Learn Programming in Python! – Data Visualization in Python by Nirmali Khound Baruah is an introductory course to Data Visualization methods in Python, using PyPlot from Matplotlib. It is a good concise course that showcases the Matplotlib API, teaching different functions and methods that are commonly used, great for anyone starting their foray into Data Visualization.
Read more: 5 BEST Online Courses to Learning Computer Science in 2023
Table of Contents
- Course Overview
- Who This Course Is For
- The Breakdown
- Conclusion
- What could I do with the knowledge in this course?
Course Overview
- Skill Level: Intermediate
- Price: Free
- Duration: 30 Minutes
- Material: 6 Sections, 7 Video Lectures, 1 Quiz, 1 Short Assignment
- Students enrolled at the time of taking: ~5000
- Course requirements/prerequisites: Some basic knowledge of Python and using an IDE
- Topics Covered:
- Concepts of Data Visualization
- Using Pyplot of Matplotlib Library
- Creating different types of charts such as Pie, Bar and Scatter Charts
My Rating
Who This Course Is For
This course is great for anyone who is keen on getting started on Data Visualization in Python. It teaches several basic functions and syntax needed to get started. This course should be treated as a good starting point, but will not be sufficient to becoming a proficient data analyst etc. Some basic knowledge of python and being comfortable with using an IDE will be required for this course.
The Breakdown
Teacher and Class material – 4/5
Nirmali Khound Baruah is a teacher with over 25 years of experience teaching in different schools and colleges, who “teaches complex things in much [easier] way”. This is very true in the course, where her explanations are succint and straight to the point, which allows for a short and sweet 30 minute course.
The course provides everything a programmer would need to know to just get started transforming their first few sets of data into presentable material. The video lectures are great for showcasing how different functions in Pyplot work and the assignment to end the course does a great job of reviewing all of the material taught.
If there were any feedback, it would have been great if the course provided some summary notes as it is a very content heavy course that revolves around learning functions and the matplotlib API as opposed to learning new concepts, so a summary sheet would be useful here. Even for students who make their own notes, they may miss out some content here and there. Nevertheless, the course still provides all that is necessary.
Content – 4.5/5
The course is split into 6 sections, namely:
- Welcome to the course
- Line Charts and Scatter Charts
- Bar Charts
- Examples of Bar Charts
- Pie Charts
- Review Quizzes and assignment
All 6 sections total to 7 video lectures of 30 minutes altogether, with a review quiz and a short assignment to end.
The course mainly teaches how to program in python using the matplotlib and pyplot, showcasing the different ways of visualising data through different types of charts to then be analysed. Do not confuse it for a course that teaches theory on how data analysis or data simplification.
She goes through different kind of useful matplotlib functions such as plot, xlabel/ylabel, show and many more. It is a great introductory course to get started programming data visualisation
It is beneficial for anyone who needs help discovering the functions of Pyplot, rather than someone who is looking to learn data visualisation techniques. It serves as more of a handbook for the Pyplot than a class on how one should be doing data visualisation. It would remind someone of learning CSS.
Engagement – 4/5
The course consists of short format videos of which she does live demonstrations through screen recordings, making it very easy to follow along and students can explore for themselves.
As the videos are short format, the content is easily digestible and the teacher’s explanations are clear and concise.
The assignment at the end encapsulates everything that was taught in the course very well and serves as excellent review material. The questions are well-constructed and cover everything taught in the course.
If there was one small gripe with the course, it would be that she uses a very instructive tone that may be monotonous to some, but given that it is a content-heavy topic, it is understandable to be taught this way. Nevertheless, it fulfils the job of conveying all the necessary information.
Pace – 4.5/5
For a short course, it conveys all of the information at a good pace, not too draggy and not too fast that it skims over examples. Each video is straight to the point and allows for all the content to be covered in such a short amount of time.
No issues in terms of the pace of this course.
Value – 4.5/5
In terms of time and effort needed to invest into completing this course, the value received from just 30 minutes is great. As a introductory course, it does just the job needed to kickstart your journey into Data Visualization and/or Data science with python. Nothing more needs to be said here.
Conclusion
If you are looking for a course to get you started creating Data Visualization material in python, this is a great course to get started. In just 30 minutes, you will be able to create several types of plots and know the functions to adjust their settings. With little time investment and the amount of return from it, I would recommend this course to anyone interested in Data science in python.
What could I do with the knowledge in this course?
- Different types of charts
- Functions for plotting
Take these concepts and import mock data from mockaroo.com to plot all sorts of charts to visualise trends!
Read more: Python For Beginners, Udemy [In-Depth Course Review]
