“I like that Dataquest doesn’t leave out visual learners. It’s text-based, but it’s not just text — concepts are explained using illustrations and animations.”

Antoine Eripret

SEO Lead

Course overview

This course builds upon Introduction to Python ProgrammingFor Loops and Conditional Statements in PythonDictionaries, Frequency Tables, and Functions in Python, and Python Functions and Jupyter Notebook. You’ll not only learn how to manipulate text, clean messy data, and more but also how to work with object-oriented programming concepts, dates, and times in Python.

Best of all, you’ll learn by doing — you’ll practice and get feedback directly in the browser. You’ll apply your skills to several guided projects involving realistic business scenarios to build your portfolio and prepare for your next interview.

Key skills

  • Cleaning and analyzing text data
  • Processing dates and times
  • Defining object-oriented programming in Python

Course outline

Intermediate Python for Data Science [5 lessons]

Cleaning and Preparing Data in Python 2h

Lesson Objectives
  • Prepare text data in Python
  • Clean data
  • Resolve errors during data cleaning

Python Data Analysis Basics 2h

Lesson Objectives
  • Analyze data
  • Summarize numeric data
  • Format strings in Python

Object-Oriented Python 2h

Lesson Objectives
  • Define object-oriented programming for data science
  • Define classes, instances, attributes, and methods.
  • Create your own class

Working with Dates and Times in Python 2h

Lesson Objectives
  • Parse dates from strings using the datetime library
  • Analyze dates and times
  • Format dates using strftime

Guided Project: Exploring Hacker News Posts 2h

Lesson Objectives
  • Employ loops to explore data CSV data
  • Clean string methods for data analysis
  • Process dates in python

Projects in this course

Guided Project: Exploring Hacker News Posts

For this project, we’ll be data analysts exploring Hacker News posts. We’ll use Python string manipulation, OOP, and date handling to analyze trends driving post popularity. Check out our Jupyter Notebook Guided Project if needed.

The Dataquest 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.


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

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for learners who complete a path

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.”


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 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!”

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