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The Dataquest Download
Level up your data and AI skills, one newsletter at a time.
Each week, the Dataquest Download brings the latest behind-the-scenes developments at Dataquest directly to your inbox. Discover our top tutorial of the week to boost your data skills, get the scoop on any course changes, and pick up a useful tip to apply in your projects. We also spotlight standout projects from our students and share their personal learning journeys.
Hello, Dataquesters!
Here’s what we have for you in this edition:
Top Read: The six AI concepts that actually mattered in 2025 and how they will guide effective work in 2026. A clear reset if you felt overwhelmed last year. Learn more
From the Community: Practical tips on data pitfalls, Parquet vs. CSV for big data, and fixing SQL errors in Jupyter. Join the discussion
What We’re Reading: The math behind AI, Advent of Code walkthroughs, Meta’s new AI compute push, and modern AWS privilege escalation patterns. Learn more
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2025 was loud. New models, new acronyms, and constant claims that everything had changed. But the learners who made real progress weren’t chasing every release. They focused on a small set of foundational concepts that showed up again and again in successful AI projects. This article breaks down the six AI concepts that truly mattered in 2025, and why they’ll continue to define how effective teams build, verify, and improve AI systems in 2026. If last year left you overwhelmed, this is your reset. |
From the Community
Working with Data—Possible Challenges: Artur provides thoughtful considerations on key challenges that can arise when working with any kind of data and how to address them, along with an insightful article on data aggregation.
Parquet vs. CSV File Formats: Alberto shared helpful documentation on the Parquet file format and explained its advantages over the CSV file format—particularly its efficiency and importance when working with big data.
Handling Errors When Running SQL in Jupyter Notebook: Linky suggests a smart and quick fix for the KeyError: ‘DEFAULT’, which occurs due to a compatibility issue when using SQL magic commands in Jupyter Notebook.
What We're Reading
The Mathematical Foundation of AI: Breaks down the math behind AI—vectors, gradients, probabilities, and explains why understanding these fundamentals gives deeper insight into how modern models really work.
Data Science Spotlight–Advent of Code 2025: Walkthroughs of selected Advent of Code 2025 programming puzzles, showing how solving them builds real-world data science skills and problem-solving approaches.
Meta Builds New AI Compute Team: Meta launched Meta Compute to scale data center power for its AI models, with Dina Powell McCormick leading global partnerships to finance and deploy infrastructure.
AWS Privilege Escalation Techniques: Explains how AWS privilege escalation is evolving beyond IAM policies into service-based execution and AI tooling (Bedrock + AgentCore), with labs showing what’s preventable and how to assess real risk.
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High-fives from Vik, Celeste, Anna P, Anna S, Anishta, Bruno, Elena, Mike, Daniel, and Brayan.
2026-01-14
A clear look at what actually mattered in 2025, with community tips, practical data lessons, and reads shaping 2026. Read More
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Learn which data skills still matter in 2026, plus community Power BI tips, and smart reads on APIs, AI, and cloud shifts. Read More
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