"I am a PhD student at Worcester Polytechnic Institute, specializing in Artificial Intelligence and enhancing LLMs’ causal reasoning. I earned my Bachelor’s degree in Computer Science from Colorado College, where I learned about programming, algorithms, and machine learning. In my senior year, I tutored fellow undergrads in core CS courses, in one-on-one sessions and small group workshops. This experience inspired my passion for teaching. I’ve since served as a Teaching Assistant at WPI, holding regular office hours to demystify data science and AI topics for learners at all levels.

My tutoring approach blends intuitive explanations with hands-on practice. I cover the following three subjects:

- Machine Learning Fundamentals: We start with simple line-of-best-fit models and progress through the mathematical foundations of linear algebra and calculus until we understand deep neural networks. You will learn how to train a neural network by working through matrices on paper and by multiplying matrices in Python.

- LLM Fundamentals: I break down the transformer architecture and attention mechanisms and explain how GPT models learn to generate text through large-scale pretraining. By the end, you’ll have built a transformer from scratch in Python.

- Real-world LLM Training: I guide you through the fine-tuning methods used to train modern production LLMs, including Instruction Tuning, RLHF, and verifiable-reward reinforcement learning. I provide an understanding of how and why they work, and the practical skills to train an LLM on whatever hardware you have access to.

The three subjects build on each other, where each concept forms a foundation for the next. With a focus on developing strong, intuitive understanding of fundamentals, I will customize every session to match your knowledge level and specific interests. I'm dedicated to transforming AI newcomers into confident practitioners by providing the personalized guidance you need to achieve your goals and create exceptional work in this field." less...