Christine Cheong

I’m a data science lecturer with experience teaching in both university and executive education settings. My work sits at the intersection of rigorous academic grounding and practical, workplace-ready skills.

I came to education through a career in data — and the thing that kept striking me was this: the hardest part of working with data is rarely the analysis itself. It’s helping people understand what the data is actually saying, and why it matters. That realisation shapes how I teach. I know what it looks like when someone finally gets it, and I design my sessions to get people there faster.

What I believe about teaching data science

Most people don’t struggle with data science because it’s too hard. They struggle because it’s taught poorly — with too much theory, too little context, and examples that bear no resemblance to the decisions they’ll actually face.

My approach is different. Every concept I teach is anchored to a real use case. Every exercise is designed to build genuine confidence, not just exam performance. I’d rather a participant leave slightly slower but genuinely understanding than fast and fuzzy.

Background

• Data Science Lecturer, NUS-ISS
• [Previous roles or industry experience — add yours here]
• [Relevant qualifications or credentials]
• [Specialisations — e.g. machine learning, applied statistics, Python]

Beyond the classroom

[2–3 sentences on what you do outside of teaching — writing, research, consulting, speaking, or what keeps you connected to the field.]