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Introduction to Data Science in Python
Dive into data science using Python and learn how to effectively analyze and visualize your data.
Data Types for Data Science in Python
Consolidate and extend your knowledge of Python data types such as lists, dictionaries, and tuples, leveraging them to solve Data Science problems.
Data Manipulation with pandas
Use the world’s most popular Python data science package to manipulate data and calculate summary statistics.
Python Data Science Toolbox (Part 1)
Learn the art of writing your own functions in Python, as well as key concepts like scoping and error handling.
Python Data Science Toolbox (Part 2)
Continue to build your modern Data Science skills by learning about iterators and list comprehensions.
Writing Efficient Python Code
Learn to write efficient code that executes quickly and allocates resources skillfully to avoid unnecessary overhead.
Regular Expressions in Python
Learn about string manipulation and become a master at using regular expressions.
Web Scraping in Python
Learn to retrieve and parse information from the internet using the Python library scrapy.
Writing Functions in Python
Learn to use best practices to write maintainable, reusable, complex functions with good documentation.
Introduction to Shell
The Unix command line helps users combine existing programs in new ways, automate repetitive tasks, and run programs on clusters and clouds.
Parallel Programming with Dask
Learn how to take the Python workflows you currently have and easily scale them up to large datasets without the need for distributed computing environments.
Software Engineering for Data Scientists in Python
Learn about modularity, documentation, and automated testing to help you solve data science problems more quickly and reliably.
Developing Python Packages
Learn to create your own Python packages to make your code easier to use and share with others.
Unit Testing for Data Science in Python
Learn how to write unit tests for your Data Science projects in Python using pytest.