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Learner Reviews & Feedback for Data Analysis with Python by IBM

4.7
stars
17,670 ratings

About the Course

Analyzing data with Python is an essential skill for Data Scientists and Data Analysts. This course will take you from the basics of data analysis with Python to building and evaluating data models. Topics covered include: - collecting and importing data - cleaning, preparing & formatting data - data frame manipulation - summarizing data - building machine learning regression models - model refinement - creating data pipelines You will learn how to import data from multiple sources, clean and wrangle data, perform exploratory data analysis (EDA), and create meaningful data visualizations. You will then predict future trends from data by developing linear, multiple, polynomial regression models & pipelines and learn how to evaluate them. In addition to video lectures you will learn and practice using hands-on labs and projects. You will work with several open source Python libraries, including Pandas and Numpy to load, manipulate, analyze, and visualize cool datasets. You will also work with scipy and scikit-learn, to build machine learning models and make predictions. If you choose to take this course and earn the Coursera course certificate, you will also earn an IBM digital badge....

Top reviews

SC

May 5, 2020

I started this course without any knowledge on Data Analysis with Python, and by the end of the course I was able to understand the basics of Data Analysis, usage of different libraries and functions.

RP

Apr 19, 2019

perfect for beginner level. all the concepts with code and parameter wise have been explained excellently. overall best course in making anyone eager to learn from basics to handle advances with ease.

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26 - 50 of 2,711 Reviews for Data Analysis with Python

By Hakki K

Jul 9, 2020

Hi,

I completed entire program and received the Professional Certificate. On the Coursera link of my certificate "3 weeks of study, 2-3 hours/week average per course" is written. This information is not correct at all, it takes approximately 3 times of that time on average! I informed Coursera about it but no correction was made. It should be corrected with "it takes approximately 19 hours study per course" or "Approx. 10 months to complete Suggested 4 hours/week for the Professional Certificate".

Here is the approximate duration for each course can be found one by one clicking the webpages of the courses in the professional certificate webpage: (*)

Course 1: approximately 9 hours to complete

Course 2: approximately 16 hours to complete

Course 3: approximately 9 hours to complete

Course 4: approximately 22 hours to complete

Course 5: approximately 14 hours to complete

Course 6: approximately 16 hours to complete

Course 7: approximately 16 hours to complete

Course 8: approximately 20 hours to complete

Course 9: approximately 47 hours to complete

This makes in total approximately 169 hours to complete the Professional Certificate. As there are 9 courses, each course takes approximately 19 hours (=169/9) to complete.

(*): https://www.coursera.org/professional-certificates/ibm-data-science?utm_source=gg&utm_medium=sem&campaignid=1876641588&utm_content=10-IBM-Data-Science-US&adgroupid=70740725700&device=c&keyword=ibm%20data%20science%20professional%20certificate%20coursera&matchtype=b&network=g&devicemodel=&adpostion=&creativeid=347453133242&hide_mobile_promo&gclid=Cj0KCQjw0Mb3BRCaARIsAPSNGpWPrZDik6-Ne30To7vg20jGReHOKi4AbvstRfSbFxqA-6ZMrPn1gDAaAiMGEALw_wcB

By Vera

Apr 7, 2021

The general course content was okay. Unfortunately I didn't learn too much about Python and Data Analysis for Data Scientists. This was due to the following reasons:

1) a lot of interaction with not working IBM infrastructure. It took me around 3x as much time to get required things working on IBM cloud and IBM Watson compared to the time spent for actual assessments. It is annoying if it's getting that obvious that IBM wants to use the course to promote own products. This is sad as we all already pay for the course...

2) There occurred quiet some arrows in the labs which even after months (according to the discussion) have to been corrected.

3) The amount of hands-on training in the notebooks/labs was really small. It was not a lot one had to program on their own and the parts which had to be programmed were only an exact copy of what was already done before. Even the final assessment did not really contain a real task.

4) Many concepts weren't explained in depth. The explanations just stayed very superficial. Some concepts like fit()/fit_transform() which appeared in the labs weren't explained at all in the videos or in the labs. This led to a lot of confusion as could be seen in the discussion threads.

As we all pay for this course please increase the amount of actually explaining concepts in depth and the amount of real in depth hands-on training and reduce the parts on IBM Watson and other such stuff. Thanks a lot!

By Javier M

Apr 28, 2021

The content is solid. However, the labs which are the best tools of this course because they allow you to actually do the exercises and go deeper in the concepts are not working. It has been like that for some weeks.

I contacted support and I saw in the course forum lots of people complaining about it but either Coursera or IBM don't seem to care. No answer from them for weeks. I had to dig into forums in the Internet to find alternative solutions to access the labs... which was a waste of time considering that I'm not auditing but paying for this course.

So terrible customer experience, that's why I put one star.

