The Top 10 Online Courses For Data Science And Data Visualisation

Data scientists need to be proficient in data visualisation in order to successfully communicate complicated discoveries. Gaining proficiency in data visualisation has grown in value as the need for data professionals rises. The top 10 online courses that enable people to become proficient in data visualisation for data science are examined in this article.

1. Duke University’s course “Data Visualisation and Communication with Tableau” is available on Coursera: It gives students practical experience with Tableau, a top data visualisation application. In addition to improving their communication skills, participants learn how to produce powerful visualisations and present an engaging data-driven narrative.

2. “Data Visualisation and D3.js” – Udacity: This course explores the foundations of web-based data visualisation offered by Udacity. D3.js, a JavaScript package for creating dynamic, interactive data visualisations in web browsers, is mastered by students.

3. From Udemy, the “Data Science and Machine Learning Bootcamp with R”: This Udemy course, taught by Jose Portilla, covers the principles of data science and includes in-depth parts on data visualisation using R. Participants gain knowledge about how to use the well-known ggplot2 library to produce powerful visualisations.

4. “Data Science and Machine Learning Bootcamp with Python” – Udemy: This Jose Portilla course, another gem from Udemy, focuses on Python for data science. It gives prospective data scientists a strong foundation by covering a lot of ground on data visualisation with tools like Matplotlib and Seaborn.

5. Coursera’s “Applied Data Science with Python Specialisation”: This specialisation, which is available on Coursera from the University of Michigan, addresses several facets of applied data science. Python-based data visualisation methods are the focus of the specialization’s “Applied Plotting, Charting & Data Representation in Python” course.

6. “MicroMasters Programme for Data Visualisation” – edX: The University of California, Irvine offers a thorough set of courses on data visualisation ideas, strategies, and technologies through its Data Visualisation MicroMasters Programme on edX. Participants receive practical Tableau and D3.js experience.

7. “Storytelling with Data” – LinkedIn Learning: The narrative component of data visualisation is the main topic of Cole Nussbaumer Knaflic’s LinkedIn Learning course. It instructs students on how to produce powerful visuals that captivate a variety of viewers and deliver a gripping tale.

8. “Visualising Data with Python” – DataCamp: This course is available on DataCamp’s interactive learning platform. It focuses on using Python to visualise data. By practicing with Matplotlib and Seaborn, participants can become proficient in the art of producing lucid and perceptive visualisations.

9. Coursera’s “Advanced Excel for Data Science”:
Excel is still an effective tool in the data scientist’s toolbox, even though it may not be used only for data visualisation. Advanced Excel concepts are covered in this Macquarie University Coursera course, which includes data visualisation through the use of charts and graphs.

10. Coursera – “Data Visualisation for All”:
This course, which is available on Coursera and is taught by the University of Illinois, attempts to make data visualisation affordable for anyone. Regardless of their level of technical expertise, learners may produce powerful visualisations because to its coverage of basic concepts and procedures.

In summary, data scientists highly value the capacity to communicate ideas through engrossing visuals. There are many online courses available nowadays that suit different skill levels and learning styles. These courses offer a strong foundation for understanding the art and science of data visualisation, regardless of your preference to specialise in a specific tool like Tableau, learn programming languages like Python and R, or concentrate on the storytelling component of data visualisation.