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: How to reduce LLM costs using Semantic Caching and Conversation Memory. Learn more

From the Community: Best practices for API security and mastering advanced search. Join the discussion

What We’re Reading: Emerging AI roles, the “luck” of publishing your work, and Codex vs. Claude. Learn more

As vector search systems grow, performance and cost start to matter—especially once you connect them to language models. In this tutorial, you’ll learn how to use vector databases for semantic caching and conversation memory. You’ll see how to avoid redundant LLM calls when users ask similar questions, handle follow-up queries that reference earlier context, and reduce costs without sacrificing quality. A practical next step for anyone building multi-turn, LLM-powered search systems.

From the Community

Using Advanced Search in the Community: Learn how to search Community posts using more granular criteria than just keywords, such as topics with specific tags, posts created before a certain date, or those that include images.

Helpful Project Reviews: Alla suggested valuable best practices for working on data science projects, particularly avoiding hardcoding API keys in scripts and using clear, consistent names for functions and variables—see here and here.

What We're Reading

New AI Roles Are Emerging: OpenAI is hiring a Head of Preparedness to plan for increasingly advanced AI systems. It’s a sign of how the job market is shifting — data skills now open doors to new roles at the intersection of AI, risk, and security.

Publishing Your Work Increases Your Luck: A quick reminder that sharing your work publicly creates more opportunities. This piece explains how visibility compounds over time, and why publishing projects can quietly open doors

Codex vs. Claude Code: A quick comparison showing there’s no single “best” AI tool. The right choice depends on how you work, and the only real way to find the strengths and limits of each is to try them yourself.

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High-fives from Vik, Celeste, Anna P, Anna S, Anishta, Bruno, Elena, Mike, Daniel, and Brayan.

2026-01-07

Action steps to acquire data skills in 2026

Learn which data skills still matter in 2026, plus community Power BI tips, and smart reads on APIs, AI, and cloud shifts. Read More
2026-01-07

Reduce LLM costs using Semantic Caching and Conversation Memory

Learn how semantic caching and conversation memory reduce LLM costs, plus community tips on API security, search, and thoughtful AI reads. Read More
2026-01-07

Postgres vs Qdrant vs Pinecone

Benchmark PostgreSQL, Qdrant, and Pinecone for vector search performance, plus community tips on plotting, cowsay, and real world AI reads. Read More

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