When working with data, you won’t always find it in a pristine CSV file. Sometimes, you’ll have to find and collect it on your own. Knowing how to do this is like a superpower, and it’s a highly sought-after skill.

In this skill path, we'll teach you how to use application program interfaces (APIs) and powerful web scraping tools to create truly unique and targeted datasets.

APIs and web scraping with R allow you to automate the process of putting unstructured data into an organized and understandable dataset. By enrolling in this path you can:

  • Learn the basics of APIs and how to query external data sources using an API with R
  • Discover the basics of scraping data from the web using a variety of web scraping tools
  • Acquire proficiency in identifying and overcoming common setbacks in practical data analysis

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What You’ll Learn

Manipulating, analyzing, and interpreting assumes that you have data to work with. For that reason, data acquisition is the beginning of every data science project. In this APIs and Web Scraping with R path, you’ll learn how to perform basic data acquisition tasks using R. This path is a succinct introduction that prepares you for more advanced courses.

Enroll in this skill path if you want to learn how to do the following:

  • Use R to perform basic data acquisition tasks
  • Query external data sources using an API
  • Create and process API requests
  • Discover how the JSON data format works
  • Authenticate with APIs
  • Uncover the basics of scraping data from the web
  • Understand how webpages are structured using HTML
  • Implement the basics of web scraping
  • Use a complex CSS Selector
  • Gain proficiency in a variety of web scraper tools
Data Scientist in Python Salary Increase

Data engineers command an average salary of $112k, according to Glassdoor.

Data Scientist in Python Job Openings

BLS data predicts a whopping 22% increase in data science jobs by 2030.

Data Scientist In Python Job Growth

Top tech giants like Google, Facebook, and Microsoft all rely on R (ListenData).

How Our APIs and Web Scraping with R Skill Path Works

As a data professional, you may find that most of the time you’re supplied with the data you need for a project. But there will also be times when you’ll need to acquire the data yourself. That’s why we’ve created this skill path⁠—to teach you how to use APIs and web scrapers with R to scrape server-side rendered pages to organize a dataset.

Dataquest believes in learning by doing, not just by watching videos. What makes our courses unique is that every data acquisition skill you’ll learn in this path you’ll also put into practice through guided projects and practice problems using real code.

We’ve helped over one million data learners develop their career skills. With our unique hands-on courses, we’ll give you the ability to demonstrate data skills in real-world scenarios. It’s one of the reasons why 97% of our learners prefer our teaching method — demonstrating those skills is exactly what you’ll need to impress a hiring manager.

Additionally, with Dataquest, you’ll never learn alone. Our vibrant community of data professionals and students is eager to assist you every step of the way. Whether you’re stuck on a problem, need advice on a project, or are looking for resources to help you find a job, we're here to support you.

Here’s a quick glance at this skill path:

  • This skill path consists of the two courses listed below, which cover beginner to intermediate topics about APIs and web scraping with R and basic HTML.
  • You’ll write real code with dozens of practice problems to validate and apply your skills.
  • At the end of the course, you’ll complete a guided project to reinforce your new knowledge and expand your portfolio.
  • When you complete the course, you’ll receive a certificate that you can share with your professional network.
  • Once you complete this skill path, you’re welcome to explore other R skill paths like Data Visualization With R, and Probability and Statistics.
  • Engage with the community, get feedback on your project, and keep building.

Enroll in this career path to learn data visualization with R!

APIs and Web Scraping with R Skill Path Course List

APIs in R
Learn how to acquire data from APIs.

Web Scraping in R
Learn how to acquire data from the web.

Who Is This APIs and Web Scraping with R Skill Path for?

This path has a very broad application in the data science field since data acquisition is step one of any data science project. If you don’t have data, you don’t have data science. So whether you’re a beginner, a student, a professional, or even a hobbyist, you’ll find value in the data acquisition skills in this path.

Here are some examples of who would benefit from this path:

  • People who want a career as a data scientist, data analyst, or data engineer
  • People seeking remote work
  • Anyone who works with data in telecommunication, finance, education, and healthcare
  • Junior data scientists or data analysts who want to advance in their current position
  • Anyone who wants to build their own datasets
  • Anyone who wants to discover how data acquisition works
  • Students who want to develop a competitive portfolio
  • Data scientists or data analysts who want to expand the tools at their disposal
  • R users seeking more variety in their skills
  • Data scientists who want to hone their data acquisition skills
  • Data journalists who want to collect data for an article 

Qualify for In-demand Jobs in APIs and Web Scraping with R

Data acquisition skills are in high demand, and many businesses across a variety of industries are seeking qualified data professionals. You can use the skills you’ll learn in this path in the following in-demand data jobs:

  • Data scientist
  • Data analyst
  • Data engineer
  • Web data analyst
  • Applications developer
  • Web harvester

  • Data acquisition analyst
  • Business analyst
  • Financial analyst
  • Applied research statistician
  • Market research manager
  • Software engineer
  • Big data developer
  • Marketing analytics manager
  • Quantitative analyst
  • Data Architect
  • Statistician