Free research training for AI in Medicine
Updated 2025 The best way to learn how to present research is to study real presentations. Here are my slides from over a decade of conference talks — with honest commentary on what worked, what I’d change, and what you can take directly as a template. Most advice on research presentations is abstract. “Tell a … Read more
From zero to your first working analysis — install R, set up RStudio, and learn the core tools every data scientist needs. Last Updated 2026 — originally published July 2018 R is still one of the most powerful tools in a data scientist’s toolkit — especially for statistical modeling, EDA, and clinical research. This guide … Read more
From raw data to publication-quality visualizations — master EDA with dplyr and ggplot2 before you build your first model. Updated 2026 edition — originally published August 2018 Exploratory Data Analysis (EDA) is the most important step before any machine learning model — and R makes it fast, visual, and intuitive. This tutorial covers everything from … Read more
Using our paper on Parkinson’s Disease subtyping as a case study, I share the essential steps for navigating the complex world of medical research. Featured Image by Erik Mclean on Unsplash Given the wide accessibility to medical imaging and NLP datasets and benchmarking efforts of LLMs, clinical research with patient data still has higher barriers … Read more
A step-by-step guide with a real case study for busy industry professionals to write quality AI papers without burnout. If you’re reading this, chances are you’re an AI professional juggling a demanding full-time job and wondering how to get your research out there without losing your mind. Publishing a paper at a top AI conference … Read more
From raw text to model-ready features — a hands-on guide to the NLP libraries every data scientist and researcher needs to know. A practical, code-first guide to natural language processing in Python — from raw text to model-ready features, using the libraries every NLP researcher needs to know. NLP in 2025 is dominated by large … Read more
From \bibitem to BibTeX, \cite to \citet, and \label to \ref — everything you need to handle references correctly in any academic paper. Updated 2025 — companion to “Writing Papers in LaTeX: The Complete Guide” Everything you need to know about citations, references, and cross-referencing in LaTeX — with working code snippets for every scenario … Read more
Why 98% accuracy can mean a useless model — and how to detect, measure, and fix class imbalance with resampling, SMOTE, and cost-sensitive learning. Updated for 2025 — originally published August 2018 Class imbalance is one of the most common real-world problems in machine learning — and it’s especially severe in medical datasets. Here’s a … Read more
A strategic guide to proving your impact, demonstrating your fit, and winning the research job offer. A research interview isn’t just a test of your knowledge; it’s a test of your value. While you can recite theorems and explain your methods, can you convince a panel that your work matters to them? What I cover … Read more
How Perplexity’s agentic platform turns browsing into a seamless, conversational experience If you’ve ever felt overwhelmed juggling dozens of browser tabs or wished your browser could do more than just display web pages, then Comet might just be the game-changer you’ve been waiting for. Launched recently by Perplexity AI, Comet is not your typical web browser. It’s … Read more