Practical Python for Data Professionals

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Sarah Nooravi

1:56:47

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01 - Introduction

01 - Introduction.mp4

01:04

02 - Prerequisites.mp4

01:39

02 - 1. Case Study Introduction

01 - The who, what, where, and why.mp4

00:18

02 - Who.mp4

03:28

03 - What.mp4

02:44

04 - Where.mp4

01:18

05 - Why.mp4

01:02

06 - Case study introduction.mp4

02:25

03 - 2. Breaking Down the Problem Statement

01 - Define the problem The three Ds.mp4

00:45

02 - Get familiar Domain.mp4

04:48

03 - Domain Applied.mp4

02:27

04 - Get familiar Data.mp4

02:53

05 - Get familiar Deliverable.mp4

03:19

06 - Set the right expectations.mp4

02:28

04 - 3. Data Collection, Cleaning, and Transformation

01 - Getting set up in Codespaces.mp4

02:19

02 - Read in data from a CSV file.mp4

04:26

03 - General cleaning techniques.mp4

01:06

04 - General cleaning techniques High-level checks.mp4

04:00

05 - General cleaning techniques Missing values.mp4

02:29

06 - Data transformations Binning.mp4

03:27

05 - 4. EDA

01 - Introduction to EDA.mp4

03:08

02 - Summary statistics.mp4

04:17

03 - Distributions Histograms.mp4

07:23

04 - Data transformations Normalization and log.mp4

03:06

05 - Other distribution types.mp4

03:37

06 - Data visualizations Comparing categories.mp4

06:01

07 - Data visualization Data tables.mp4

05:26

08 - Data visualization Relationships.mp4

04:44

09 - Create a ridge plot.mp4

04:34

06 - 5. Data Visualization and Storytelling

01 - Visual best practices Part 1.mp4

04:05

02 - Visual best practices Part 2.mp4

03:57

03 - Leverage exploratory and explanatory visualizations.mp4

02:37

04 - Choose a medium.mp4

01:44

05 - Storyboarding.mp4

03:20

06 - Whats in a story.mp4

03:10

07 - Putting it all together.mp4

06:03

07 - Conclusion

01 - Wrap-up and next steps.mp4

01:10

Description

As data and data-related jobs have grown over the past decade, so has the demand for data skills. If you’re a data professional, this is great news! However, it’s important to continue to adapt to the changing demands of the market, which include adopting tools like Python to approach big data challenges. In this course, Sarah Nooravi shares a practical, project-based examination of Python, covering the skills needed to help you stand out among others in a competitive market. Sarah walks through an end-to-end Python analysis, typical of what you would encounter on the job– starting from the problem statement and takes you all the way through to insight delivery. Sarah helps you break down the problem, set expectations, and covers best practices around data cleaning, data visualization and storytelling. Lastly, she also shares common pitfalls and critical business and soft skills that will help you stand out.

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Python

Data Mining

Sarah Nooravi

Instructor's Courses

Data is the new oil. —European Consumer Commissioner Meglena Kuneva

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