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: Learn how to set up PySpark locally with Docker, understand core Spark concepts like RDDs and SparkSession, and build your first distributed data processing app. No cluster needed. Learn more
From the Community: Learn how one learner built a 98% accurate spam filter, another predicted heart disease using logistic regression, and get a clear breakdown of the difference between else and elif. Join the discussion
DQ Resources: Build and deploy automated ETL pipelines using Apache Airflow, starting locally and scaling to the cloud with AWS. Learn more
Struggling with slow Python scripts and crashing Excel files? It’s time to level up. This beginner-friendly tutorial walks you through setting up PySpark locally, explains Spark’s architecture in plain language, and shows you how to build your first distributed data processing app using Python.
- Learn the role of SparkSession, RDDs, and SparkContext
- Set up PySpark in Jupyter without configuration headaches
- Understand how distributed computing tackles real-world data challenges
- Run your first Spark job on real data—no cluster required
From the Community
Building a Spam Filter with Naive Bayes: Steve’s machine learning project hits over 98% accuracy using clean, efficient code and well-structured functions. Simple yet powerful.
Predicting Heart Disease Risk with Logistic Regression: Dimitar delivers a full end-to-end project with clear goals, strong EDA, and impactful visualizations, all tied together with great storytelling.
Else vs. Elif in Python: Raisa breaks down the difference between else and elif with clear examples. Great for anyone refining their Python logic.
DQ Resources
Automate and Monitor ETL Pipelines Locally (Part I): Build a fully functional ETL pipeline running locally with Apache Airflow and Docker. Automate data tasks, monitor them through a visual UI, and quickly identify and fix any issues. No more manual runs or missed jobs. Learn more
Launch a Scalable, Cloud-Hosted ETL Pipeline (Part II): Deploy your ETL workflow to the cloud using AWS. Production-ready Airflow setup that includes cloud storage (S3), a relational database (RDS), IAM roles, and secure infrastructure, built to scale and run reliably. Learn more
How to Choose the Right Cloud Service Provider: Not sure whether to go with AWS, Azure, or GCP? This 30-day roadmap helps you test all three using their free tiers so you can make an informed choice based on hands-on experience. Perfect for beginners! Learn more
What We're Reading
Estimating Memory Usage in pandas: Understand how pandas handles memory and file sizes with this clear breakdown. Helpful for anyone working with large datasets or optimizing data pipelines.
Train Your Own Vision Language Model with nanoVLM: Inspired by nanoGPT, nanoVLM lets you explore vision-language modeling in a beginner-friendly way, right from a free Colab notebook. Great for learning the fundamentals of multimodal AI.
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High-fives from Vik, Celeste, Anna P, Anna S, Anishta, Bruno, Elena, Mike, Daniel, and Brayan.