Training: Data Analysis and Visualization with Python

Mode: Online Courses

Duration: 28 Hours (4 days)

Number of Participants: 15

Fee: 724 EUR

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  • Ability to analyze, visualize, and interpret their data using data mining tools such as Python Pandas, Matplotlib and Seaborn.
  • Familiarization with Data science tools, and installation: Jupyter Notebook as an integrated development environment.
  • Learning data wrangling & analysis with python pandas: hand-on skills training with practical examples and exercises.
  • Hand-on skills training with Matplotlib, Plotly and Seaborn for data visualization.

Target groups

Students, researchers, scientist, and graduates.

Course Detail

  1. Data collection and management
  2. Understanding the need for data analysis
  3. Familiarization with Jupyter Notebook – A tool for data analysis
  4. Introduction to Pandas data structure
  5. Pandas basic functionalities
  6. Descriptive statistics with Pandas
  7. Pandas Date Time operation
  8. Pandas text operation
  9. Pandas Functions
  10. Working with missing data
  11. Pandas iteration, indexing and sorting operation
  12. Pandas selection and aggregation
  13. Grouping, merging, concatenation and joining
  14. Data visualization fundamentals with Matplotlib
  15. Statistical chart with Matplotlib
  16. Data visualization with Seaborn
  17. Data visualization with Plotly

Learning outcomes

  • Participants will be able to use Python Pandas to explore data and conduct statistical analyses.
  • Participants will learn to present their data attractively in such a manner to allow their audiences understand their research using Matplotlib, Plotly and Seaborn.
  • Ability to use of Jupyter Notebook.

Installing Jupyter Notebook

Jupyter notebook is an open source web application that allows you do the following:

  • Produce and exploit documents containing live code, equations, visualizations & narrative texts
  • Data analysis and visualizations
  • Machine learning & deep Learning models implementation

Installation guide for windows:

  • Either Mozilla Firefox or Google Chrome works well.
  • Avoid MS Explorer (Although it works too).
  • Python 3, 64 bits

Download link:


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