Boost Data Science Productivity with PyCharm

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Dan Tofan

2:33:19

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1. Course Overview

1. Course Overview.mp4

01:47

2. Getting Started

1. Version Check.mp4

00:15

2. Setting Expectations.mp4

03:20

3. PyCharm Editions.mp4

03:22

4. Installation.mp4

02:58

5. Customizing PyCharm.mp4

05:34

6. Interpreters.mp4

04:58

3. Understanding Code

1. Projects.mp4

05:37

2. Searching.mp4

04:26

3. Find Usages.mp4

03:09

4. Diagrams.mp4

02:59

5. Hierarchies.mp4

03:15

6. Documentation.mp4

02:03

7. Running Code.mp4

05:57

8. Running Tests.mp4

03:48

4. Writing Better Code

1. Code Completion.mp4

03:40

2. Refactoring.mp4

03:33

3. Demo.mp4

05:46

4. Inspections.mp4

05:25

5. Testing.mp4

06:56

6. Version Control with Git.mp4

06:49

5. Debugging Code

1. Breakpoints.mp4

07:15

2. Debug Tool Window.mp4

05:01

3. Stepping.mp4

04:49

4. Attaching to a Process.mp4

03:40

5. Remote Debugging.mp4

06:28

6. Exploring Data

1. Scientific Mode.mp4

05:35

2. Exploring a Dataset.mp4

08:32

3. Jupyter Notebooks.mp4

07:03

4. R Scripts.mp4

07:50

5. SQL Queries.mp4

08:41

6. Summary.mp4

02:48

Description

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.

What You'll Learn?

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.

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Python

Data Science

Dan Tofan

Instructor's Courses

Dan started programming decades ago on a Spectrum clone and started his professional programming career in 2003. Eager to learn, Dan moved to Netherlands to study at the University of Groningen. Now, Dan is proud of his PhD thesis on decision making and knowledge acquisition in software architecture, and about a dozen publications with hundreds of citations. Dan used Microsoft technologies for many years, but migrated gradually to Python, Linux and AWS, to learn more of the computing world. Currently, Dan is a full-time Python programmer at the Romania office of a global company in the research domain.

Pluralsight

View courses Pluralsight

Pluralsight, LLC is an American privately held online education company that offers a variety of video training courses for software developers, IT administrators, and creative professionals through its website. Founded in 2004 by Aaron Skonnard, Keith Brown, Fritz Onion, and Bill Williams, the company has its headquarters in Farmington, Utah. As of July 2018, it uses more than 1,400 subject-matter experts as authors, and offers more than 7,000 courses in its catalog. Since first moving its courses online in 2007, the company has expanded, developing a full enterprise platform, and adding skills assessment modules.