The Opportunity
Accepted into Coding Camp 2026 by DBS Foundation on the AI Engineer track. A 4-5 month intensive bootcamp covering machine learning, deep learning, and MLOps. Currently learning to build and deploy production-ready AI systems through hands-on projects and working on a capstone.
Why This Matters
Up until now, I’ve been building web applications that use AI services via APIs. But to truly become an AI engineer, I need to understand what’s happening under the hood — training neural networks, tuning hyperparameters, evaluating models, and deploying them in production. This bootcamp moves me beyond being a web developer who integrates AI to being someone who can actually build and train AI systems. It’s the next evolution of my journey.
Technologies & Skills Being Developed
Program Structure
- Machine Learning Fundamentals: Supervised learning, unsupervised learning, and evaluation metrics
- Deep Learning: Neural networks, CNNs, RNNs, transformers, and architectures for different tasks
- MLOps & Deployment: Training pipelines, model monitoring, and production deployments
- Capstone Project: Build and deploy an end-to-end ML system from problem definition to production
My Goals
I’m entering this bootcamp with specific goals: First, I want to truly understand machine learning fundamentals so I can build effective models, not just use libraries. Second, I want to experience the full ML pipeline from data collection to deployment, understanding the challenges and best practices at each stage. Third, I want to build a capstone project that solves a real problem and demonstrates that I can take an idea from concept to production.
Beyond technical skills, I want to join a cohort of like-minded people passionate about AI, form connections with mentors and peers who can challenge me to think deeper, and position myself for roles where I can build AI systems that have meaningful impact.