The Covid pandemic has underscored the importance of embracing technological disruptions and being resilient, and the need to constantly adapt to new developments. Michelle Loke, like other graduates of AI Singapore’s AI Apprenticeship Programme (AIAP), is well prepared for these challenges.
Michelle graduated from the Singapore University of Technology and Design (SUTD) with a degree in Engineering Systems and Design in 2015, and was working as a senior transport planner with the Land Transport Authority (LTA) when AI beckoned.
At LTA, her role revolved around transport modelling, data analytics and visualisation projects. To further improve the projects, she experimented with AI and machine learning to gain deeper insights and value from the data,
At the same time, her research led her to appreciate the potential of AI as a game-changing technology and a platform for change. She also found out about AIAP.
In 2019, Michelle made up her mind to join the programme, which would require her to quit her full-time job at LTA. That, to her, was one of the most difficult aspects of the decision. “I loved being a part of LTA – the people, culture and nature of the work was uplifting. And knowing that you are making a positive contribution to the long-term infrastructure and well-being of your country was also an important reason why I enjoyed being in LTA.”
But she also knew that the fourth industrial revolution was coming, powered by AI and other emerging technologies. AIAP presented her with the opportunity to be part of these new developments and to equip herself with advanced skills that would enable her to contribute more to future projects. This realisation, together with the support of her family, helped strengthen her resolve. Michelle joined AISG’s fourth batch of apprentices and started her stint in September 2019.
The going was tough, especially in the initial stages of the programme. While the coding she learnt in university and the data analytics skills she developed at LTA came in useful, there was still so much to learn. “The environment was fast-paced and the assignments were challenging as the basics of machine learning were drilled into us,” she recalled.
But the experience, although demanding, was made enjoyable by the camaraderie amongst the apprentices. “We were a diverse group of individuals – from fresh grads to mid-career professionals with backgrounds across various sectors. There was something to learn from everyone,” she said. “With the support of fellow apprentices, all of us made it through.”
The programme enabled Michelle to build and strengthen her foundations in machine learning. Good coding practices were drilled into her by her mentor and fellow apprentices, together with the agile methodology of failing fast and reiterating for continuous learning and continuous improvement. “Failure is inevitable when experimenting; the important thing is that the lessons learned from failing are utilised to improve your next attempt,” she said.
She also picked up important skills in project management when she and a fellow apprentice got to work on a healthcare project for a start-up under AISG’s 100Experiments programme. “I had regular meetings with my project sponsor and from the project managers, I learnt how to manage expectations and honed my people and communication skills.
The start-up was focused on developing customised solutions for skincare and her team was tasked to detect features such as pores, spots and inflammation on images of skin using computer vision. “It was really exciting to create a solution for a real-world problem,” she said. “Being involved in the model development process from start to finish was a new experience.”
AIAP also opened the door to new opportunities in data science and AI. Through the AISG Talent and Career Development team, Michelle landed a job as senior analyst with the SingHealth Office for Insights and Analytics after she graduated in June 2020.
In her current role, she creates machine learning models to empower healthcare professionals to make more informed and strategic decisions. “Being involved throughout the whole model development process – from data extraction to modelling to deployment – gives me a sense of ownership over my projects and the opportunity to understand how the different parts of the model development process fits together,” she said.
Looking back on her nine months as an apprentice, Michelle said she really enjoyed her time in AIAP and had fun. “I met with so many gifted, talented and awesome individuals. The supportive and nurturing environment cultivated at AISG made the experience so worthwhile and enjoyable,” she said. “And with the Covid pandemic accelerating the digital revolution, the creative thinking and AI skills I learnt have more than prepared me for the new normal.”