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[FreeCoursesOnline.Me] [Pluralsight] Programming Python Using An IDE [FCO]
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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.
Description
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.
Level
• Intermediate
About Author
Xavier is very passionate about teaching, helping others understand search and Big Data. He is also an entrepreneur, project manager, technical author, trainer, and holds a few certifications with Cloudera, Microsoft, and the Scrum Alliance, along with being a Microsoft MVP.
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FILE LIST
Filename
Size
0. Websites you may like/How you can help Team-FTU.txt
237 B
01 - Course Overview/01 - Course Overview.mp4
12.6 MB
02 - Programming Python Using an IDE! But Why And Which One/02 - Programming Python Using an IDE! But Why And Which One.mp4
18.7 MB
02 - Programming Python Using an IDE! But Why And Which One/03 - Code Editors vs. Integrated Development Environments.mp4
3.4 MB
02 - Programming Python Using an IDE! But Why And Which One/04 - Overview of Available Code Editors for Python.mp4
28.9 MB
02 - Programming Python Using an IDE! But Why And Which One/05 - Configuring Python Features for Specific Code Editors.mp4
29.7 MB
02 - Programming Python Using an IDE! But Why And Which One/06 - Takeaway.mp4
2.7 MB
03 - Improving Your Productivity Programming in Python with an IDE/07 - Improving Your Productivity Programming in Python with an IDE.mp4
21.4 MB
03 - Improving Your Productivity Programming in Python with an IDE/08 - Customizing IDEs.mp4
22.8 MB
03 - Improving Your Productivity Programming in Python with an IDE/09 - Features That Improve Productivity Coding with an IDE.mp4
19.7 MB
03 - Improving Your Productivity Programming in Python with an IDE/10 - Organizing, Navigating, Refactoring, and Styling Code.mp4
31.6 MB
03 - Improving Your Productivity Programming in Python with an IDE/11 - Running and Debugging Python Code with an IDE.mp4
26.3 MB
03 - Improving Your Productivity Programming in Python with an IDE/12 - Integrating with Version Control Using an IDE.mp4
25.8 MB
03 - Improving Your Productivity Programming in Python with an IDE/13 - Working with Databases in Python Using an IDE.mp4
7.9 MB
03 - Improving Your Productivity Programming in Python with an IDE/14 - Unit Testing with an IDE.mp4
7.6 MB
03 - Improving Your Productivity Programming in Python with an IDE/15 - Takeaway.mp4
3.8 MB
04 - Leveraging a Python IDE for Data Science_/16 - Leveraging a Python IDE for Data Science.mp4
4.2 MB
04 - Leveraging a Python IDE for Data Science_/17 - Leveraging Data Science and Scientific Tools in PyCharm.mp4
5.4 MB
04 - Leveraging a Python IDE for Data Science_/18 - Working with an IDE Built for Scientific Python - Spyder.mp4
4.9 MB
04 - Leveraging a Python IDE for Data Science_/19 - Using Jupyter Notebook for Data Science.mp4
8.1 MB
04 - Leveraging a Python IDE for Data Science_/20 - Using Apache Zeppelin for Data Science.mp4
4.8 MB
04 - Leveraging a Python IDE for Data Science_/21 - Cloudera Data Science Workbench for Data Science at Scale.mp4
10.3 MB
04 - Leveraging a Python IDE for Data Science_/22 - Takeaway.mp4
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