The AI Apprenticeship Programme idea was conceived to solve a major issue AI Singapore faced – lack of local engineering talent trained in AI to work on the 100 Experiments (100E) programme. 100E is AI Singapore’s flagship programme to solve industries’ AI problem statements and help them build their own skilled teams.
“When we first thought of the AI Apprenticeship Programme back in July 2017, we were not sure if we could pull it off and get the support we needed as the AI Apprenticeship Programme was not part of the original AI Singapore programme approved. As much as we tried to hire, it was not easy to find Singaporean engineers and developers trained in AI. It also did not help that we were not able to match the salaries of Google, Facebook, Alibaba and the big boys.
So I asked my team if we could train Singaporeans who are keen in AI and are already learning AI on their own but perhaps did not have an opportunity to work on real world AI problems.
Lo and behold…. we found these rough stones and polished them into gems. This was the genesis of the AIAP.” – Laurence Liew, Director of AI Industry Innovation, AISG.
The Pioneer Batch's Toolkit
Thanks to the 100E project offered by the programme, our apprentices were assigned different projects that allowed them to gain valuable hands-on experience at tackling real-world problems that they might face in their future professional lives. According to one of our graduates Lee Cheng Kai, the “fastest way to learn something is to do it.” And that is what the programme delivered. It gave the apprentices the opportunity to “work on real life machine-learning problems and challenges,” which allowed them to learn all about an end-to-end life cycle of a machine learning project. “…practical experience from the apprenticeship accelerated my learning of various AI concepts and frameworks.” concurred Tai Kai Yu, Systems Specialist, Data Analytics/AI, ST Engineering.
Exposure to Substantial Educational Resources
“The programme exposed me to numerous resources and helped me learn all things from AI to DevOps,” said Christopher Leong, a member of our pioneer batch who recently joined the R&D team at Virtuos Games.
Calling on AI talents from various walks of life and different stages of their careers allowed for a diverse and dynamic learning environment. Apprentices shared their expertise and experiences that allowed them to expand each other’s knowledge. According to Hoo Chan Kai, one of our Batch 1 graduates who recently joined DBS as a Data Scientist, the programme allowed him to connect “with like-minded individuals and mentors with a specific domain expertise.”
“…the other apprentices have made my learning easier through discussions and sharing their domain expertise. They are also a fun bunch of people with amazing ideas on AI.” Raimi added.
Giving the apprentices free reign over their AI projects to choose but providing sound guidance and advice, our mentors created a hands-on learning experience for our pioneer batch.
According to Leo Tay, “I was able to share freely with mentors on thoughts and issues about the projects and how to tackle them.”
Spanning over the 9 months programme, the apprentices, who came into AI despite their diverse backgrounds, learnt a lot more about AI especially through the 100E projects they were assigned to. Almost all of them went through at least one end-to-end cycle of an AI project – from problem formulation, modelling, solution engineering to MVP deployment. We also saw the bond they had built amongst themselves – this, we believe is the most important takeaway from the programme. It was also a fulfilling experience for the AISG mentors who, in return, had learnt much from the apprentices through the different interactions and discussions.
12 out of our 13 graduates went to AI-related jobs immediately after the programme; 1 will further her studies in Research at a local university
Advice from the Pioneer Batch
“Be humble and keep an inquisitive and open mind since there are always new skills and knowledge to acquire. Do not shy away from seeking additional inputs or asking your peers for opinions.”
Hoo Chan Kai
“I had no computer science background but I have been trying to get my feet wet with programming and statistics in the last two to three years. In the first three months, we were given time to learn about some basic skills required in AI. Now, I have a better appreciation of AI and the technologies involved, as well as a foundation and platform to go more in-depth.”
What's next for AIAP?
We will continue to grow our own timber!!!
1 batch done
2 batches ongoing…and
6 more batches to go!