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!

In this edition, we’re covering powerful tools and resources to advance your data skills. From APIs and web scraping to career tips, there’s something for everyone.

Here’s what’s in store for you this week:

APIs & Web Scraping: Discover how gathering data from online sources using APIs to web scraping in Python can enhance your data projects. Read the full article
Weekly Practice Challenge: Put your Python skills to the test by creating a function to select the first five elements from a list—how fast can you solve it? Take the challenge
Inspiration from the Community: Get tips on AI tools like ChatGPT and GitHub Copilot for coding and explore Alina Mulenkova’s analysis of Heavy Traffic Indicators on I-94. Learn more

In this article, Mike shares how learning APIs and web scraping expanded his data collection capabilities, allowing him to access real-time and custom datasets, automate data retrieval, and enhance his machine learning projects. He highlights the importance of:

Using Python’s requests library to interact with APIs
Processing and handling JSON data structures
Managing API rate limits and implementing effective retrieval strategies
Navigating API documentation for precise data access
Applying web scrape for data sources without APIs
Combining API and web-scraped data for richer, more accurate analyses

If you’re ready to explore APIs and Web Scraping, our APIs and Web Scraping in Python for Data Science course covers all these skills and more, empowering you to collect and analyze data from various online sources.

Read the full article

Practice Challenge

In this edition’s challenge, we invite you to put your Python skills to the test by creating a function that selects the first five elements from a list. While it might seem simple, it’s an excellent way to reinforce your understanding of Python’s list operations and slicing techniques.

Getting comfortable with this will make it easier to filter, manipulate, and access data subsets in your projects. Give it a try and see how quickly you can solve it!

Take the challenge

DQ Resources

📌 Complete Guide to SQL ― A collection of tutorials, practice problems, a handy cheat sheet, guided projects, and frequently asked questions. Click here

📌 Complete Guide to Python ― A collection of tutorials, practice problems, a handy cheat sheet, guided projects, and frequently asked questions. Click here

📌 60+ Python Project Ideas ― A curated list of fun and rewarding Python projects to help you apply your skills in real-world scenarios. Perfect for learners at all levels. Click here

What We're Reading

📖 Become a Better Coder: 10 Tips

Discover 10 tips to enhance your coding skills, including building side projects, contributing to open source, and mastering debugging—perfect for developers looking to grow as programmers. Read more

📖 How to Contribute to Open Source

Learn how to contribute to open source projects, improving the projects and enhancing your portfolio. This guide covers ways to contribute and where to find good projects to join. Read more

📖 3 Career Principles that got me to Director at Google

A former Google director shares career principles that led to five promotions: Glue (essential but overlooked tasks), Grit (persistence through challenges), and Friction (overcoming gaps between reality and ideals). Read more

Community highlights

Project Spotlight

Sharing and reviewing others’ projects is one of the best things you can do to sharpen your skills. Twice a month we will share a project from the community. The top pick wins a $20 gift card!

In this edition, we’re spotlighting Alina Mulenkova‘s well-structured project, Heavy Traffic Indicators on I-94, where she analyzed the factors contributing to heavy traffic on a U.S. interstate. Alina’s project is notable for its thorough background research, along with concise and insightful descriptions of both intermediate findings and final results, making it informative and easy to follow.

Want your project in the spotlight? Share it in the community.

Learn how

Ask Our Community

In this edition, we’re spotlighting the question, “AI-powered coding assistants: whether, which, and how” along with the top advice from our Community. Do you have insights to share? Join the conversation

Neha Jasani (Community Moderator)

I can understand the hesitation when it comes to integrating generative AI into your coding workflow, especially with concerns about maintaining genuine coding skills and sustainability. However, having explored both traditional methods and AI tools, I believe there’s a way to find balance and make the most of the available resources.

1. Tool Choices & Integration Options:

ChatGPT: A versatile tool that can help with coding queries, debug issues, and even explain concepts directly in a conversation. You can use the browser version or integrate it with your development environment using extensions like the Jupyter AI plugin, which allows you to interact with it within Jupyter Notebooks. This way, you can get assistance without leaving your coding workspace, making it more seamless.
GitHub Copilot: This tool works more like an assistant that suggests code snippets and even auto-completes as you type. It integrates directly into your IDE (like VS Code), offering suggestions in real time as you write Python code. This can save time when writing boilerplate code or common functions, but it also allows you to review, tweak, and learn from its suggestions.
Anaconda Pilot: This is a newer tool that comes integrated with Anaconda and works similarly to Copilot. If you’re already using Anaconda, it could be worth exploring to see if it integrates better with your workflow in Jupyter Notebooks.

2. Will These Tools Make You “Dependent”?

It’s understandable to be concerned about relying too much on AI-generated code. However, using AI assistants doesn’t have to replace problem-solving. Instead, view them as tools to enhance your productivity, helping you focus on higher-level logic and more complex challenges while handling repetitive tasks or suggesting best practices. You can still write your code and only use AI as a reference or to unblock yourself when stuck.

3. Productivity Boost & Learning Curve:

In my experience, these tools do improve productivity, but there’s also a learning curve. At first, you might feel like you’re copying and pasting, but over time, you’ll see that AI-generated suggestions can introduce new coding patterns, libraries, and practices you may not have considered.
ChatGPT: It’s like having a personal tutor. You can ask for clarifications on why a certain piece of code works, which encourages active learning rather than passive usage.
Copilot: It learns from your coding style, so the more you use it, the better it gets at giving relevant suggestions.

4. Getting Started:

For ChatGPT, you can simply start by using the web version and asking Python-related questions to get a feel for how it can assist you.
For GitHub Copilot, if you use VS Code, it’s a straightforward extension to install. You can use it directly in your code editor and see how it integrates with your coding workflow.
If you prefer sticking to Jupyter Notebooks, you can explore plugins like Jupyter AI or check out the Anaconda Pilot feature since you’re already familiar with Anaconda.

These tools are like “assistants” that can help you move faster, but they won’t replace the logic, creativity, and understanding required in coding. Experiment with them to see how they fit into your workflow, but keep practicing your problem-solving skills independently as well.

Ask a question

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

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2025-11-12

Learn faster and retain more.
Dataquest is the best way to learn

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The Dataquest Download

Level up your data and AI skills, one newsletter at a time.

Practice Challenge

DQ Resources

What We're Reading

Community highlights

Ask Our Community

Give 20%, Get $20: Time to Refer a Friend!

Real data workflows: Airflow, TensorFlow, and more

What really drives developer salaries?

Learn AI. Build with AI. Think with AI.

Learn faster and retain more.
Dataquest is the best way to learn

The Dataquest Download

Level up your data and AI skills, one newsletter at a time.

Practice Challenge

DQ Resources

What We're Reading

Community highlights

Ask Our Community

Give 20%, Get $20: Time to Refer a Friend!

Real data workflows: Airflow, TensorFlow, and more

What really drives developer salaries?

Learn AI. Build with AI. Think with AI.

Learn faster and retain more.Dataquest is the best way to learn

Learn faster and retain more.
Dataquest is the best way to learn