Building Your First Python Analytics Solution

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Janani Ravi

2:46:28

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1. Course Overview

1. Course Overview.mp4

01:47

2. Getting Started with Python for Analytics

01. Version Check.mp4

00:16

02. Module Overview.mp4

01:21

03. Prerequisites and Course Outline.mp4

01:21

04. Python for Data Analytics.mp4

05:46

05. Python Development Environments.mp4

04:56

06. Python Packages.mp4

04:01

07. Demo- Windows - Installing Python and Using Pip to Install Packages.mp4

03:53

08. Demo- MacOS - Using Brew to Install Python 3.mp4

03:49

09. Demo- MacOS - Using Pip to Install Packages.mp4

03:55

10. Demo- Installing and Working with Virtual Environments.mp4

03:27

11. Demo- Editing a Python Script Using Nano and Vim.mp4

03:29

12. Demo- Editing a Python Script Using SublimeText.mp4

02:55

13. Demo- Using Online Editors to Write Python Code.mp4

03:40

14. Module Summary.mp4

01:38

3. Working with Python Using Anaconda

01. Module Overview.mp4

01:23

02. Introducing Jupyter Notebooks.mp4

03:43

03. Demo- Windows Installing Anaconda and Running Jupyter Notebooks.mp4

02:57

04. Demo- Mac OS Installing Anaconda and Running Jupyter Notebooks.mp4

03:19

05. Demo- Installing the Python 2 Kernel along with Python 3.mp4

03:06

06. Demo- Executing Code in Jupyter.mp4

03:44

07. Demo- Restarting and Switching Kernels.mp4

04:07

08. Demo- Exploring Magic Commands.mp4

04:37

09. Demo- Line Magic and Cell Magic Commands.mp4

03:58

10. Demo- Exploring Interactive Widgets.mp4

03:34

11. Demo- Wrangling and Visualizing Data.mp4

04:44

12. Module Summary.mp4

01:29

4. Working with Python Using Other IDEs

01. Module Overview.mp4

01:52

02. Exploring Popular IDEs for Python.mp4

03:02

03. Demo- Installing and Setting up IDLE.mp4

04:43

04. Demo- Running and Debugging Code with IDLE.mp4

06:20

05. Demo- Installing Eclipse and Setting up the PyDev Plugin.mp4

04:29

06. Demo- Running and Debugging Code with Eclipse.mp4

06:00

07. Demo- Installing and Setting up PyCharm.mp4

04:15

08. Demo- Running and Debugging Code with PyCharm.mp4

05:51

09. Demo- Working with Spyder.mp4

06:09

10. Module Summary.mp4

01:31

5. Working with Python on the Cloud

1. Module Overview.mp4

01:40

2. Jupyter on the Cloud.mp4

03:46

3. Demo- Getting Started with Azure Notebooks.mp4

03:47

4. Demo- Analyzing and Visualizing Data on Azure Notebooks.mp4

04:30

5. Demo- Setting up and Connecting to Cloud Datalab on the GCP.mp4

05:31

6. Demo- Building a Simple Regression Model on Datalab.mp4

05:47

7. Demo- Setting up a SageMaker Notebook Instance on AWS.mp4

03:51

8. Demo- Executing Code to Integrate with S3 Buckets.mp4

04:43

9. Summary and Further Study.mp4

01:46

Description

This course covers the important aspects of choosing a development environment for Python, the differences between Conda and Pip for working with Python libraries, popular IDEs such as PyCharm, IDLE, Eclipse, and Spyder, as well as running Python on the cloud.

What You'll Learn?

Python has exploded in popularity in recent years, largely because it makes analyzing and working with data so incredibly simple. Despite its great success as a prototyping tool, Python is still relatively unproven for large, enterprise-scale development.

In this course, Building your First Python Analytics Solution you will gain the ability to identify and use the right development and execution environment for your enterprise.

First, you will learn how Jupyter notebooks, despite their immense popularity, are not quite as robust as fully-fledged Integrated Development Environments, or IDEs. Next, you will discover how different execution environments offer alternative ways of configuring Python libraries, and specifically how the two most popular, Conda and Pip, stack up against each other.

You will also explore several different development environments including IDLE, PyCharm, Eclipse, and Spyder.

Finally, you will round out your knowledge by running Python on the major cloud environments, including AWS, Microsoft Azure, and the GCP.

When you’re finished with this course, you will have the skills and knowledge to identify the correct development and execution environments for Python in your organizational context.

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Python

Data Analysis

Janani Ravi

Instructor's Courses

Janani has a Masters degree from Stanford and worked for 7+ years at Google. She was one of the original engineers on Google Docs and holds 4 patents for its real-time collaborative editing framework. After spending years working in tech in the Bay Area, New York, and Singapore at companies such as Microsoft, Google, and Flipkart, Janani finally decided to combine her love for technology with her passion for teaching. She is now the co-founder of Loonycorn, a content studio focused on providing high-quality content for technical skill development. Loonycorn is working on developing an engine (patent filed) to automate animations for presentations and educational content.

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.