Technology in Finance Immersion Programme (TFIP)

The Technology in Finance Immersion Programme (TFIP) aims to help individuals gain experience in key technology areas, such as agile IT project management, artificial intelligence, business analysis, cloud computing, cybersecurity, data analytics, software engineering and technology, information and cybersecurity risk within the financial services sector.

The program is managed by the Institute of Banking and Finance (IBF), with the support of Workforce Singapore (WSG), Infocomm Media Development Authority (IMDA), SkillsFuture Singapore (SSG), Monetary Authority of Singapore (MAS), and participating financial institutions.

Trainees will acquire the necessary skills through structured training with industry-recognized training providers and an attachment with a leading financial institution.

DigiPen (Singapore) is the training provider for the following tracks:

• Data Analytics Track — Data Analytics and Data Engineering
• Software Engineering Track — Full Stack in Software Development with Java

After selecting one of two available tracks, TFIP trainees must complete eight courses to build strong foundations and robust backgrounds in their specializations that will serve them well in financial institutions.

Self-sponsored individuals may apply to each course directly by reaching out to DigiPen (Singapore) via email at ce.sg@digipen.edu.

Program Details and Fees

Before starting your selected track, TFIP trainees should look over important information regarding course duration and training location, prerequisites, course fees, laptop recommendations, and graduation requirements.

Duration and Training Location

The duration for each course is 15 days. This is a full-time program. Classes are conducted in person at the DigiPen (Singapore) campus between 9:00 a.m. and 5:00 p.m. on Mondays through Fridays, except on public holidays.

TFIP trainees will proceed to their on-the-job training with their respective financial institutions after they have completed all eight courses of classroom learning. View the academic calendar for dates and additional details.

Student-to-Faculty Ratio

The Student-to-Faculty ratio for Data Analytics Track – Data Analytics and Data Engineering is 7:1. The Student-to-Faculty ratio for Software Engineering Track – Full Stack in Software Engineering with Java is 10:1.

Prerequisites

A diploma with two years of working experience is a minimum requirement for entry. In order to receive SkillsFuture funding, self-sponsored individuals must be Singapore Citizens or permanent residents with a minimum age of 21 years old.

Mid-career individuals who are passionate about pursuing a technology career in the financial services sector and who fulfill the eligibility criteria and prerequisites may apply. For prerequisites and application details, please visit the IBF website.

Course Fee

The total course fee for the TFIP is S$28,340.00 per trainee. All fees above are inclusive of 9% GST. This applies to individuals and Singapore-registered companies.

Laptop Recommendation

Trainees will be required to bring their laptops for the classroom learning. Please visit our Laptop Recommendations page for the laptop specifications.

Graduation Requirement and Certification

Trainees must maintain a minimum of 80% attendance and demonstrate competence in the course to receive a Statement of Attainment (SOA) issued by Singapore Workforce Skills Qualifications (WSQ).

Trainees enrolled in the TFIP who received all eight SOAs will be conferred a Specialist Diploma in their specialization track by DigiPen (Singapore).

Please visit the Standard of Progress for more information.

Curriculum Tracks

TFIP trainees will take eight courses during their selected track. The duration for each course is 15 days.

Data Analytics Track — Data Analytics and Data Engineering

Learning Objectives:

• To gain proficiency in the Python programming language based on strong computer science foundations

• To gain proficiency in relational databases and develop a good understanding of database theories

• To gain proficiency in essential mathematical knowledge necessary for data analytics and introductory machine learning

• To gain proficiency in data visualization using industry-standard tools and be equipped with a strong understanding of data visualization theory

• To gain proficiency working with large unstructured data using industry-standard big data tools and software

• To gain an understanding of machine learning algorithms and how to process data for machine learning use

Software Engineering Track — Full Stack in Software Development with Java

Learning Objectives:

• To gain proficiency in the Java programming language based on strong computer science foundations

• To gain proficiency in relational databases and develop a good understanding of database theories

• To gain proficiency in web front-end development and experience with select modern front-end frameworks

• To gain proficiency in web back-end development using Java and experience with select Java-based back-end frameworks

• To gain an understanding of computer networks and network security, which is essential for full-stack software developers