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Learner Reviews & Feedback for Data Visualization with Python by IBM

4.5
stars
11,492 ratings

About the Course

One of the most important skills of successful data scientists and data analysts is the ability to tell a compelling story by visualizing data and findings in an approachable and stimulating way. In this course you will learn many ways to effectively visualize both small and large-scale data. You will be able to take data that at first glance has little meaning and present that data in a form that conveys insights. This course will teach you to work with many Data Visualization tools and techniques. You will learn to create various types of basic and advanced graphs and charts like: Waffle Charts, Area Plots, Histograms, Bar Charts, Pie Charts, Scatter Plots, Word Clouds, Choropleth Maps, and many more! You will also create interactive dashboards that allow even those without any Data Science experience to better understand data, and make more effective and informed decisions. You will learn hands-on by completing numerous labs and a final project to practice and apply the many aspects and techniques of Data Visualization using Jupyter Notebooks and a Cloud-based IDE. You will use several data visualization libraries in Python, including Matplotlib, Seaborn, Folium, Plotly & Dash....

Top reviews

LS

Nov 27, 2018

The course with the IBM Lab is a very good way to learn and practice. The tools we've learned in this module can supply a good material to enrich all data work that need to be presented in a nice way.

CJ

Apr 22, 2023

Learnt a lot from this visualization course. The one I found most interesting was making the dashboard. Although sometime the code and indentation are tedious, but this might be useful in the future.

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1201 - 1225 of 1,795 Reviews for Data Visualization with Python

By Michael J L

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Mar 25, 2020

Best of the 5 IBM Data Science Courses I've taken so far. Some problems connecting with the labs, but you can bypass these by downloading the ipynb's from cognitiveclass.ai.

By Konduru G

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Jul 30, 2019

It was very nice and brief course but it could have been better. Some other topics must be included and some more exploration of different properties needed to be addressed

By Michael L

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Jun 15, 2019

This course, although useful was difficult to follow at times. It did not get that into the Artist Layer of Matplotlib but the final project requires the student to use it.

By Elyass S

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May 23, 2021

It's an informative course, it even tested a student's perseverance and creativity in solving/bypassing various bugs. The final assignment was definitely an eye opener.

By Venkata S S G

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Jan 30, 2020

final assignment is tough. Everything else was decent and intuitive. Good jupyter notebooks and labs for practice were provided. Do practice all ungraded lab sessions.

By Christopher L

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Aug 2, 2019

Would've enjoyed the course more, if it got into the nitty gritty of annotations, but a comprehensive and decently delivered course nonetheless. Kudos to the IBM team.

By Julie D

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Dec 21, 2022

The learning was good - I had a really hard time with getting the IDE environment and labs/assignments to work well. Doing screenshots over and over is inefficient.

By Wesley C

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Oct 3, 2019

Just like the few previous Python courses by IBM - errors and typos have yet to be fixed. But other than that, it is a really good introduction into using Matplotlib.

By Tichaona M

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Sep 10, 2020

This is a very fascinating and demanding course when one follows all the Skills Network Lab exercises. The advanced visualization tools are worth the trouble!

By Neelam S

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Jan 3, 2020

Examples contained less python codes as compared to asked in final assignment. More python codes for visualization are to be conveyed.

Queries are not solved.

By Seymur D

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Jul 23, 2019

The course content was good, but final assignment needed more clarity in the what was demanded from the question. Lots of interpretation left for the student.

By Alexej Z

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Nov 1, 2018

Some tests are not comprehensible in their entirety and can only be carried out with a great deal of effort. Otherwise very good content. I could learn a lot.

By Jonathan P

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Oct 26, 2022

Material had great breadth of topics. Should also cover related topics like how to add "narratives" to the visualizations to enhance storytelling skills.

By Rohan B

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Jun 20, 2019

Course is really helpful for indulging someone into data visualization but sometimes in the lab some stuff is just present for you to figure out yourself.

By Magnus B

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Mar 11, 2019

The information provided was straightforward and easy to understand. However, the final lab requires extended knowledge that is not covered in the videos.

By Niladri B P

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Jun 7, 2019

Excellent lab material. However, I feel the video lectures were a bit too brief and could have tried to explain the technical concepts a little bit more.

By Varun V

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Jan 1, 2019

Nice course. But Seaborn examples could have been more helpful. Also, please use Python 3 for examples. Thanks for the video and more better class labs.

By Makinde M D F

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Sep 17, 2020

The Course is an interesting and practical Course. Alex Aklson, the lecturer is a good teacher too.

Many thanks to IBM and all the teachers on Coursera.

By RICHARD D

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Oct 11, 2019

The Course materials are brief and Short and understandable. No need to learn junk topic only relevant areas are learn in this course. Thanks to IBM .

By S B A

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Sep 16, 2020

The course was good, syllabus was okay, I think that seaborn could have also been added in this, though waffle chart and map was very new for me...

By Tenin M L K

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Aug 19, 2019

Good condense course. One thing is a the recall of the data set and the lab at the beginning or at the end of each lecture which are very annoying.

By Nicklas N

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Jan 29, 2019

A good overview of different visualization methods in Python. The final assignment is a little tricky and requires a diverse set of Python skills.

By Sai S D

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Sep 11, 2019

Its a great course to learn all Data Visualization libraries in python and thier constructs. It helps me alot to learn Data Science using Python.

By Pradeep M

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Jan 9, 2020

Good course. However, the instructor should add a slide mentioning what kind of errors can occur in python programming and how to correct them.

By Andrew R

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Oct 23, 2019

Some instructions could have been clearer. The final project required code that wasn't covered in the lessons. Had to research the internet.