Before joining Heicoders, I was in the education field. I had been a teacher, an editor, a curriculum specialist, and a tutor for several years. Over time, I realised that my work involved a lot of giving, with limited room to invest in my own growth.
I was motivated to switch to data analytics because I had a strong maths background, exposure to programming courses during university, and a genuine interest in finding patterns in data. While teaching, I proactively learned various technologies in my own time and applied them to design interactive digital resources to help students visualise mathematical concepts. Even in education, I found myself drawn to analysing results, spotting trends, and understanding why things behaved the way they did.
Before Heicoders, I attended a data science bootcamp the year before, but I was unable to secure a job in that field. I then pivoted to applying for data analyst roles while juggling freelance curriculum writing and a teaching assistant role for the TFIP data analytics programme. During my job search, I realised that many data analyst roles required practical skills I did not yet have, such as proficiency in Tableau or Power BI. That was when I started actively looking for a programme that could help me close those gaps.
After doing some research, I came across Heicoders, which was listed among the top international training programmes. I decided to take a leap of faith and signed up for DA100 because I wanted to strengthen my technical stack, especially in SQL and Tableau.
I really enjoyed the lessons. My instructor, Min Yan, made a strong impression from the very first class. I was struck by how organised the programme was and how engaging the lessons felt. Concepts were explained clearly using stories and real examples, which made learning feel approachable rather than intimidating. Lesson materials and notes were always available for revision, which helped reinforce learning. Both teaching assistants were also incredibly supportive throughout the course.
One thing that stood out to me was the feedback for the capstone project. It was not just a grade, but detailed and constructive feedback that focused on how to improve our dashboards. I appreciated that a lot. The course also covered a wide range of data visualisation techniques. Coming from a maths background, I did not find the concepts difficult, but I was still impressed by how clearly they were explained to learners from very different backgrounds.
Heicoders also offers a career guidance programme, which I found extremely helpful. Before this, I had spoken to career coaches from other organisations who told me my resume looked good, yet I did not receive any responses. Under Yu Ning's guidance, I started getting some replies, which gave me hope.
With persistence and a bit of luck, I eventually landed a role at my current company. I did not start out as a data analyst. My first role was actually as a data engineer, where I learned a lot on the job. Later, when I was reassigned as a Tableau developer to convert SAP reports into Tableau dashboards, what I learned in Heicoders became an essential foundation that I relied on daily.
Since then, I have taken GA100, the Generative AI for Automation course, and I am currently enrolled in AI300, which focuses on machine learning deployment to the cloud. I have applied what I learned to develop teaching resources as a hobby and as a way to explore the practical limits of these tools. In my day-to-day work, I often use generative AI to automate processes such as data validation.
It has been almost two years since I took my first course at Heicoders, and I am now working as a Tableau developer in the transport industry. I design dashboards from scratch and maintain existing ones using custom SQL. I genuinely enjoy the work because it involves constant problem solving and learning, and it feels both challenging and rewarding.
Heicoders gave me the foundation to take confident first steps and continue making meaningful progress in the workplace.
