Course Information
Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
1 Hour(s) 5 Minute(s)
Language
English
Taught by
James Thomson
Certificate
- Available
- *The delivery and distribution of the certificate are subject to the policies and arrangements of the course provider.
Rating
3 views
Course Overview
Learn how to analyze and visualize data by using Python libraries such as Plotly, Seaborn, Matplotlib, Pandas, and NumPy
This course will provide an introduction to the fundamental Python tools for effectively analyzing and visualizing data. You will have a strong foundation in the field of Data Science!
You will gain an understanding of how to utilize Python in conjunction with scientific computing and graphing libraries to analyze data, and make presentable data visualizations.
This course is designed for both beginners with some basic programming experience or experienced developers looking to explore the world of Data Science!
In this course you will:
- Learn how to create and analyze data arrays using the NumPy package
- Learn how to use the Pandas library to create and analyze data sets
- Learn how to use Matplotlib, and Seaborn to create professional, eye-catching data visualizations
- Learn how to use Plotly to create interactive charts and plots
You will also get lifetime access to all the video lectures, detailed code notebooks for every lecture, as well as the ability to reach out to me anytime for directed inquiries and discussions.
Course Content
- 7 section(s)
- 7 lecture(s)
- Section 1 Introduction and Setup
- Section 2 Data Analysis - NumPy
- Section 3 Data Analysis - Pandas
- Section 4 Data Visualization - Matplotlib
- Section 5 Data Visualization - Seaborn
- Section 6 Data Visualization - Plotly
- Section 7 Exercises
What You’ll Learn
- Create presentable data visualizations with Python
- Learn how to analyze data with Python
- Make interactive data visualizations using the Plotly module
- Learn how to create plots from your data using Matplotlib, and Seaborn
- Analyze data using the Pandas library to create and structure data
- Analyze data using the NumPy library to create and manipulate arrays
- Use the Jupyter Notebook Environment
Skills covered in this course
Reviews
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PPhilip Thomas
Very good course, simple and defined so anyone can go through, also keeping the work after has helped me to recap on the points raised and taught, well done.
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RRobby Snitkof
Very disappointed. The instructor gives absolutely no explanation as to why certain functions take a specific syntax, benefits of one function or package over another, etc. It's completely devoid of anything beyond a surface level demonstration of how to use certain packages for visualizing data. It's worth approximately $0 and none of anyone's time.
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TTadeu Barradas Badaró
This course delivers what it promisses - an introduction to data analysis tools in Python - in a fast and simple way. It has resources and exercises with which one can practice.
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NNeetu Dey
small codes defined well which we use mostly in huge codes most of the times without knowing the purpose. The codes & the purpose of libraries have been explained really well.Thanks.
