Back to top

3D mesh of a humanoid man with programming code overlaid on his body.

Together with the Institute of Banking and Finance (IBF) and Workforce Singapore (WSG), DigiPen (Singapore) launched the Artificial Intelligence (AI) track of the Technology in Finance Immersion Programme (TFIP) in October last year. In line with the nation’s push toward digitalization, TFIP aims to help eligible Singapore citizens and permanent residents (PRs) upskill and gain expertise in technology areas such as AI, Cloud Computing, Cybersecurity, Data Analytics, and Full-Stack Development within the financial services sector. In the recent run of the program, DigiPen (Singapore) was the training provider for the AI technology component, whereby trainees were equipped with machine learning expertise and technical knowledge.

TFIP 2020’s AI track offered by IBF is a full-time program spanning two years. Trainees first have to complete six months of academic coursework with DigiPen (Singapore), followed by 18 months of on-the-job training at a financial institution. The participating financial institutions in TFIP 2020’s AI track are DBS, Deutsche Bank, LGT Bank, Mizuho Bank, Singapore Exchange and UOB. May 2021 marked the end of the classroom training for this first batch of trainees, and all 22 of them will be moving on to their respective job attachments.

During the course at DigiPen (Singapore), trainees were exposed to a variety of topics. In the beginning, they learned programming in Python and R and studied introductory topics in databases, artificial intelligence and machine learning, as well as fundamental data structures and algorithms. Familiarizing themselves with these core computer science concepts allowed them to progress to more complex topics such as applied mathematics for machine learning; data engineering for processing, visualizing, and administering data; and artificial neural networks and deep learning.

The goal of TFIP’s AI track is to empower trainees to use artificial intelligence and machine learning technologies in a financial setting to generate insights and automate processes. For instance, machine learning can be leveraged for financial monitoring, making investment predictions, algorithmic trading, and to better secure transactions.

TFIP trainees attending a virtual class
TFIP trainees attending a virtual class.

Due to the vast amounts of knowledge trainees had to pick up, the curriculum was designed so that new topics would always build upon the foundations of earlier topics. This made learning more progressive and seamless. Furthermore, classroom theory was always accompanied by hands-on practice, giving trainees ample opportunity to apply their knowledge via daily assignments and regular projects. This ensured that trainees had a deep understanding of what they were taught. Lessons were held five days a week, with lectures in the mornings and practical sessions in the afternoon.

Trainees Teo Zuo Zhe and Toh Chern Yi can attest to the thoroughness of the program. “The most challenging part was absorbing the sheer amount of content that was taught,” says Zuo Zhe, who was a manufacturing engineer in the oil and gas industry prior to joining TFIP. He overcame this by putting in extra hours to study and looking up additional resources on Coursera or YouTube.

For fellow trainee Chern Yi, who was previously an analyst, reaching out to his peers and lecturers helped him keep on top of his studies. “Though the pace of learning was fast, the program was structured with sufficient breaks in between,” he says. “I’m also thankful to the helpful, hands-on lecturers and experienced classmates that I had, all of whom I could discuss problems with whenever I needed to.”

Zuo Zhe and Chern Yi have since started their attachments at DBS and LGT Bank, respectively. Both of them are excited to apply what they have learned in a practical way. Having gone through the program, they also encourage others who are considering upskilling themselves to give TFIP a shot.

“Congratulations to all 22 graduates on the successful completion of their training with DigiPen (Singapore), under the TFIP’s Artificial Intelligence track,” Mr. Ng Nam Sin, Chief Executive Officer of IBF, says. “I understand that the programs and learning are very rigorous — understandably so, as AI is a very specialized field of work. It will equip you well for your attachments with your respective financial institutions. I wish you success and look forward to you joining the financial sector as technology professionals.”

“We are grateful to IBF for this collaboration and look forward to upskilling more talents for the financial sector together,” Mr. Tan Chek Ming, Managing Director of DigiPen (Singapore), says.