Aaron

“The beauty of Dataquest is that it starts at the most basic level, so a true beginner can understand the concepts”

Aaron Melton

Business Analyst @Aditi Consulting

Course overview

In this course, you’ll learn how to build a simple data pipeline using imperative and functional paradigms. You’ll also learn how to use functional closures in Python, how to implement a well-designed pipeline API, how to write decorators, and how to apply them to functions.
At the end of the course, you’ll work on a real-world project, using a data pipeline to summarize Hacker News data. This project is a chance for you to combine the skills you learned in this course and build a real-world data pipeline from raw data to summarization.

Key skills

  • Writing a robust pipeline with a scheduler in Python
  • Using advanced Python concepts like closures, decorators, and more

Course outline

Building a Data Pipeline [5 lessons]

Functional Programming 2h

Lesson Objectives
  • Identify the differences between imperative and functional programming
  • Write code in Python in a functional style using map, reduce, and filter

Pipeline Tasks 2h

Lesson Objectives
  • Build task functions in a pipeline
  • Write functions using the functional paradigm

Building a Pipeline Class 1h

Lesson Objectives
  • Implement functional closures in Python
  • Apply decorators to functions
  • Implement a pipeline API

Multiple Dependency Pipeline 1h

Lesson Objectives
  • Define graph theory
  • Implement a directed acyclic graph in Python
  • Write a scheduler for the pipeline class

Guided Project: Hacker News Pipeline 1h

Lesson Objectives
  • Process JSON API data in Python.
  • Expand your portfolio by building a data pipeline

Projects in this course

Guided Project: Hacker News Pipeline

For this project, we’ll step into the role of data engineers to process Hacker News posts using Python. We’ll apply skills in JSON parsing, string cleaning, and building data pipelines.

The Dataquest guarantee

Guarantee

Dataquest has helped thousands of people start new careers in data. If you put in the work and follow our path, you’ll master data skills and grow your career.

Money

We believe so strongly in our paths that we offer a full satisfaction guarantee. If you complete a career path on Dataquest and aren’t satisfied with your outcome, we’ll give you a refund.

Master skills faster with Dataquest

Go from zero to job-ready

Go from zero to job-ready

Learn exactly what you need to achieve your goal. Don’t waste time on unrelated lessons.

Build your project portfolio

Build your project portfolio

Build confidence with our in-depth projects, and show off your data skills.

Challenge yourself with exercises

Challenge yourself with exercises

Work with real data from day one with interactive lessons and hands-on exercises.

Showcase your path certification

Showcase your path certification

Impress employers by completing a capstone project and certifying it with an expert review.

Grow your career with
Dataquest.

98%
of learners recommend
Dataquest for career advancement
4.85
Dataquest rating
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$30k
Average salary boost
for learners who complete a path
Aaron

Aaron Melton

Business Analyst at Aditi Consulting

“Dataquest starts at the most basic level, so a beginner can understand the concepts. I tried learning to code before, using Codecademy and Coursera. I struggled because I had no background in coding, and I was spending a lot of time Googling. Dataquest helped me actually learn.”

Jessi

Jessica Ko

Machine Learning Engineer at Twitter

“I liked the interactive environment on Dataquest. The material was clear and well organized. I spent more time practicing then watching videos and it made me want to keep learning.”

Victoria

Victoria E. Guzik

Associate Data Scientist at Callisto Media

“I really love learning on Dataquest. I looked into a couple of other options and I found that they were much too handhold-y and fill in the blank relative to Dataquest’s method. The projects on Dataquest were key to getting my job. I doubled my income!”

Join 1M+ data learners on
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