Gain the career-building skills you need to successfully develop software, wrangle data, perform advanced data analysis, and become a Python programmer. No prior coding experience is required; you can start your journey to becoming a Python programmer today! In this track, you’ll learn how to manipulate data, write efficient Python code, and work with challenging data, including date and time data, text data, and web data using APIs. As your skills grow, you'll progress to writing Python functions and unit testing—an essential skill needed to find bugs in your code before your users do! Through interactive exercises, you'll also gain experience working with powerful Python libraries, including NumPy, pytest, and pycodestyle, that will help you perform key programmer tasks such as web development, data analysis, and task automation. By the time you finish this track, you’ll have a firm grasp of what’s needed to become a Python programmer and have the skills to get started as one.
Python67 hours17 Courses
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Introduction to Python
Master the basics of data analysis with Python in just four hours. This online course will introduce the Python interface and explore popular packages.
Level up your data science skills by creating visualizations using Matplotlib and manipulating DataFrames with pandas.
Data Manipulation with pandas
Learn how to import and clean data, calculate statistics, and create visualizations with pandas.
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.
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.
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.
Introduction to Git
Familiarize yourself with Git for version control. Explore how to track, compare, modify, and revert files, as well as collaborate with colleagues using Git.
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.
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