Practical Python for Data Professionals

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Practical Python for Data Professionals [TutsNode.net] - Practical Python for Data Professionals 01 - Introduction
  • 02 - Prerequisites.mp4 (32.7 MB)
  • 01 - Introduction.srt (1.9 KB)
  • 02 - Prerequisites.srt (2.7 KB)
  • 01 - Introduction.mp4 (15.9 MB)
05 - 4. EDA
  • 03 - Distributions Histograms.srt (12.1 KB)
  • 06 - Data visualizations Comparing categories.srt (8.2 KB)
  • 07 - Data visualization Data tables.srt (8.0 KB)
  • 08 - Data visualization Relationships.srt (7.2 KB)
  • 02 - Summary statistics.srt (6.2 KB)
  • 09 - Create a ridge plot.srt (5.8 KB)
  • 03 - Distributions Histograms.mp4 (16.3 MB)
  • 05 - Other distribution types.srt (5.1 KB)
  • 01 - Introduction to EDA.srt (4.9 KB)
  • 04 - Data transformations Normalization and log.srt (4.8 KB)
  • 06 - Data visualizations Comparing categories.mp4 (16.1 MB)
  • 08 - Data visualization Relationships.mp4 (15.1 MB)
  • 07 - Data visualization Data tables.mp4 (13.0 MB)
  • 09 - Create a ridge plot.mp4 (13.0 MB)
  • 02 - Summary statistics.mp4 (11.8 MB)
  • 05 - Other distribution types.mp4 (8.3 MB)
  • 04 - Data transformations Normalization and log.mp4 (8.3 MB)
  • 01 - Introduction to EDA.mp4 (8.2 MB)
02 - 1. Case Study Introduction
  • 01 - The who, what, where, and why.srt (0.4 KB)
  • 04 - Where.srt (2.2 KB)
  • 05 - Why.srt (1.7 KB)
  • 02 - Who.srt (5.9 KB)
  • 03 - What.srt (4.8 KB)
  • 06 - Case study introduction.srt (4.2 KB)
  • 02 - Who.mp4 (11.1 MB)
  • 03 - What.mp4 (8.1 MB)
  • 06 - Case study introduction.mp4 (7.7 MB)
  • 01 - The who, what, where, and why.mp4 (5.6 MB)
  • 04 - Where.mp4 (4.1 MB)
  • 05 - Why.mp4 (1.5 MB)
07 - Conclusion
  • 01 - Wrap-up and next steps.mp4 (24.2 MB)
  • 01 - Wrap-up and next steps.srt (1.8 KB)
06 - 5. Data Visualization and Storytelling
  • 07 - Putting it all together.srt (10.2 KB)
  • 01 - Visual best practices Part 1.srt (6.4 KB)
  • 02 - Visual best practices Part 2.srt (6.2 KB)
  • 05 - Storyboarding.srt (5.8 KB)
  • 06 - What's in a story.srt (5.0 KB)
  • 03 - Leverage exploratory and explanatory visualizations.srt (4.6 KB)
  • 04 - Choose a medium.srt (3.1 KB)
  • 07 - Putting it all together.mp4 (14.0 MB)
  • 02 - Visual best practices Part 2.mp4 (9.1 MB)
  • 01 - Visual best practices Part 1.mp4 (8.1 MB)
  • 06 - What's in a story.mp4 (6.8 MB)
  • 05 - Storyboarding.mp4 (6.1 MB)
  • 03 - Leverage exploratory and explanatory visualizations.mp4 (4.8 MB)
  • 04 - Choose a medium.mp4 (4.5 MB)
03 - 2. Breaking Down the Problem Statement
  • 02 - Get familiar Domain.srt (7.7 KB)
  • 01 - Define the problem The three Ds.srt (1.2 KB)
  • 05 - Get familiar Deliverable.srt (5.6 KB)
  • 04 - Get familiar Data.srt (4.8 KB)
  • 06 - Set the right expectations.srt (4.3 KB)
  • 03 - Domain Applied.srt (4.2 KB)
  • 01 - Define the problem The three Ds.mp4 (14.2 MB)
  • 02 - Get familiar Domain.mp4 (8.6 MB)
  • 06 - Set the right expectations.mp4 (6.2 MB)
  • 05 - Get familiar Deliverable.mp4 (4.9 MB)
  • 04 - Get familiar Data.mp4 (4.6 MB)
  • 03 - Domain Applied.mp4 (4.3 MB)
04 - 3. Data Collection, Cleaning, and Transformation
  • 02 - Read in data from a CSV file.srt (7.0 KB)
  • 04 - General cleaning techniques High-level checks.srt (6.1 KB)
  • 03 - General cleaning techniques.srt (1.9 KB)
  • 06 - Data transformations Binning.srt (4.4 KB)
  • 01 - Getting set up in Codespaces.srt (3.5 KB)
  • 05 - General cleaning techniques Missing values.srt (3.4 KB)
  • 02 - Read in data from a CSV file.mp4 (11.7 MB)
  • 04 - General cleaning techniques High-level checks.mp4 (10.5 MB)
  • 06 - Data transformations Binning.mp4 (9.1 MB)
  • 05 - General cleaning techniques Missing values.mp4 (7.8 MB)
  • 01 - Getting set up in Codespaces.mp4 (4.9 MB)
  • 03 - General cleaning techniques.mp4 (2.7 MB)
  • TutsNode.net.txt (0.1 KB)
  • [TGx]Downloaded from torrentgalaxy.to .txt (0.6 KB)
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Description


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.

Last Updated 3/2023



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Practical Python for Data Professionals

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368.5 MB
seeders:44
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Practical Python for Data Professionals

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