TGx:Pluralsight | Boost Data Science Productivity with PyCharm [FCO] TGx Exclusive

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Pluralsight | Boost Data Science Productivity with PyCharm [FCO] TGx Exclusive

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Other > Training

Language:

English

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426.98 MB

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3bcc6cdefd40c28a9b01c990cbe22f9484228113

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Prom3th3uS :_verified_uploader:

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10-04-2019 17:10

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File	Size
01.Course Overview/0101.Course Overview.mp4	15.34 MB
02.Getting Started/0201.Setting Expectations.mp4	12.53 MB
02.Getting Started/0202.PyCharm Editions.mp4	11.59 MB
02.Getting Started/0203.Installation.mp4	6.17 MB
02.Getting Started/0204.Customizing PyCharm.mp4	12.63 MB
02.Getting Started/0205.Interpreters.mp4	10.05 MB
03.Understanding Code/0301.Projects.mp4	13.05 MB
03.Understanding Code/0302.Searching.mp4	12.56 MB
03.Understanding Code/0303.Find Usages.mp4	6.79 MB
03.Understanding Code/0304.Diagrams.mp4	8.36 MB
03.Understanding Code/0305.Hierarchies.mp4	10.45 MB
03.Understanding Code/0306.Documentation.mp4	6.14 MB
03.Understanding Code/0307.Running Code.mp4	21.99 MB
03.Understanding Code/0308.Running Tests.mp4	17.07 MB
04.Writing Better Code/0401.Code Completion.mp4	5.62 MB
04.Writing Better Code/0402.Refactoring.mp4	6.05 MB
04.Writing Better Code/0403.Demo.mp4	20.60 MB
04.Writing Better Code/0404.Inspections.mp4	13.45 MB
04.Writing Better Code/0405.Testing.mp4	22.65 MB
04.Writing Better Code/0406.Version Control with Git.mp4	18.97 MB
05.Debugging Code/0501.Breakpoints.mp4	16.07 MB
05.Debugging Code/0503.Stepping.mp4	12.16 MB
05.Debugging Code/0504.Attaching to a Process.mp4	10.41 MB
05.Debugging Code/0505.Remote Debugging.mp4	14.31 MB
06.Exploring Data/0601.Scientific Mode.mp4	13.17 MB
06.Exploring Data/0602.Exploring a Dataset.mp4	26.09 MB
06.Exploring Data/0603.Jupyter Notebooks.mp4	16.43 MB
06.Exploring Data/0604.R Scripts.mp4	22.22 MB
06.Exploring Data/0605.SQL Queries.mp4	25.83 MB
06.Exploring Data/0606.Summary.mp4	15.89 MB
Discuss.FTUForum.com.html	31.89 kB
Exercise Files/pycharm-boost-data-science-productivity.zip	2.11 MB
FreeCoursesOnline.Me.html	108.30 kB
FTUForum.com.html	100.44 kB
How you can help Team-FTU.txt	235.00 B
Torrent Downloaded From GloDls.to.txt	84.00 B
[TGx]Downloaded from torrentgalaxy.org.txt	524.00 B

Description

Created by: Dan Tofan
Language: English
Released: Mar 29, 2019
Torrent Contains: 37 Files, 7 Folders
Course Source: https://www.pluralsight.com/courses/pycharm-boost-data-science-productivity

About

PyCharm is an incredible Python integrated development environment. This course shows tips, tricks, and techniques to boost your Python productivity with PyCharm, with step-by-step demos targeted at Data Science projects.

Description

Being productive with the tools at your disposal is key to the success of any data scientist. Pycharm brings many coding, debugging, and scientific tools to the table. In this course, Boost Data Science Productivity with PyCharm, you will gain the ability to use PyCharm’s most relevant features for Data Science projects. Features such as highlighting typos and visual debugging reduce development friction and empower you to focus on finishing your Data Science projects faster. First, you will learn to understand code faster, by finding usages, creating classes diagrams, viewing hierarchies, and accessing documentation. Next, you will discover how to write better code faster by using PyCharm features, such as code completion, refactoring, and inspections, as well as how to debug code by using breakpoints, stepping, and remote debugging. Finally, you will learn how to explore data by using the scientific mode in PyCharm, Jupyter notebooks, running R script, and SQL queries. When you’re finished with this course, you will have a great set of tips, tricks, and techniques to boost your Python productivity in your Data Science projects.

Level

• Intermediate

About Author

As a software engineer and lifelong learner, Dan wrote a PhD thesis and many highly-cited publications on decision making and knowledge acquisition in software architecture. Dan used Microsoft technologies for many years, but moved gradually to Python, Linux and AWS to gain different perspectives of the computing world.

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