Data Visualization with Python
“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. IBM offers a wide range of technology and consulting services; a broad portfolio of middleware for collaboration, predictive analytics, software …
Courses : 7
Specification: Data Visualization with Python
90 reviews for Data Visualization with Python
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Collin G C –
The information was valuable and generally well explained. The final was a massive failure; the classes and examples prepare us for maybe half of the questions, but all the questions depend on building off each other. The only way to pass is to Google for hours.
Gaurav R B –
Course is not organized properly
Satishkumar M –
Eunice C –
not too practical over the course, a lot of theory based which is great as well. But I personally not a big fan of the Watson studio as it’s not user friendly. I have to go through a lot of layer on their site before getting to the studio or the notebook.
Pradeep M –
Good course. However, the instructor should add a slide mentioning what kind of errors can occur in python programming and how to correct them.
Awful. You don’t learn anything you’re tested on.
Kong C H –
Course content is good. But there’re some replication for each video about “recap of the data”. The final assignment is quite difficult because I need to find some codes from the internet to meet some task requirements.
Justice N –
a ton of helpful example make it easy to understand
Josh H –
Really informative course on visualization however very beginner!
Aditya D –
Need more clarity and practice for this course. This course seems the toughest as it asks for memorizing artistic layer syntax which seems so difficult coupled with the humongous choropleth map! A huge amount of practice is needed for this certificate even after labs!
Carlos N J –
Lots of in depth labs. However, final assignment required some techniques that were not covered at all, so the difficulty was much higher than expected.
Lee Y Y –
Wonderful contents and learning experience, especially creating/annotating Earth map and making word cloud.
Sanjeev s –
Muntakimur R –
Helped me to enrich my skill in visualization
Elke L –
I have to resubmit final assignment many times and wait for peer review for so long only to be reviews unfairly. Course needs grade moderation for peer reviewed assignments.
Carol L –
Me parecio super interesante el curso, pero los videos muy cortos dejando todo el material para el lab, y el final assigment con solicitudes que no fueron explicadas durante el curso.
Amala H –
That was fun!
Muhammad Y R –
The Course Was Perfect And Was The Lab.The only thing that was so annoying was intructor just give a brief introduction and left the topic with lot of confusion.Lab was annoying to it was very hard to open and was giving so mcuh error
Yeh Y J –
will be good if the module can elaborate more on how to add data label as annotation.
Simran P S –
interesting course, but i really faced a challenge doing the assignment, i guess it would be better if assignment questions were covered in Labs session also. The assignment was over the top, and tougher to get it correct.
Sean M –
Since students weren’t able to submit code, this made it extremely difficult to answer the final project (which I couldn’t figure out how to finish). Getting feed back on how to correctly code the answers is more important than showing a screenshot of the final product.
Ana C T M –
Links did not work for classes hands on exercises, repetitive video explanations, and final project required content that was not explained in classes. Overall, it was a bad experience on a subject that should have received more thought and caring from instructors on lesson plans and class materials given its importance.
Karen M –
Excellent class only problem was one of the map types available in the labs are no longer available open source. Challenging project.
Akash K M –
NICE MENTORED COURSE
Kristopher K –
This was a lot of fun learning to plot crime statistics of districts over a map. Very cool stuff!
Johan M R Z –
Jayesh M –
nice course but little bit of complex course. There is a lot in simple plot. So, It is not that much good idea to do so,
Benjamin S –
This course has one advantage over the others in the series: practice time. The labs are more thorough and provide more practice problems. However, the overall quality in production of this course is lower than the others. Additionally, there were some points awarded on the final project for things simply not covered in the lectures or labs, which was frustrating to say the least.
George R –
It was one of the better courses in this data science professional certificate. I like that the datasets didn’t come prepared in advance in the lab exercises and I had to do some work on the on the data before creating the charts.
Rabaa A –
Some of the exercise tools didn’t work
Juan D P –
Very good course!
Vera C –
The final project is challenging but rewarding.
Alok M –
I didn’t find the modules very helpful. Okayish Experience
Yuriy S –
Great and Informative!
