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Python for Data Science and Machine Learning Essential Training Part 2

This is the repository for the LinkedIn Learning course Python for Data Science and Machine Learning Essential Training Part 2. The full course is available from LinkedIn Learning.

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If you are a working professional who wants to use business data to make improved decisions through predictive analytics, this course can help you. Lillian Pierson—engineer, CEO, and the head of product at Data-Mania—guides you through a robust combination of basic data science coding experience, demonstrations, challenges, solutions, and exercises that you can quickly apply in customized data analyses and analytics projects. Learn best practices for data cleaning, data visualization, data analysis, and Python programming.

By the end of the course, you will be able to use Python to:

  • Clean, reshape, reformat, and describe data
  • Generate data visualizations for data presentation and visual exploratory analysis
  • Identify and remove outliers
  • Perform simple data analysis
  • Source, scape, and analyze data from the internet
  • Generate collaborative analytics assets using Plot.ly

Instructor

Lillian Pierson, P.E.

Engineer, CEO, and Head of Product at Data-Mania

Check out my other courses on LinkedIn Learning.

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This repo is for LinkedIn Learning course: Python for Data Science and Machine Learning Essential Training Part 2

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