8 Best Python Data Visualization Courses [2020]

best python data visualization course class certification training online

Our team of global experts compiled this list of Best Python Data Visualization Courses, Classes, Tutorials, Training, and Certification programs available online for 2020. This list includes both free and paid courses to help you learn different concepts of Python Data Visualization. Also, it is ideal for beginners, intermediates, as well as experts.

 

8 Best Python Data Visualization Courses [2020]

1. Learn Python for Data Analysis and Visualization (Udemy)

If you are entirely new to Python, then this course will provide you with all the resources for learning Python and effectively use it for analyzing and visualizing data. Taking this course will help you get a clear understanding of Python programming and how to use it in aggregation with scientific computing modules and libraries for analyzing data. Moreover, you will learn how to work with different data formats within Python, such as MS Excel Worksheets, JSON, HTML, etc. After finishing the course, you will get a certificate of completion that can be used with your LinkedIn profile and resume to showcase your skills.

 

Key USPs –

– A practical course that will give you a clear understanding of Python programming and how to use it for data analysis and visualization

– Learn how to create and manipulate arrays with NumPy and Python, as well as how to use Pandas for creating and analyzing data sets

– Know the process of using matplotlib and seaborn libraries for creating beautiful data visualizations with a clear understanding of Machine Learning and Scikit Learn

– Included with 100+ lectures, 20 hours of information, more than 100 examples of Python code notebooks, quizzes, practice exercises, and much more to help you enhance your knowledge and skills

 

Duration: 2 months. 3-4 hours/week

Rating: 4.3 out of 5

You can Sign up Here

 

Review: Yes. Great intro to machine learning concepts (Section 10) and beginner-level implementations of them in Python. – Angel Sarmiento

 

 

2. Data Visualization with Python (Coursera)

If you want to learn how to explain the insight obtained from the analysis of large datasets with visualizations, then this course can help you in your quest. It is an introductory course designed by an experienced faculty of the IBM organization to help individuals learn how to represent both small and large-scale data with data visualization. With this course, you will learn how leveraging software for visualizing data can also be used to extract information, better understand the data, and make more effective decisions. This course is entirely focused on teaching you how to take data from a glance and represent it in a form that makes sense to people.

 

Key USPs –

– Learn the most common techniques and methods that can be used to analyze and visualize data with Python programming

– Get introduced to various data visualization tools and some of the best practices for creating plots and visuals with Python

– Learn how to create plots with specialized visualization tools like Matplotlib, histograms, bar charts, and many more

– Apply your learned skills with hands-on projects, graded quizzes, assignments, and readings while studying from your own pace

– Get 7 days free trial with the opportunity to enroll yourself in other best data visualization courses

 

Duration: 10 hours

Rating: 4.6 out of 5

You can Sign up Here

 

Review: This course gives very well knowledge about different types of visualization techniques and helps to start with visualization. Coursera provided an amazing course with an amazing instructor. – RB

 

 

3. Introduction to Data Visualization in Python (DataCamp)

If you already have sufficient knowledge of using Python for data science, then this course can provide you with a stronger foundation in data visualization in Python. Enrolling into this course will help you get a broader coverage of the Matplotlib library and an overview of seaborn, which is used as a package for statistical graphics. The course includes four chapters, amongst which the first chapter is absolutely free to enroll, which means you don’t have to pay any amount to go through and learn the content. Completing the course with given assignments will provide you with a certificate of completion that can be used to showcase your skills to employers.

 

Key USPs –

– Learn the fundamental concepts of using Python for data visualization, such as customizing graphics, statistical graphics, distributions, regressions, etc.

– Get a clear understanding of customizing plots with Matplotlib, including overlaying plots, making subplots, adding legends and annotations, controlling axes, and using different plot styles

– Learn various techniques for visualizing two-dimensional arrays, including the use, presentation, and orientation of grids for representing two-variable functions

– Understand how plots can be customized for generating histograms of image pixel intensities and improve image contrast through histogram equalization

 

Duration: 4 hours

Rating: 4.5 out of 5

You can Sign up Here

 

 

4. Python for Data Science with Examples (Udemy)

Individuals who have no prior experience in using Python for data science can take help from this course. It is a step-by-step course that will guide from the basics of Python to using it for advanced data analysis and visualization. The course is included with multiple videos, and after completing each video lecture, you will learn a new valuable concept that can be applied in real-life right away. The course is designed by Kirill Eremenko, who is a data science management consultant and has more than ten years of experience in providing python training to various individuals. After completing this course, you can enroll yourself in some of the best Python data science courses to improve your skills and experience.

 

Key USPs –

– An intermediate course that is designed for all skill levels and individuals who don’t have any prior experience in Python programming

– Packed with real-life analytical challenges that will help you learn how to solve complex problems in data science

– Learn how to program in python at a good level while earning the core principles of programming

– Understand some advanced concepts of Python programming, such as how to code in Jupiter Notebooks, how to create variables, etc.

