Data Analysis with Python - Full Course for Beginners (Numpy, Pandas, Matplotlib, Seaborn)

Learn Data Analysis with Python in this comprehensive tutorial for beginners, with exercises included! NOTE: Check description for updated Notebook links. Data Analysis has been around for a long time, but up until a few years ago, it was practiced using closed, expensive and limited tools like Excel or Tableau. Python, SQL and other open libraries have changed Data Analysis forever. In this tutorial you'll learn the whole process of Data Analysis: reading data from multiple sources (CSVs, SQL, Excel, etc), processing them using NumPy and Pandas, visualize them using Matplotlib and Seaborn and clean and process it to create reports. Additionally, we've included a thorough Jupyter Notebook tutorial, and a quick Python reference to refresh your programming skills. 💻 Course created by Santiago Basulto from DataWars 🔗 Check out all Data Science courses from DataWars: https://datawars.io/ref=fcc ⚠️ Note: Instead of loading the notebooks on notebooks.ai, you should use Google Colab instead. Here are instructions on loading a notebook directly from GitHub into Google Colab: https://colab.research.google.com/github/googlecolab/colabtools/blob/master/notebooks/colab-github-demo.ipynb#

Free1 lesson4h 22mBeginner

by freeCodeCamp.org

April 2020

Checked 2 days ago

Free

This course is free and published on YouTube. The channel is its author; we organise it and check that the videos still play.

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This course includes

  • 4h 22m of video
  • 1 lessons
  • Level: Beginner
  • Spoken in English
  • Your place is remembered
  • Free in full, no card

Lessons

1 sections · 1 lesson · 4h 22m total length

What you need

  • No prior experience: this course starts from zero.

Description

Learn Data Analysis with Python in this comprehensive tutorial for beginners, with exercises included! NOTE: Check description for updated Notebook links. Data Analysis has been around for a long time, but up until a few years ago, it was practiced using closed, expensive and limited tools like Excel or Tableau. Python, SQL and other open libraries have changed Data Analysis forever. In this tutorial you'll learn the whole process of Data Analysis: reading data from multiple sources (CSVs, SQL, Excel, etc), processing them using NumPy and Pandas, visualize them using Matplotlib and Seaborn and clean and process it to create reports. Additionally, we've included a thorough Jupyter Notebook tutorial, and a quick Python reference to refresh your programming skills. 💻 Course created by Santiago Basulto from DataWars 🔗 Check out all Data Science courses from DataWars: https://datawars.io/ref=fcc ⚠️ Note: Instead of loading the notebooks on notebooks.ai, you should use Google Colab instead. Here are instructions on loading a notebook directly from GitHub into Google Colab: https://colab.research.google.com/github/googlecolab/colabtools/blob/master/notebooks/colab-github-demo.ipynb#

Who this course is for

  • Anyone starting Python from nothing.

Those two are our reading of the course's level. The description is the author's own.

Data Analysis with Python - Full Course for Beginners (Numpy, Pandas, Matplotlib, Seaborn), by freeCodeCamp.org