The Dataquest Download
Level up your data and AI skills, one newsletter at a time.
Hello, Dataquesters!
Here’s what we have in store for you in this edition:
Top Read: See prompt engineering in action, and learn how to use AI to generate and analyze realistic survey data, step by step. Learn more
From the Community: Explore the winning projects and key takeaways from Dataquest’s first-ever Kaggle competition on heart disease prediction—real data, real solutions, and valuable lessons from fellow learners. Learn more
New Resource: Segment customers with K-means clustering—analyze real data, build groups, and uncover actionable business insights. Learn more
Practical Application of Prompt Engineering for Data Professionals
Want to see how professionals use prompt engineering for data tasks? In this hands-on follow-up, you’ll learn how to use AI tools to generate realistic synthetic survey data, categorize open-ended feedback, and extract insights in structured formats. These are skills every data professional can use to streamline analysis and build practice datasets with ease.
From the Community
Exploring NYC Taxi Data in 2016 with Python: Nguyen has conducted exploratory data analysis and built an impressive individual project with detailed analysis steps, efficient use of functions, and compelling visualizations. It is an excellent example of applying acquired knowledge on independent projects, and a great start for any beginner data analyst!
Mobile App for Lottery Addiction: Fakhriddin skillfully used functional programming to create a highly flexible project with enhanced code readability, demonstrating the application of the Don’t Repeat Yourself (DRY) programming principle.
Heart Disease Prediction Kaggle Competition—Winners’ Projects: Check out the projects of Yash and Aghogho, the winners of the first Kaggle competition in partnership with Dataquest, and be ready for the next competition.
Heart Disease Prediction Kaggle Competition—Insights: Ravi shared his completed solution notebook, together with valuable insights and lessons learned while participating in the Kaggle competition.
Creating an Algorithm for Mesoscale Convective Systems: Raisa provides a structured guide to help develop an algorithm for mesoscale convective systems (MCSs), describing all key steps, processes, tools, and possible challenges.
DQ Resources
Customer Segmentation Using K-Means Clustering: Discover how to group customers by behavior and demographics using K-means clustering. Learn to identify key segments, unlock actionable insights, and target your marketing more effectively. Learn more
Cloud Providers: AWS, Azure, GCP: Explore the strengths, key services, and pricing models of AWS, Azure, and Google Cloud. This guide compares and contrasts the major cloud providers, helping you understand, choose, and get hands-on with today’s leading platforms for your next cloud project. Learn more
Build a Python Word Guessing Game: Learn to create a Wordle-style word guessing game in Python. A fun way to practice programming fundamentals like loops, logic, and object-oriented design. Great for beginners looking to build interactive projects. Learn more
What We're Reading
What Is MCP, and Why Is Everyone – Suddenly!– Talking About It?: This article breaks down where MCP came from, why they’re trending, and what we can expect their impact on the world of AI to be.
How to Create Beautiful Documentation That Developers Actually Love: Most dev docs get overlooked, but this article shares practical tips on structure, design, and tools to help you create documentation developers will actually want to read.
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High-fives from Vik, Celeste, Anna P, Anna S, Anishta, Bruno, Elena, Mike, Daniel, and Brayan.