The Dataquest Download
Level up your data and AI skills, one newsletter at a time.
Hello, Dataquesters!
Here’s what we have for you in this edition:
Top Read: Learn how function calling works, how LLMs decide when to use tools, and the common mistakes that can break AI agents, chatbots, and automation workflows in Python. Learn more
From the Community: A strong COVID-19 trend analysis, a forest fire visualization project, practical R plotting tips, and advice for making project insights easier to understand. Join the discussion
What We’re Reading: AI agents for AWS workflows, the human skill AI still cannot automate, and the IT career trends heating up and cooling down. Learn more
Top Read
Many AI apps fail not because the model is wrong, but because tool calls are. A missing parameter, poor schema design, or incorrect function handling can break an otherwise solid application.
This tutorial shows how function calling works, how LLMs decide when to use tools, and the most common implementation mistakes to avoid when building AI agents, chatbots, and automation workflows in Python.
From the Community
COVID-19 Trends Analysis: Daniel’s project showcases a complete data analysis workflow and stands out for its well-organized structure, detailed explanations of each step, neat visuals, and comprehensive summary that provides a clear picture of virus trends for anyone seeking quick insights.
Removing Plot Titles and Labels in R: Alla presents two valid methods for correctly removing titles or labels from visualizations in R when necessary, ensuring the code runs cleanly without producing warnings.
Analyzing Forest Fire Data: In this professional and easy-to-follow, visualization-focused project, Daniel effectively uses a variety of plots to uncover and explore relationships between natural factors and forest fires, such as the influence of wind and humidity.
Helpful Tips for Better Insight Demonstration: Casandra provides specific suggestions for making project findings easier to digest, such as adding charts where relevant, sorting and grouping data in charts and tables, and using meaningful names for table columns.
What We're Reading
How Spotify Generated 1.4 Billion AI Stories: Spotify Engineering shares how it combined heuristics, prompt engineering, and LLMs to create personalized Wrapped stories for hundreds of millions of users. A fascinating behind-the-scenes look at AI operating at massive scale.
The Skill AI Can’t Automate: AI is making it easier than ever to build software, but deciding what to build is becoming the real challenge. This article explores why judgment, ownership, and taste matter more than ever in the age of AI-assisted development.
5 Hot IT Career Trends — and 5 Going Cold: This article explores the skills gaining momentum, from AI integration and data analysis to cloud and security, and the roles that may be losing relevance.
Give 20%, Get $20: Time to Refer a Friend!
Give 20% Get $20
Now is the perfect time to share Dataquest with a friend. Gift a 20% discount, and for every friend who subscribes, earn a $20 bonus. Use your bonuses for digital gift cards, prepaid cards, or donate to charity. Your choice! Click here
High-fives from Vik, Celeste, Anna P, Anna S, Anishta, Bruno, Elena, Mike, Daniel, and Brayan.