Anthony T –
a great course, data visualization is one of the topics that draws many people into the field of Data Science. I found it to be a very interesting course, one whose lessons I will return to often as I continue to build my knowledge and experience
Venkata S S G –
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.
Louis J –
I have mixed feeling about this course. I think the purpose of this course (visualizing data) and the different ways of doing it is really motivating and awesome, specially when you realize all the things you can do (types of charts , maps etc…). This is actually awesome! However, on the down sides: Each video repeats the steps on how the database used in each course has been “cleaned”. I agree with the feedback from other people, reminding us one or two times is fine, but in each video… This is too much! I would have liked more practical exercises, specially to plot multiple linear regression models (and polynomial of different degrees, in particular), to display on a chart, and to make predictions. That would be great ! Labs: they are of unequal difficulty: some are relatively easy to complete, some require more thinking/research and time, while some have no question at all or very little. Maybe it would be useful to re organize the labs ?… Week 3: as everyone mentions, the “artist layer” method is only briefly covered in one of the lab. It would have be really useful to spend more time on it, and on all the things we do with it. Like others, I spent lot of time searching online, and it took me a full afternoon to complete that part of the final assignment ! To summarize: it’s a very important and interesting course, but video lessons should be re recorded with deleting all parts repeating the initial database processing, and adding more topics such as artist layers, etc. Also, maybe split each lab in 2 since there are few labs in this course, but if we follow them correctly, it requires quite few hours to spend on each lab (at least for “beginners” like us starting learning about this topic). Thank You !
Haowen W –
Bryce Y –
This course was presented in a way that challenged me more than other courses in this program. I was very happy to have been challenged to think critically.
Very interesting summary of different graphs I saw in my life, though the data can’t be imported to the Jupyter notebook for exercises.
Kristin R –
i took a long break and still managed to come back and finish
Joao C –
Out of all the courses in the IBM Data Science Professional Certificate, this was the one I had the highest expectation for and unfortunately I was a bit disappointed. The course materials are lacking in information and the final assignment asks for customisations that weren’t covered in the course materials, which leads to question: are these important things to know and the materials are lacking in information ? Or are these irrelevant and should be a part of the final assignment? Because if they’re just there to make sure no one gets a 100% grade, then that’s just sad.
Diana H –
Best course in the specialization! The final assignment was challenging in all the right ways
Frank H –
Some new packages i’ve never seen. Map one was really cool.
Toby C –
This course was good but for too many of the final assignment questions I really had a to look up how to do it on the web. A better explanation of the key on parameter in choropleths would help even though the entry in the json file is features the key on value is feature.properties.
not features.properties. .
Ryan H –
This course felt less well organized and structured as compared to the other courses in the IBM Data Science track. The videos were sparse on detail, and while the labs did have a lot of good information, they were missing crucial material that was necessary for the final assignment. The final assignment also didn’t include a Jupyter notebook template / starter code, which combined with the missing information from the labs made the assignment much more frustrating than those for the other courses in this series.
Dony G –
Poor study material compared to the assignment
Javier A P G –
A great course to prepare, I’m thankfull
Michael S –
This was the worst course in the specialization.. It was hard to follow, there weren’t many lessons, and it wasn’t worth the cost.
Mayank s –
Very less detail and seaborn was not covered which is better for visualisation than matplotlib in most cases.
Mo S H –
Better to read matplotlib and folium documentation and look for answers from stackoverflow. This course didn’t offer enough components of matplotlib and folium. This offers lab sessions but they are not main contents. Final assignments are impossible for someone who just takes only this course.
Ankit S –
Very wisely chosen content of ungraded lab assignments
Claudio C –
A very great course of Data Visualization in Python. The exercises proposed are not trivial
Muthu M H –
Aurelio L G –
Muy completo y bien desarrollado. Excelentes explicaciones, ejemplos y retos.
Clara R –
The videos were very repetitive, and didn’t teach you much about best uses for diferent kinds of graphs.
Franck A B K –
Very interesting course! I’ve learnt diverse tools about data visualization, and I’m ready to apply them in my projects.
