Towards Data Science

5 AI Skills That Will Keep Data Scientists Relevant in 2027

The article titled "5 AI Skills That Will Keep Data Scientists Relevant in 2027" outlines five specific AI competencies, explaining what each skill addresses and providing runnable code snippets that readers can directly paste into a notebook. It serves as a practical guide for data scientists aiming to stay current with emerging AI technologies.

Towards Data Science
Aug 29

4 Claude Skills Every Data Scientist Needs in 2026

The article lists four skills that data scientists should acquire to stay competitive in 2026. It emphasizes the importance of integrating these skills into current workflows to avoid falling behind. The post was originally published on Towards Data Science.

By Haden Pelletier
Towards Data Science
22h ago

4 Ways to Use AI on a PhD Thesis

The article outlines four practical applications of AI for PhD students: locating relevant citations, consolidating code snippets, fact‑checking research claims, and preparing for the thesis defence. It highlights how AI tools can streamline the research process and improve the quality of academic work.

By Conor O'Sullivan
Towards Data Science
Aug 27

How to Work with AI Coding Agents

The article "How to Work with AI Coding Agents" offers a practical guide aimed at improving code quality rather than merely increasing quantity. It focuses on strategies and best practices for effectively collaborating with AI coding tools to produce better code. The post was originally published on Towards Data Science.

By Sara A. Metwalli
Towards Data Science
Sep 8

Introducing ShipAI

Towards Data Science has released a video showcase titled "Introducing ShipAI," which highlights real‑world AI work. The post announces this new visual resource and its focus on practical AI applications. It is positioned as a first look into the platform’s capabilities.

By TDS Editors
Towards Data Science
1d ago

An Introduction to Jev

The article titled "An Introduction to Jev" discusses an AI system that focuses on making decisions rather than generating text. It highlights Jev’s unique approach to decision-making within the broader context of AI development. The piece was originally published on Towards Data Science.

By Thomas Reid