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IBM 기술 네트워크의 Data Visualization with Python 학습자 리뷰 및 피드백

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"A picture is worth a thousand words". We are all familiar with this expression. It especially applies when trying to explain the insight obtained from the analysis of increasingly large datasets. Data visualization plays an essential role in the representation of both small and large-scale data. One of the key skills of a data scientist is the ability to tell a compelling story, visualizing data and findings in an approachable and stimulating way. Learning how to leverage a software tool to visualize data will also enable you to extract information, better understand the data, and make more effective decisions. The main goal of this Data Visualization with Python course is to teach you how to take data that at first glance has little meaning and present that data in a form that makes sense to people. Various techniques have been developed for presenting data visually but in this course, we will be using several data visualization libraries in Python, namely Matplotlib, Seaborn, and Folium. LIMITED TIME OFFER: Subscription is only $39 USD per month for access to graded materials and a certificate....

최상위 리뷰


2018년 11월 27일

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.


2020년 8월 13일

Great course, one of the best course to get hands-on learning for Data Visualization with Python. Particularly the lap exercise, it will make you think on every line of code you write. Excellent!!!

필터링 기준:

Data Visualization with Python의 1,554개 리뷰 중 26~50

교육 기관: Yiannis E

2020년 6월 12일

This was not a course. This was a "go get them tiger": the labs are there, go do them and come back for the assignment. And then, in the assignment there were features that we had to include in a chart that were not even hinted - let alone explained - anywhere in the course. If we the idea is that we must search for everything on the web, then the course should at least include references to websites where we can find relevant information. Back in my student days we called that "suggested reading". Some of the Multiple Choice questions were really annoying: do we really have to remember the first name of the creator of Matlab to become data scientists? Great Material, but a very frustrating overall experience since there was no teaching.

교육 기관: David A

2019년 10월 22일

While I enjoyed the content of this course, I feel that the instruction was disorganized. This course is part of a beginner sequence in data science, but the teacher assumes certain advanced skills are already known and does not teach them. For example, chart annotation is only briefly covered in the second lab, but the final assignment requires a depth of knowledge not taught in this course. If that's the case then chart annotation should be taught as its own section. A lot of the quizzes are written to trick you with ambiguous phrases, rarely do they actually test what is learned in the labs. I think the teaching in the other IBM data science courses is far better than this one, hopefully they improve this one.

교육 기관: Hesam R

2019년 12월 22일

In my opinion, it's a terrible course. The labs seem to belong to an advanced course, whereas the videos are elementary and for absolute beginners. The labs take several hours and and even days to complete and understand, whereas it's claimed only an hour is required. None of the links/path at the final assignment worked! zero to none customer support, which is an absolute shame. The final assignments are way beyond the scope of a beginner course. Waste of money!!!

교육 기관: Elian A

2019년 8월 26일

The course was shallow in content. I wish it explored pros/cons of advanced visualization techniques & how to go about implementing them in python with several real-world examples. The videos were extremely short & repetitive explaining the same dataset in each video. Bulk of the learning happens in optional labs & peer reviewed final assignment. Most of the insights are easily available online.

교육 기관: Sarra A

2019년 1월 26일

I appreciate that the videos were done in a human's voice and not a robot. It helps me focus to hear the natural pace and emphasis on certain points. Also, the labs were very clear (thank you). There was clear guidance/notes through steps which is very helpful because this is a new thing for me. The final was also fair and comprehensive. I have a long way to go but this class was very well done.

교육 기관: Ashutosh M

2020년 8월 14일

Great course, one of the best course to get hands-on learning for Data Visualization with Python. Particularly the lap exercise, it will make you think on every line of code you write. Excellent!!!

교육 기관: Sahil s

2019년 11월 21일

It's a really great course with proper hands on time and the assignments are great too. i got enough opportunity to explore the things which were taught in the course. Really Satisfied. Thanks :)

교육 기관: Hani H

2022년 4월 3일

This course started out good but quickly went downhill. The first two weeks focused on matplotlib, and while I did learn something useful, I did not need a dataset recap on every single video. its a waste of time.