 

Duration: 11-12 hours

Rating: 4.6 out of 5

You can Sign up Here

 

Review: I was good, but I was looking for more regress training in real-life problems of data science, which will help me in my resume. – Sarad Mishra

 

 

5. Data Visualization on Desktop with Python and Bokeh (Udemy)

If you want to learn how to impress your clients with impressive and attractive data visualization on the browser with Bokeh, then this course from Udemy is an ideal option for you. It is a step-by-step course that will help you master Bokeh – a python library that is used to build advanced and modern data visualization web applications. You will begin with learning how to plot simple datasets, and then move on to creating vibrant and beautiful data visualization web apps that can plot data in real-time and enable web users to interrelate and change the behavior of your plots. It is included with exercises that will help you check your skills during the course.

 

Key USPs –

– An absolute perfect course for data scientists, data analysts, and data managers who want to make an impression on their clients or employers with their data visualization using Bokeh

– Designed by an expert instructor of Udemy who will assist you during the course to understand complex concepts of Python

– Gain advanced skills to visualize data in a way that excites the audience and eventually sells your product or idea in an easy way

– Get access to various data samples with additional examples that will enforce your Bokeh skills

 

Duration: 6-7 hours

Rating: 4.6 out of 5

You can Sign up Here

 

Review: Course is good, but there is a lack of assistance. I asked a question weeks ago and nobody has entertained it yet. – Pawan Kumar

 

 

6. Visualize Data with Python (edX)

This course is created to help you learn how data visualization plays an essential job in the illustration of both small and large-scale data. Taking this course will enable you to learn how to become a data scientist who has the ability to tell a powerful story, visualizing data and findings in an appropriate and stimulating way. It is designed by the IBM organization, so when you sign up for the course, you will get the opportunity to create your own data science projects and collaboration with other data scientists with IBM Watson Studio. The course is included with various video lectures, exercises, and hands-on projects to help you equip better knowledge of the subjects.

 

Key USPs –

– Get introduced to various concepts of data visualization, such as Matplotlib, plotting with Matplotlib, line plots, and many more

– Learn about basic and specialized visualization tools like Area Plots, Bar Charts, Pie Charts, Scatter Plots, Bubble Plots, Histograms, etc.

– Learn to use some of the most effective and useful data visualization libraries in Python, such as Matplotlib, Seaborn, and Folium of presenting data

– Receive an instructor-signed certificate with the IBM logo to verify your achievements and increase your job prospects

 

Duration: 5 weeks

Rating: 4.5 out of 5

You can Sign up Here

 

 

7. Data Visualization with Python and Matplotlib (Udemy)

If you want to learn how to analyze big data for maximum benefits and output, then this course from Udemy is an ideal option for you. Taking this course will help you learn how to create easy to read, simple to understand graphs, charts, and other visual representation of data with data visualization. You will get a clear understanding of Big Data Python while learning how to visualize multiple forms of 2D and 3D graphs, loading and organizing data from various sources of visualization, etc. The course comes with multiple sets of exercises, quizzes, and hands-on projects designed to help you analyze what you have learned so far in the program.

 

Key USPs –

– An extensive course that covers almost every major chart that Matplotlib is capable of providing for data visualization

– Provides a step-by-step approach for creating line graphs, scatter plots, stack plots, pie charts, bar charts, 3D lines, geographic maps, live-updating graphs, and much more

– Learn how to import data from both CSV and NumPy, as well as cover more advanced features like customized spines, styles, annotations, averages, and indicators, etc.

– Learn three of the most extensive tools used for data visualization – Python 3, Matplotlib, and IDLE

 

Duration: 6-7 hours

Rating: 4.0 out of 5

You can Sign up Here

 

Review: Everything is clear, and the examples of the script are helpful to understand the topics. – Paolo Roberto Di Palma

 

 

8. Data Visualization with Python (Cognitive Class)

Individuals who want to learn how to tell a convincing story, visualize data, and findings in an approachable way with Python can learn from this course. Taking this course will allow you to learn how data visualization can be used for data representation to interactively and efficiently convey insights to clients. You will get a clear understanding of creating impressive graphics and charts and customizing them to make them more productive and more attractive to your audience. Moreover, you will also learn how using a tool for data visualization can also help you extract information and make more effective decisions.

 

Key USPs –

– A practical course that gives you a useful approach for analyzing and visualizing data to impress your clients and customers

– Designed by expert instructors of IBM who have years of experience in providing data visualization and python coaching

– Get a clear understanding of using various Python programming concepts that can be used to make your data visualization more appealing

– Learn about specialized and advanced visualization tools, such as Waffle Charts, Box Plots, Bubble Plots, Seaborn and Regression tools, and many more

– Receive a shareable certificate of completion that can be used to showcase your skills to employers

 

Duration: 10 hours

Rating: 4.5 out of 5

 

Those were some of the best Python Data Analysis courses available online. Do have a look around to see more data science courses on our website.