By Srikantha R

Mar 23, 2021

Definitely NOT for beginners. No proper explanation of basic concepts. The instructor assumes that all students knows everything and they just explaining python formulas without giving basic concepts on data analysis or statistics. If one has to complete this course only for the sake of certification, one must get the basics right with free online materials and then only can enroll for this so called 'BEGINNER' course to get certificate. I am cancelling my subscription and can learn on my own with free and better online materials

By Thamarak

Aug 22, 2020

This course is too hard. This should be go on more slowly and explain more about meaning of each value described. The course is not for beginner and not for a person who doesn't have enough statistics background.

By Sobhan A

May 6, 2020

Low quality.

Do not recommend this course at all.

Boring teaching method.

Full of errors.

No IT support for problems.

By Titans P

Aug 17, 2020

worst ever

the greatest thing i have learned here is patience and searching online

By Oana M

May 22, 2019

Thank you so much! - Oana

By Aditya J

May 18, 2019

None

By William B L

Mar 20, 2019

The techniques, methodologies, and tools presented here are essential parts of the data analysts tool box. The coverage was, in general, well done. I am glad I took this class, and look forward to the next.

That said, there were problems:

1) The meta parameter, Alfa (or is is Alpha) is never explained, except that it helps. To be useful, the student needs to know a bit more. Also, the spelling should be consistent between the training texts and the lab.

2) The lab needs maintenance to keep up with changes in the Python packages. I received warnings about using deprecated functions and values.

3) The text needs grammar/spelling checking, for example, the end of the course exam is labeled "Quizz"

By Karen B

May 25, 2019

Does an excellent job in providing the Python commands needed to do data analysis, along with some descriptions of what the steps actually involve. Has quite a few typos and minor issues -- looks a little sloppy.

By Matthew A

Apr 13, 2021

During the 4th week of the course, lots of important information and explanations are over summarized and in some cases skipped over. Learning tools outside of what is provided in the course or a decent understanding statistics is required in order to be successful in this course.

By Shuting Z

Nov 22, 2020

Not well designed at all.

By Shashank S C

May 6, 2020

I started this course without any knowledge on Data Analysis with Python, and by the end of the course I was able to understand the basics of Data Analysis, usage of different libraries and functions.

By Vallian S

Jan 31, 2022

This is totally one of the hardest course I've ever taken on Coursera. It's packed with knowledge I did not know before. Definitely recommended for people who want to learn data analysis with Python.

By Joseph A

Feb 27, 2023

Great example of what's wrong with technical training. Lot's of syntax that you won't remember unless you are already familiar with it, (often intrusive) quizzes on syntax that you've only just seen (sometimes for only seconds), important themes and ideas lost in the implementation details, covering too much material at a superficial level instead of less material and actually learning it, skipping over the necessary mathematical/statistical background in order to quickly advance to blindly coding, skipping over the broader understanding of the (multitude of) libraries that were used in order to go right to using them, and meaningless labs that give the illusion of deep understanding but are in fact cut-and-paste fests devoid of understanding. I'd rather have taken a slower course in just pandas and a separate course in the linear algebra and statistics being used (with some math pre-requisites). I was also recommended this course immediately after finishing part 2 of introduction to python and I don't feel like I have nearly the python background that this class assumes, however I guess flaws in recommendations are not necessarily flaws in this course (unless it purports to be perfect for python novices).

By Andrea

Oct 22, 2021

I can't believe this course has an average of 4.5 stars. I think they're fake reviews.

They state that no previous knowledge is needed and yet the topics are complex and not explained during the course. They give you information without any introduction on them, giving for granted that you know that information.

There's a lab to exercise that is full of bugs.

If you want to learn Data Analysis with Python and you don't have any previous knowledge of Python, Statistics and Econometrics, stay away from this course.

Probably if you have a firm knowledge of the above subjects it can be useful.

I think people rated it with high score, because it's easy to get the certificate, not because is useful in terms of learning the subject.

By Jennifer R

Mar 31, 2020

The topic is very interesting, but the execution was poor. Code and numbers were just being read at me, instead of focusing the recorded lectures on teaching concepts and troubleshooting, and leave the code to be read by myself in the labs. Also, the quizzes along the way were nearly useless: only two questions, a "pass with at least 50%", and the questions asked were very superficial. This is the most poorly executed course I have taken on Coursera so far.

By Vincent L

Sep 17, 2018

Ton of errors, both minor and major, in the videos and the quizzes. For example, saying the a difference between two variables is significant because p > 0.05. I report them all and I've stopped counting.

Not professional at all.

By Anastasiya B

Sep 22, 2019

Low technical quality of the course with lots of typos, errors and comletely mess in final assignment.

Low quality of material, bad structure, and you can get your certificate just by clicking shift+ enter

By John K

Jul 7, 2019

Poorly put together course - especially the labs. Frequent misspellings, incorrect links and confusing instructions. The technical problems are a greater challenge than the course material.

By Abhijit R

Sep 6, 2019

Course content is very poor. Not clearly explaining each & every thing in each slide. Disgusting

By Saba A

Jul 28, 2020

The instructor does not explain the codes at all. She just rushes to finish the videos!

By Ritesh C

Aug 4, 2020

Nothing explained in course, nor even exercise for practice any good

By Ahmed B

Jul 14, 2020

the explanation isn't good