Python Programmer
Gain the career-building programming skills you need to successfully develop software, wrangle data, and perform advanced data analysis in Python. No prior coding experience required.
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 on to writing 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 of 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. Start this track and embark on your journey to becoming a Python programmer.
1 Introduction to Data Science in Python Dive into data science using Python and learn how to effectively analyze and visualize your data. No coding experienc...
Consolidate and extend your knowledge of Python data types such as lists, dictionaries, and tuples, leveraging them t...
Use the world’s most popular Python data science package to manipulate data and calculate summary statistics.
Learn the art of writing your own functions in Python, as well as key concepts like scoping and error handling.
Continue to build your modern Data Science skills by learning about iterators and list comprehensions.
Learn to write efficient code that executes quickly and allocates resources skillfully to avoid unnecessary overhead.
Learn how to work with dates and times in Python.
8 Regular Expressions in Python Learn about string manipulation and become a master at using regular expressions.
9 Web Scraping in Python Learn to retrieve and parse information from the internet using the Python library scrapy.
Learn to use best practices to write maintainable, reusable, complex functions with good documentation.
The Unix command line helps users combine existing programs in new ways, automate repetitive tasks, and run programs ...
Learn about modularity, documentation, and automated testing to help you solve data science problems more quickly and...
13 Developing Python Packages Learn to create your own Python packages to make your code easier to use and share with others.
14 Unit Testing for Data Science in Python Learn how to write unit tests for your Data Science projects in Python using pytest.
Dive in and learn how to create classes and leverage inheritance and polymorphism to reuse and optimize code.
Statement of Accomplishment