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Data Analysis and Visualization with Python for beginners
Practical Hands-on Data Analysis and Visualization using Python and Jupyter Notebook.

This Course Includes
udemy
5 (63 reviews )
1h 48m
english
Online - Self Paced
professional certificate
Udemy
About Data Analysis and Visualization with Python for beginners
Data is everywhere. That means more companies are tracking, analysing, and using the insights they find to make better decisions.
Python
is a popular programming language. It is used for:
web development (server-side),
software development,
mathematics,
Data Analysis
Data Visualization
System scripting.
What can Python do?
Python can be used on a server to create web applications.
Python can be used alongside software to create workflows.
Python can connect to database systems. It can also read and modify files.
Python can be used to handle big data and perform complex mathematics.
Python can be used for rapid prototyping, or for production-ready software development.
Python can be used for data analysis and visualization.
Data analysis
is the process of analysing, interpreting, data to discover valuable insights that drive smarter and more effective business decisions. Data analysis tools are used to extract useful information from business and other types of data, and help make the data analysis process easier.
Data visualisation
is the graphical representation of information and data. By using visual elements like charts, graphs and maps, data visualisation tools provide an accessible way to see and understand trends, outliers and patterns in data. The
Jupyter Notebook
is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations and narrative text. Uses include: data cleaning and transformation, numerical simulation, statistical modelling, data visualization, machine learning, and much more.
What You Will Learn?
- Data Analysis .
- Data Visualization .
- Quantitative Visualization .
- Qualitative Visualization .
- Tabular Data .
- Jupyter Notebook Server Setup .
- Creating Jupyter Notebooks .
- Exploring Pandas DataFrame .
- Manipulating Pandas DataFrame.