Surya T C –
David C –
Good course, however, should add some additional readings on the topics. Because the videos don’t develop too much the topics.
LAURA T G –
Mmany mistakes that make the studentsd work and stress more tan required
Daniel T G –
Musfiqul A –
Need more hand notes
Eden P –
Great course. Demonstrated some great techniques on representing data in an informative way. Will definitely use the learnings in future.
Siwei L –
I feel this is harder than the other ones in the series, sometimes you need to google a little bit to figure it out. I spend more time for a week, but I wonder why I have to do it in Python. I learn Python just for faster loops than R. Personally I think R need less coding and produce better graphs.
Fernanda T d S T –
Congratulations Alex Aklson for this incredible course that you made. I learnt a lot! Good content, good questions and good assignment!
Khandoker S I –
This course helped me a lot to improve my knowledge of python.
Thierrawat J –
The assignment is a bit too difficult
RITIK Y S –
All the time practice lab is not working.
David H –
Poor examples / labs! Labs very often not working.
Juan C C –
Content was solid, but videos mostly said “go do the labs” vs offer meaningful tips for the final an beyond. Worst of all, the tech is outdated. I spent an entire weekend working on the final assignment due to technology issues. An embarrassment for Coursera and IBM that they let this happen.
Gustavo P F d X –
There are some problems with the labs according to installation required.
Stamatios G –
Although the content of this course is very interesting and has a lot of depth in the field, I believe that it needs further improvement, specifically with more examples in the labs, in order to get a better hang on the different types of visualizations.
Catalina M C –
The lab stopped working and we didn’t get any support.
I liked the assignment presented by the course. I learned from solving the problems. The constant error with the lab problems discouraged me at times.
Colette C –
The subject matter of this class was very enjoyable. However, the level of presentation of the material was not in depth enough . As a person who is not from a computer science background, this class was extremely challenging; not because it was too difficult per se, but because I was not given the tools needed to be able to confidently complete the Final Assignment. It took many days of researching, watching several videos outside of the Coursera platform, and a lot of trial and error, to be able to complete the course. In addition, the labs had trouble loading (not Coursera’s fault, as it was through another site) quite a lot, which hindered my progression.
Tara S –
A lot of problems opening the labs. The final assignment required us to do things that were not discussed in the course and it was unclear where to get the relevant information to complete it.
Francine S –
The content of courses are great! Went through step by step until a high technical level. Unfortunately, the lab is always out of server, me and others users have been reported the same problems every now and then and nothing changed. I finished the course without practice the labs and I can’t check the exercises to start an own project! Apart from that the whole course is worthwhile.
Michael J L –
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.
Stephen v –
Doing the IBM Data Science Certificate and this is probably the worse course. The content is relevant but the directions and labs are poor compared to the others. The explanations aren’t as clearn.
Oscar C C –
Alessandro C –
So far this is the worse course the coding is not well explained and the lessons are extremely ripetitive!
Penthala v –
Chayapol M –
This course so challenge for me. If you give me discuss about how difficult of assignment. I thought this one also hard and seriously.
Glenda m –
Labs do not help solve assignments. They must explain examples to learn, I have to research in google to solve. those practices are bad I don’t like this way of working at all
Svetlana S –
Labs didn’t work for the whole week. it’s often happens with all IMB Data Science specialisation courses. Videos are not really useful, labs are the most valuable, but it’s always hard to load them
Jacqui T –
Labs are very interesting. Would suggest including more data wrangling techniques (to better align with the final assignment), and removing Mapbox Bright references. On the whole, this was a far more interesting module than I had expected.
Naveen G –
Appreciate the content and visualization. Labs dont work most of the time, it hinders the progress and momentum
Elizabeth B –
Complete waste of time and money! Skills Network Labs was constantly malfunctioning. The labs were so glitchy that I spent more time troubleshooting how to open the labs than I did on learning the actual course material.
Gabriel d C C –
Muitos problemas com ferramentas externas
Soham N –
Nice video and Lectures. Great Explaination