Productivity Tips, Data Career Insights, and Other Recent Must-Reads

Data Science is a fast-moving field, with new tools constantly emerging, workflows evolving, and career paths changing rapidly—sometimes within the span of mere weeks.

Our most-read and -discussed articles reflect these trends, with readers flocking to excellent articles by data and ML professional who have insights to share based on their on-the-ground experience. To make sure you don't miss our best articles, we're thrilled to share some of our standout stories from the past month. They cover a lot of ground—from coding to LLMs to data storytelling—but share a focus on actionable, firsthand advice. Enjoy!

• Coding was Hard Until I Learned These 2 ThingsHow do you go from "aspiring programmer" to someone who can actually compete for good, coding-heavy jobs? Natassha Selvaraj‘s viral hit looks at the practical aspects of developing a growth mindset and building a daily programming routine.
• 6 Bad Habits Killing Your Productivity in Data ScienceAs Donato Riccio points out, becoming more productive isn't only—or even primarily—about learning and doing more; avoiding or breaking habits that are detrimental to your work is just as important. The ones Donato focuses on are particularly relevant for the daily workflows of data scientists.
• Forget RAG, the Future is RAG-FusionRetrieval-augmented generation has become a common approach for optimizing large language models, but it comes with major drawbacks. Adrian H. Raudaschl presents RAG-Fusion, a modified technique that addressed these challenges by incorporating reciprocal rank fusion and generated queries into the process.

• Introducing KeyLLM – Keyword Extraction with LLMsStill on the topic of making LLMs more efficient, Maarten Grootendorst recently shared the news of the launch of KeyLLM, his extension to the KeyBERT package, which facilitates keyword extraction at scale. He then walks us through an example based on the open-source Mistral 7B model.
• How to Become a Data EngineerIf you're a beginner-level IT practitioner or intermediate software engineer who would like to make a career change,

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