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It’s been exciting to see so many TDS authors dive headfirst into Fall, sharing hands-on, actionable insights on topics starting from cutting-edge (agents, MCP…) to evergreen (Python skills and machine learning engineering, to call just a few).
Equally thrilling? To see our September articles resonate with so many readers, who then share them far and wide. Join us as we have a good time our most-read stories of the past month — they cover a broad spectrum of knowledge science, ML, and AI themes, so that you’re certain to find something relevant to your current interests.
Find out how to Turn out to be a Machine Learning Engineer (Step-by-Step)
Egor Howell has made it his specialty to create guides for aspiring data and ML practitioners — and their success proves how eager job seekers are for honest, pragmatic, and detailed advice. His latest, on the (increasingly popular) machine learning engineer profession path, is one other resource that ought to go straight to your bookmarks.
Implementing the Coffee Machine in Python
Programming basics explained with an attractive twist? Yes, please! Mahnoor Javed’s latest Python tutorial covers conditional statements, loops, and dictionaries.
Python Can Now Call Mojo
A second Python post zoomed all of the solution to the highest of our best-performing articles this month: Thomas Reid’s comprehensive, example-filled guide to boosting your runtime with a healthy dose of Mojo code.
Creator Spotlights
TDS contributors are embedded across industries, disciplines, and organization types, so chatting with them gives us — and also you — an unfiltered view of life on the forefront of knowledge science and AI. Listed here are two recent Q&As you shouldn’t miss.
Other September Highlights
Don’t miss our other top reads from September, tackling a number of the most buzz-generating tools, concepts, and workflows of the moment.
- Using LangGraph and MCP Servers to Create My Own Voice Assistant, by Benjamin Lee
- The End-to-End Data Scientist’s Prompt Playbook, by Sara Nobrega
- Creating and Deploying an MCP Server from Scratch, by Vyacheslav Efimov
- Constructing Research Agents for Tech Insights, by Ida Silfverskiöld
- My Experiments with NotebookLM for Teaching, by Parul Pandey
- Why Context Is the Recent Currency in AI: From RAG to Context Engineering, by Sudheer Singamsetty
Meet Our Recent Authors
The newest cohort of TDS contributors has done a unbelievable job translating modern work into engaging and accessible articles.Â
- Iva Pezo explores AI’s potential to make the resource-intensive strategy of fact-checking faster, scalable, and more reliable.
- Sruly Rosenblat and coauthors Ilan Strauss, Isobel Moure, and Tim O’Reilly take an in depth have a look at the emerging AI developer ecosystem and the rise of MCP.
- Karol Struniawski (together with Antoni Olbrysz and Tomasz Wierzbicki) presents a picture recognition project on the intersection of computer vision, ecology, and biotechnology.
We love publishing articles from recent authors, so in the event you’ve recently written an interesting project walkthrough, tutorial, or theoretical reflection on any of our core topics, why not share it with us?
