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 to make your Kubernetes apps production-ready with health checks, resource limits, non-root users, and configuration management. Read the blog
Community Highlights: From predicting IPO listing gains with deep learning to improving Python readability, see how learners are turning data into insights. Join the discussion
What We’re Reading: Spot security risks in Python’s dynamic features, explore the power of agentic AI, and get an overview of Power BI’s capabilities for data storytelling. Learn more
Deploying applications to Kubernetes is one thing—running them safely in a shared production cluster is another. Without safeguards, a single runaway workload can consume resources, broken apps might still receive traffic, and sensitive data could end up hardcoded in your images.
This tutorial shows you how to add the production-ready features every Kubernetes app needs. You’ll learn how to implement health checks, set resource limits, run containers as non-root users, and manage configuration with ConfigMaps and Secrets. By the end, your apps will be safer, more reliable, and ready to run in shared clusters.
From the Community
Hacker News Posts: Elena shared a concise, professional, and easy-to-read report, with clean and well-commented code, and a clear focus on academic style. This is a great example of using a simple dataset to provide meaningful insights
Predicting Listing Gains in the Indian IPO Market Using TensorFlow: Through a series of visualizations, data cleaning and preparation steps, model-building blocks, and logical reasoning, Mohammad wrote an enticing story and achieved 71% accuracy with his deep learning model.
Project Tutorials
Star Wars Survey Analysis Using Python and Pandas: Learn how build professional-quality visualizations that tell a compelling story about Star Wars fandom, demonstrating how proper data cleaning and thoughtful visualization design can transform raw survey data into stakeholder-ready insights. Learn more
Finding Heavy Traffic Indicators on I-94: Learn how to build multiple visualizations that tell a comprehensive story about traffic patterns, demonstrating how exploratory data analysis can reveal insights that summary statistics alone might miss. Learn more
What We're Reading
Python’s Dynamic Features and Security Risks: Python’s exec, eval, and other dynamic features are powerful but can be abused. This article explores how malicious code can hide in scripts and offers techniques to detect obfuscation.
Power BI – Everything You Need to Know: Power BI is a leading tool for data analysis and storytelling. This piece explains its core features, what makes it stand out, and how it works in practice.
AI Agent vs. Agentic AI: AI agents handle single tasks, but “agentic AI” can coordinate, adapt, and drive outcomes independently. This article breaks down the differences and why agentic AI could redefine automation.
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High-fives from Vik, Celeste, Anna P, Anna S, Anishta, Bruno, Elena, Mike, Daniel, and Brayan.