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Artificial Intelligence & Machine Learning: Level-3

Learn to Master Data Visualization and perform Exploratory Data Analysis (EDA) using Python, Matplotlib and Seaborn

  • 2500
  • 25000
  • Course Includes
  • 3 Hour Video Class
  • Downloadable Resources
  • Free Certificate of Completion
  • 1 Year Access

Enrol and get access to the full course.

What you will learn

  • Perform Exploratory Data Analysis (EDA) for any Dateset
  • Visualise Data using a Variety of Charts Types
  • Learn Matplotlib and Seaborn Fundamentals
  • Creating Bar, Grouped Bar, Stacked Bar, Lollipop charts
  • Creating Pie, Tree-map charts
  • Creating Line, Area, Stacked Area charts
  • Creating Histogram, Density, Box-and-Whisker, Swarm charts
  • Creating Scatter, Correlogram, Heat-Map, Hexbin-Map charts


  • You should be knowledgeable in Python Basic Syntax, skilled working with the Pandas Library - Loading Datasets and Manipulating Data in a Data Frame. It is recommended to start with the Level 1 and Level 2 of the "Artificial Intelligence & Machine Learning" training program


Unleash the Power of ML

Machine Learning is one of the most exciting fields in the hi-tech industry, gaining momentum in various applications. Companies are looking for data scientists, data engineers, and ML experts to develop products, features, and projects that will help them unleash the power of machine learning. As a result, a data scientist is one of the top ten wanted jobs worldwide!

This training program is designed for beginners looking to understand the theoretical side of machine learning and to enter the practical side of data science. The training is divided into multiple levels, and each level is covering a group of related topics for a continuous step by step learning path.

Level 3 – Data Visualization with Matplotlib and Seaborn

The third course, as part of the training program, aims to help you to perform Exploratory Data Analysis (EDA) by visualizing a dataset using a variety of charts. You will learn the fundamentals of data visualization in Python using the well-known Matplotlib and Seaborn data science libraries, including:

⚫ Matplotlib fundamentals

⚫ Seaborn fundamentals

⚫ Selecting the right chart for the right job

⚫ Bar, Grouped Bar, Stacked Bar, Lollipop charts

⚫ Pie, Three-map charts Line, Area, Stacked Area charts

⚫ Histogram, Density, Box-and-Whisker, Swarm charts

⚫ Scatter, Correlogram, Heatmap, Hexbin charts

Course Content

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preview 4min
Our Overall Learning Path
preview 3min
How to Practice?
Matplotlib - Overview
Matplotlib – Figures, Axes
Matplotlib – The OO and Pyplot Interfaces
Matplotlib – APIs Reference Review
Seaborn – Overview
Seaborn – Figure and Axes-level Functions
Seaborn - Chart Customization
Seaborn – API Reference Review
A little bit about NumPy
The Right Chart for the Right Job