Why this course?

Description

Data Visualization using Python is a course designed to teach you how to visualize data in a way that communicates insights effectively. In this course, you will learn the principles of data visualization and how to use Python libraries such as Matplotlib, Seaborn, and Plotly to create interactive visualizations, charts, and graphs. The course covers the basics of data cleaning and preparation, explores different visualization techniques, and shows you how to create custom visualizations. By the end of the course, you will have gained the skills and knowledge to create effective visualizations to help you gain insights from your data.

Total Duration: 5 Hrs | Modules: 4  | Assignments: 4 | Projects – 2

Module 1:  Introduction for data visualization  (30 minutes)

Learning objective: Understand the principles and best practices of data visualization. Learn how to identify the appropriate visualization types for different types of data and analytical tasks.

Assignment -01:- What is data visualization and list various applications 

Module 2: Matplotlib libraries for visualization  (2 hours)

Learning objective 

Matplotlib is a Python library used for creating high-quality, customizable visualizations of data. It is one of the most popular visualization libraries and is known for its flexibility and ease of use. With Matplotlib, you can create a wide range of static and interactive visualizations, including line charts, scatterplots, histograms, and more. You can customize your visualizations with a range of aesthetics, including colors, sizes, and fonts, and even export your visualizations in various file formats. Overall, Matplotlib is an essential tool for anyone working with data in Python who needs to create compelling and informative visualizations.

Applying Data visualization for large datasets.

Assignment -02:- implementation of various features using matplotlib

Module 3: Seaborn libraries for visualization (2 hour)

Key Learning Objectives:  Seaborn is a Python data visualization library that provides a high-level interface for creating informative and attractive statistical graphics. The objective of Seaborn is to make it easy to explore and understand complex data by providing a range of built-in visualization types and customization options.

Assignment-03: what is the importance of seaborn library file in data visualizations.

 

Module 4: Difference between seaborn and matplotlib (30 min)

Key Learning Objectives:

Understand the key differences in design philosophy and functionality between Seaborn and Matplotlib.

Learn when to use each library for different types of data visualizations, and how to integrate them effectively in your data analysis workflows.

Assignment -04:- customize the plotting of various features using matplotlib and seaborn library.

 

For Related courses

After completing the course, automatically e-certificate will be generated for the participants.

 

Software / Tools:  

Anaconda Navigator Software Tool:

https://www.anaconda.com/products/distribution

Python Programming Installation link:-

https://www.python.org/