Teaching

A list of courses and talks I’ve given.

📚 Courses

These are courses I’ve led or taught:

• AI Evals For Engineers & PMs: A 4 week intensive course on how to improve LLM applications with evals. (2025)

• Mastering LLMs: A survey course on LLMs, covering topics like evals, RAG, fine-tuning, prompt engineering, and more. (2024)

🎤 Talks

These are a list of talks I’ve given:

• How to Construct Domain Specific LLM Evaluation Systems, AI Engineering World’s Fair, June 2024.

• Building Real-World LLM Products with Fine-Tuning, TWIML AI Podcast, June 2024.

• Evaluating and Productionizing LLMs, Vanishing Data Podcast, Nov 2023.

• Innovating on Software Development, Data Council, March 2023.

• AutoML, Literate Programming, and Data Tooling Cargo Cults, Vanishing Gradients Podcast with Hugo Bowne Anderson, July 2022.

• How to evaluate ML Tooling: Guest Lecutre for Stanford CS 329S ML Systems Design, Feb 2022. Slides, Video

• JupyterCon 2020: “fastpages - A new, open source Jupyter notebook blogging system.”. Slides, Video.

• Gradient Descent by Weights & Biases: A discussion on Automated Machine Learning, CodeSearchNet, GitHub Actions and MLOps: Video

• GitHub Universe 2019: “Machine Learning Ops With GitHub Actions & Kubernetes”. Video

• TensorFlow World, 2019: “Automating your developer workflow on GitHub with Tensorflow”. Slides, Link

• Data Skeptic Interview, Jan 2018: “Semantic Search at Github”.

• KubeCon 2018, “Natural Language Code Search With Kubeflow”. Slides, Video

• KDD, London August 2018: Hands on tutorial, “Feature Extraction and Summarization With Sequence to Sequence Learning”. Tutorial-site

• Ml4all, Portland May 2018: “How to Create Magical Data Products Using Sequence-to-Sequence Models”. Slides, Video

• ODSC, San Francisco Nov 2017: “Advice For New And Junior Data Scientists” Video