In our Python for Data Science Intermediate course, we’ll cover some key techniques for working with the Python programming language for data science.

To start off, you’ll learn how to clean and prepare data in Python, a critical skill for any data analyst or data scientist job. To do this, you’ll dig into some real-world data about artwork at the Museum of Modern Art and learn to manipulate text, clean messy data, and more. You’ll also get to practice summarizing numeric data and formatting strings in Python.

Next, you will unlock the true power of Python as we dive into object-oriented programming (OOP) and how it relates to data science. Then, you’ll apply this new understanding by building your own class.

Finally, you’ll learn how clean, standardize, and analyze date and time data using Python’s datetime module.

At the end of the course, you will combine all the skills you learned to create a portfolio project centered around Hacker News post titles to find out what types of posts are most likely to be successful at what times.

By the end of this course, you'll be able to:

  • Clean and analyze text data.
  • Understand object-oriented programming in Python.
  • Work with dates and times.

Become a Python data science expert

Cleaning and Preparing Data in Python

Learn how to clean and prepare text data in Python.

Python Data Analysis Basics

Learn the fundamentals of data analysis in Python and how to format text data.

Object-Oriented Python

Learn about using objects, classes, methods, and attributes.

Working With Dates And Times In Python

Learn how to work with and analyze date and time data.

Exploring Hacker News Posts

Practice using loops, cleaning strings, and working with dates in Python.