Linkedin - Python Tools Jupyter vs. PyCharm
"softddl.org"
24-10-2021, 22:35
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MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Skill Level: Beginner | Genre: eLearning | Language: English + srt | Duration: 29m | Size: 350.3 MB
As Python has risen in popularity, there are many tools and repositories that have also become increasingly important. Of the many that are available, Jupyter and PyCharm have emerged as leading tools. In this course, software engineer and instructor Sam Pettus provides you with the baseline knowledge you need to work effectively with both Jupyter and PyCharm, as well as determine which option works best for you. Sam begins by detailing the difference between integrated development environments (IDEs) and open-source web applications, as well as how each of these tools function. Sam then walks through the key differences between each tool when working on a data science project, including topics such as debugging and integrating data. He then goes over the user profiles that most commonly leverage each program, giving you the ability to make a decision between the two depending on the project or task at hand. After watching this course, you'll be familiar with the pros, cons, and use cases for each programming tool.
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Skill Level: Beginner | Genre: eLearning | Language: English + srt | Duration: 29m | Size: 350.3 MB
As Python has risen in popularity, there are many tools and repositories that have also become increasingly important. Of the many that are available, Jupyter and PyCharm have emerged as leading tools. In this course, software engineer and instructor Sam Pettus provides you with the baseline knowledge you need to work effectively with both Jupyter and PyCharm, as well as determine which option works best for you. Sam begins by detailing the difference between integrated development environments (IDEs) and open-source web applications, as well as how each of these tools function. Sam then walks through the key differences between each tool when working on a data science project, including topics such as debugging and integrating data. He then goes over the user profiles that most commonly leverage each program, giving you the ability to make a decision between the two depending on the project or task at hand. After watching this course, you'll be familiar with the pros, cons, and use cases for each programming tool.
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