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Courses>Database Design & Development>Graph plotting in Python for scientific Journals & papers
DevelopmentGraph plotting in Python for scientific Journals & papers
Price:Free
Length:1.5 hours
Content type:video
level:all levels
Updated:26 February 2024
Published:21 August 2022
Similar courses
Opportunities
Courses>Database Design & Development>Graph plotting in Python for scientific Journals & papers
Graph plotting in Python for scientific Journals & papers
4.9 (750.0)
1.5 hours
750 students
What you will learn
1You will learn how to use Python to create stunning charts and data visualizations
2Create complex data visualizations using Matplotlib
3Create custom Matplotlib settings for journals, and conference plots
4Student, researchers, data scientist and teachers who wants to elevate their figures to the next level
5Explore dimensionality of the data, data interpretation
6Import multiple datasets and plot
Target audiences
1Students (undergrad and graduate) keen in data visualization
2Researchers, data scientists
3Anyone who wants to learn data visualization
4Explore dimensionality of the data
5PhD's and Postdoc's
Requirements
1No prior knowledge in programming is required
2You will need a desktop or a laptop computer
3People curious about data analysis, data visualization, or data science
FAQ
You can view and review the lecture materials indefinitely, like an on-demand channel.
Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don't have an internet connection, some instructors also let their students download course lectures. That's up to the instructor though, so make sure you get on their good side!
Description

Welcome to the finest data visualization or graph plotting course using Matplotlib  on the web, in my viewpoint. The technical skills you learn in this course will help you advance in your career as a data scientist, researcher, or science student. This course is designed for students of science & engineering interested in producing top-notch scientific graphics as well as researchers and data scientists. First,  I'll give you a brief overview of Python. Along with that, I'll cover the essential packages, such as Numpy, Pandas, and Matplotlib, that we'll use often in this course. Before getting into more complex preparation for posters and scientific publications, I'll start with the fundamentals. At the completion of this course, You will be able to plot any form of data from different varieties of data files.

In this course, you will learn:

  • Working with JupyterLab

  • Create complex data visualizations using Matplotlib

  • Import and extract data from CSV, TXT, MAT, and H5 files

  • Import multiple datasets and plot

  • Create custom Matplotlib settings for journals, and conference plots

  • 2D colormap plots and customization

  • 3D plots and customization

  What distinguish this course from the hundreds of others available online?

While most online courses follow simply descriptive material and take endless hours, this short course highlights the necessity of visually appealing plots as a need for any kind of scientific or professional presentation, as well as the integration of visualizations from various datasets. Instead of spending endless hours on hypothetical data, this combines the ideas, tactics, and crucial settings.

Similar courses
Opportunities
Make the most out of your online education
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Careertail
Courses>Database Design & Development>Graph plotting in Python for scientific Journals & papers
DevelopmentGraph plotting in Python for scientific Journals & papers
Price:Free
Length:1.5 hours
Content type:video
level:all levels
Updated:26 February 2024
Published:21 August 2022
Similar courses
Opportunities
Courses>Database Design & Development>Graph plotting in Python for scientific Journals & papers
Graph plotting in Python for scientific Journals & papers
4.9 (750.0)
1.5 hours
750 students
What you will learn
1You will learn how to use Python to create stunning charts and data visualizations
2Create complex data visualizations using Matplotlib
3Create custom Matplotlib settings for journals, and conference plots
4Student, researchers, data scientist and teachers who wants to elevate their figures to the next level
5Explore dimensionality of the data, data interpretation
6Import multiple datasets and plot
Target audiences
1Students (undergrad and graduate) keen in data visualization
2Researchers, data scientists
3Anyone who wants to learn data visualization
4Explore dimensionality of the data
5PhD's and Postdoc's
Requirements
1No prior knowledge in programming is required
2You will need a desktop or a laptop computer
3People curious about data analysis, data visualization, or data science
FAQ
You can view and review the lecture materials indefinitely, like an on-demand channel.
Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don't have an internet connection, some instructors also let their students download course lectures. That's up to the instructor though, so make sure you get on their good side!
Description

Welcome to the finest data visualization or graph plotting course using Matplotlib  on the web, in my viewpoint. The technical skills you learn in this course will help you advance in your career as a data scientist, researcher, or science student. This course is designed for students of science & engineering interested in producing top-notch scientific graphics as well as researchers and data scientists. First,  I'll give you a brief overview of Python. Along with that, I'll cover the essential packages, such as Numpy, Pandas, and Matplotlib, that we'll use often in this course. Before getting into more complex preparation for posters and scientific publications, I'll start with the fundamentals. At the completion of this course, You will be able to plot any form of data from different varieties of data files.

In this course, you will learn:

  • Working with JupyterLab

  • Create complex data visualizations using Matplotlib

  • Import and extract data from CSV, TXT, MAT, and H5 files

  • Import multiple datasets and plot

  • Create custom Matplotlib settings for journals, and conference plots

  • 2D colormap plots and customization

  • 3D plots and customization

  What distinguish this course from the hundreds of others available online?

While most online courses follow simply descriptive material and take endless hours, this short course highlights the necessity of visually appealing plots as a need for any kind of scientific or professional presentation, as well as the integration of visualizations from various datasets. Instead of spending endless hours on hypothetical data, this combines the ideas, tactics, and crucial settings.

Similar courses
Opportunities
Make the most out of your online education
Careertail
Copyright © 2021 Careertail.
All rights reserved
Quick Links
Get StartedLog InAbout UsCourses
Company
BlogContactsPrivacy PolicyCookie PolicyTerms and Conditions
Stay up to date
Trustpilot