Programming Python Using an IDE
Once you have learned the foundations of Python, the next step to increase your productivity is learning how to be proficient with a development environment or IDE. This course will help you get started.
What you'll learn
Learning and becoming proficient with Python is one of the best decisions a coder can make. The simplicity of Python, along with the many libraries available make it one of the most productive languages you can use.
This course, Programming Python Using an IDE, will help you use an IDE to take your coding skills one level higher!
First, you will explore the selection of popular IDEs and how they can help you improve your productivity. Next, you will learn about the many features that make IDEs great for creating applications including syntax highlighting, refactoring, code checking, and more. You will also discover some other features that help you run, debug, unit test, and source control your code. Finally, you will see how some IDEs have features that are meant for scientific Python and creating data science applications.
By the end of this course, you will know and understand how IDEs can help you be a more productive developer.
Table of contents
- Improving Your Productivity Programming in Python with an IDE 9m
- Customizing IDEs 7m
- Features That Improve Productivity Coding with an IDE 7m
- Organizing, Navigating, Refactoring, and Styling Code 9m
- Running and Debugging Python Code with an IDE 12m
- Integrating with Version Control Using an IDE 9m
- Working with Databases in Python Using an IDE 3m
- Unit Testing with an IDE 3m
- Takeaway 3m
- Leveraging a Python IDE for Data Science 3m
- Leveraging Data Science and Scientific Tools in PyCharm 3m
- Working with an IDE Built for Scientific Python: Spyder 2m
- Using Jupyter Notebook for Data Science 4m
- Using Apache Zeppelin for Data Science 2m
- Cloudera Data Science Workbench for Data Science at Scale 5m
- Takeaway 1m