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The Technology in Finance Immersion Programme (TFIP) aims to help individuals gain experience in key technology areas, such as Artificial Intelligence, Cloud Computing, Cybersecurity, Data Analytics, Software Engineering, Technology Product Management, Business Analysis, Digital Marketing, Agile IT Project Management, and User Experience Design within the financial services sector.

It has been jointly developed by the Institute of Banking and Finance (IBF) and Workforce Singapore (WSG), in consultation with the Infocomm Media Development Authority (IMDA) and the Monetary Authority of Singapore (MAS). Additionally, it has the support and validation of 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:

TFIP trainees will be equipped with strong foundations and robust backgrounds in their specializations that will serve them well in financial institutions.

Duration

This is a full-time, 18-month program consisting of:

  • Classroom learning (six months)
  • On-the-job training (12 months)

Classes will be conducted in person, between 9:00 a.m. and 5:00 p.m. on Mondays to Fridays, except Public Holidays, with a total of 720 contact hours.


Curriculum Modules

Below are the modules that trainees will take during the classroom learning. The duration for each module is 15 days with 90 contact hours.


Artificial Intelligence Track — Machine Learning Software Development

Learning Objectives:

  • To gain proficiency in the Python programming language based on strong computer science foundations
  • To gain proficiency in relational databases and develop good understanding of database theories
  • To gain proficiency in essential mathematical knowledge necessary for machine learning
  • To gain proficiency in modern machine learning algorithms and techniques and be able to develop new machine learning models

Modules:

  • Programming Methodologies: Python
  • Programming Paradigms: Advanced Python
  • Data Structures and Algorithms with Python
  • Databases and Data Modeling
  • Applied Mathematics and Statistics for Machine Learning
  • Introduction to Machine Learning
  • Advanced Machine Learning
  • Artificial Neural Networks and Deep Learning

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 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 strong understanding of data visualization theory
  • To gain proficiency working with large unstructured data using industry-standard big data tools and software
  • To gain understanding of machine learning algorithms and how to process data for machine learning use

Modules:

  • Programming Methodologies: Python
  • Programming Paradigms: Advanced Python
  • Data Structures and Algorithms with Python
  • Databases and Data Modeling
  • Applied Mathematics and Statistics for Data Analytics
  • Data Visualization
  • Data Engineering: Big Data Technologies
  • Introduction to Machine Learning

Software Engineering Track (Java) — 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 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 understanding of computer networks and network security essential for full-stack software developers

Modules:

  • Programming Methodologies: Java
  • Programming Paradigms: Advanced Java
  • Data Structures and Algorithms with Java
  • Databases and Data Modeling
  • Computer Networks and Network Security
  • Backend Development with Java
  • Web Programming
  • Modern Full-Stack Development with Java

Software Engineering Track (Python) — Full Stack in Software Development with Python

Learning Objectives:

  • To gain proficiency in the Python programming language based on strong computer science foundations
  • To gain proficiency in relational databases and develop 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 Python-based back-end frameworks
  • To gain understanding of computer networks and network security essential for full-stack software developers

Modules:

  • Programming Methodologies: Python
  • Programming Paradigms: Advanced Python
  • Data Structures and Algorithms with Python
  • Databases and Data Modeling
  • Computer Networks and Network Security
  • Backend Development with Python
  • Web Programming
  • Modern Full-Stack Development with Python

Prerequisites

Individuals who are passionate about pursuing a career in artificial intelligence, data analytics, or software engineering and who fulfill the following pre-requisites may apply:

  • Singapore Citizens or Permanent Residents
  • Graduated from tertiary education at least two years prior to TFIP application or completed two years of National Service (whichever is later and where relevant)
  • No prior work experience in artificial intelligence, data analytics, or software engineering
  • Tertiary qualification (Diploma/Degree) in Science, Technology, Engineering, or Mathematics (STEM) OR a quantitative field (for data analytics only)
  • Basic understanding of computer systems configuration
  • Basic knowledge of one programming language
  • Any applicant with outstanding obligations to previous sponsorship(s) will not be allowed to participate
  • Must not be a shareholder* of the hosting financial institution or its related entities
  • Must not be owner(s)** of the hosting financial institution
  • Must not be immediate ex-staff of the hosting financial institution or related entities

*Does not apply to publicly traded shares in listed companies
**For non-publicly listed companies, refers to individuals with shareholding per ACRA profile

Course Fee and Training Allowance

  • The course fees are fully funded by the IBF and partnering financial institutions.
  • Trainees will be given a monthly training allowance of S$5,500 for 18 months.

Assessment Methods

Trainees will be assessed by the following:

  • Attendance
  • Assignments
  • Lab Exercise
  • Quizzes
  • Examination

Graduation Requirement

Trainees have to maintain a minimum 80% attendance and a minimum grade of 70% (overall) in order to graduate from the course and receive certification.

Certification

Trainees who meet the Graduation Requirement will be issued a Specialist Diploma in their specialization track by DigiPen (Singapore).

Upon completing the classroom learning, graduates will undergo the 12-month On-the-Job Training (OJT) at their respective financial institutions.

Application Details

Classes commenced in December 2021. Please visit the IBF website for more details on future program dates.

Technical Assessment

  • Only those applications which meet the prerequisites will be further shortlisted, except for exceptional cases.

  • Shortlisted applicants will be invited to complete an online technical assessment. Successful candidates will then be invited for an interview with IBF.

Note

Selected trainees will be required to bring their own laptops for the six months of the classroom learning. Please visit our Computer Recommendations page for the laptop specifications.