Week three is where things quickly go off the rail. Waffle charts were introduced, and we were told that there is no quick way to do a waffle chart in python. That's fine, I'll learn how to do it the old school way. That was time consuming but time well spent right? WRONG. When you take the module quiz you are asked if pyWaffle is the best way to create a waffle chart. You answer no because you actually watched the videos and did the lab training, but you get a wrong answer. You check online and what do you know, you can actually do a waffle chart with 2 lines of code. IBM knew this (hense the question in the quiz) but nobody bothered to update the lab or the videos

The video on word clouds introduces the concept and you were supposed to learn in in the lab, but then you get to the lab and you are told to skip this section. I have no words for this

The part on dashboards takes the cakes. IBM basically provides you with external links and leaves it at that, there isnt even an attempt to teach you these concepts. And you know what the best part is? the course project requires you to build a dashboard. Yep, the thing they didnt even attempt to teach you.

Anyway this review is too long and I doubt anyone reads it, but hey, if you do, just be prepared to read a ton of external resources because you are not getting what you are promised

교육 기관: Olin H K

2020년 4월 19일

Bottom Line Up Front: You are going to have to teach yourself using Google for the Final Project

This course was unique in the Data Science Professional Certificate Progression in that the content of the videos was not very helpful, making your rely on the labs to teach yourself.

The labs were not great in walking you through all the parameters that were available for each type of plot, and while you can copy and paste solutions and tinker to learn things, the course didn't leave me with a good understanding of how or why things work and thus, unable to apply solutions creatively and appropriately without much effort.

By far my least favorite course of the 7 IBM courses I have completed so far.

교육 기관: Paul B

2020년 2월 29일

Like other reviews I was really looking forward to this course in the IBM syllabus but was very disappointed. Videos were very high level and repetitive - and there were a lot of them. The detail in the exercises was better but there were significant challenges in getting them to work. And then the final assignment was a bit of a joke. The visualisations you were expected to produce had not been taught in the course and as you'll see from the forums requires a lot of work arounds. I would suggest this course needs a bottom up re-write. Do less but cover it better!

교육 기관: Johannes W

2019년 8월 30일

The videos were unfortunately pretty useless. At least half of the time the respective dataframe was processed (but always in exactly the same manner... zero information about the actual new concept). In addition the videos were too short and the really important new concepts were only introduced by quickly showing the code snippets. There was often no explanation of key concepts. Unfortunately, overall one of the weaker courses on Coursera. The Data Analysis Python course is much better and explains similar concepts.

교육 기관: MAJ A S

2020년 6월 22일

There's a lot of good material, and ultimately enough to integrate into successive work in data science.

On the frustrating side, most of the explanations focused on "what" rather than "why", and there's so many "why" left unanswered when choosing to address a problem with these tools.

Additionally, most of the questions were either insultingly easy or incredibly difficult. Plenty of googling in addition to reviewing presented material.

교육 기관: Bhavesh B

2020년 4월 17일

This course did not went into the depth and breadth as per expectation after following previous course. In my personal opinion as PhD myself with history of teaching for 4 years, the content is not enough to make a separate course. This course can be included as part of data analysis course itself as separate week worth of lesson.

교육 기관: Ian A T

2020년 5월 7일

While the data visualization tools outlined here are valuable, the final assignment for this course does a very poor job of assessing the things that were actually taught.

Early on, you are assured that the course will emphasize the scripting layer of matplotlib, rather than the more complex artist layer. In the final assignment, however, you are instructed to use the artist layer, and configure many parameters that were never covered in any of the labs or videos.

