statistics

Analyse finance data to track any changes

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

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

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 is an ACLP-certified trainer with a Ph.D. in Operations Research from Nanyang Technological University and extensive teaching experience in Python, quantitative methods, and finance analytics. He has served as a lecturer at universities such as NTU, SUSS, and Curtin, and as a Data Science/AI trainer at Tertiary Infotech. With multiple IBM and Kaggle certifications in Python, R, data science, and machine learning, Alvin combines academic rigor with practical applications in finance, operations, and analytics.
In his Python for Finance training, Alvin emphasizes applying Python to financial modeling, portfolio analysis, and risk assessment. Learners gain hands-on practice with Python libraries such as pandas, NumPy, and matplotlib to perform time-series analysis, data visualization, and quantitative finance computations. His structured approach ensures participants understand both the technical coding aspects and the financial logic behind their applications.

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.

Solomon Soh is a data scientist and ACLP-certified trainer with strong expertise in Python, machine learning, and finance-related applications. At IBM Singapore and Workforce Optimizer, he managed projects involving financial forecasting, optimization models, and AI-powered decision support systems. His technical expertise spans Python (pandas, NumPy, scikit-learn), Flask, SQL, and deployment pipelines for financial and analytics solutions.
In his Python for Finance training, Solomon emphasizes practical coding and problem-solving. He teaches learners to build Python scripts for financial data extraction, time-series forecasting, and portfolio simulations. By incorporating real-world case studies and hands-on projects, he ensures participants develop the confidence to apply Python in solving finance and investment challenges.

Yeoh Heng Theng is a data science and analytics professional with extensive experience in Python programming, machine learning, and quantitative modeling. As the Data & Analytics Product Lead at Amplify Health, she oversees AI-driven projects that enhance financial and business intelligence across regional operations. Her career spans key roles in companies such as Huawei International and DataRobot, where she developed and implemented data analytics solutions for enterprise clients. Holding a Master of Technology in Enterprise Business Analytics from the National University of Singapore, she brings both technical expertise and strategic acumen to data-driven decision-making.
In “Python Programming for Finance,” Heng Theng focuses on helping learners apply Python to real-world financial analytics and quantitative modeling. Her sessions cover financial data manipulation, statistical analysis, and portfolio optimization using libraries such as NumPy, pandas, and scikit-learn. By blending finance principles with data science techniques, she equips participants to automate workflows, build forecasting models, and extract actionable insights from complex financial datasets.

Mohamed Afiq is a financial data analyst and programming instructor with expertise in Python development, financial modeling, and data visualization. With a background in financial engineering and quantitative analytics, he has applied programming solutions to support risk assessment, market prediction, and investment decision-making. As an educator, Afiq specializes in simplifying technical concepts and guiding learners in developing practical coding proficiency for finance applications.
In “Python Programming for Finance,” Afiq teaches participants how to harness Python’s capabilities for automating financial tasks and conducting analytical modeling. His training covers topics such as time-series forecasting, data cleaning, and visualization using libraries like matplotlib and seaborn. Through real-world exercises and case-based learning, he enables learners to develop Python-based solutions for pricing, trading analysis, and financial performance evaluation, bridging programming knowledge with applied financial insight.