Likewise, utilizing geojson files for choropleth maps was covered in the most cursory manner - you are never requried to open a geojson file, or understand how it is configured. You just load it in and carry on with the assignment. However, without understanding the setup of a geojson file, no student is going to understand how to properly configure the key_on parameter when making their own choropleth map for the final assignment.

The ability to actually create a graph from a set of data is perhaps the smallest part of the final assessment. Everything else is fussing with irritating details, often details that we were never taught about in class.

교육 기관: Mya S

2019년 9월 9일

This was a valuable course to learn visualization with Python. I especially appreciate the section on mapping and the waffle charts. The only suggestion I would offer is to have more opportunities for practice coding, especially for grouping data for analysis, labeling charts, calculating percentages. These could either be optional assignments or links to other resources. But regardless, this is the best course out of the series for me so far.

교육 기관: Toan L T

2018년 10월 20일

This course is really good. The instructor did a great job introducing common graphs, charts and map techniques. What they look like. How, where and when to use them.

The lab is time-intensive which give chance to thoroughly practice the technique. One more plus point is the lab uses real data and guide you through the step of retrieving, cleaning, analyzing, visualizing and mapping.

Definitely recommend.


2018년 11월 28일

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.

교육 기관: Ruchit S

2020년 1월 8일

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.

교육 기관: Mirena T T

2020년 4월 24일

Great course, extremely thorough! Interesting assignments. It is more than obvious that the author has put time and effort into it. Thanks for that :)

교육 기관: Aylin B E

2020년 3월 16일

The video content was not extensive and it was recommended to study on labs for more detiled information, however, like many people who took the lesson, I had difficulty opening and using the lab When I wrote about the problem to the support team, they said they already escalate this issue to their partner to take care of it and fix it as soon as possible. I completed assigments and labs on a different compiler.

I'm disappointed about this course after all the good courses I took on Coursera. I hope they will fix the issue quickly.

교육 기관: Yan C C

2020년 6월 11일

quiz had strangely tricky questions, which were not thoroughly covered in the videos. And as others have said, the final assignment challenged us to do a bunch of things that are out of the scope of this topic. It would have been much better if we had more guidance on setting up the groundwork to perform the visualizations. For instance, I had to figure out how to import folium into my notebooks, which took up some time - some direction might have helped with that. Overall, I did learn some from the material, but the experience could be way better.

교육 기관: Arnold H

2019년 12월 28일

I enjoy the IBM certificate programme in data science so far. But this course is a great disappointment because of the followings. 1) The clips are not organised which waste us time to read the same contents (i.e. how to clean up the data) for more than five times. 2) The instruction is not clear without going into the details of the coding. 3) Some of the images of the assignment are incorrect, misleading many of us to spend extra time to fix something that should not be fixed. Hope Coursera can redo this course.

교육 기관: Sarah W

2019년 8월 26일

The class is beneficial as it allows you to understand how to create visualizations of your projects. However, the final project for this class was very hard to understand. A lot of the parts that were expected to be completed were no where in the videos or labs. In the forum, you could tell because a lot of people were confused about the same stuff. Others and I ended up using other sources as a way to get the results Coursera was wanting, rather than what Coursera taught us.

교육 기관: Jennifer B

2020년 3월 12일

This course does very little teaching. The labs demonstrate how to do things, but there is little explanation of why, and no theory about visualisation at all. Instead, students are simply taught to follow recipes. Also, for the past week, the IBM servers have been extremely unreliable. I haven't taken off any stars as it's not the fault of the teaching staff, but it's a bad look when an IBM run course can't actually get the IBM computing services to work properly.

교육 기관: Gilles W

2019년 4월 9일

Videos are so so, the same introduction for all videos with 2 minutes of data formatting, which is exactly the same in all videos, leaving only few minutes at the end of the vid's for the content of the lesson. The examples in Jupyter were interesting but not very well structured. At the end, I better used Google and Pandas documentation to solve problems and learn about the topic. Not a bad lesson, but there are just more effective way to learn in my opinion.