Chevron Left
Back to Data Analysis with Python

Learner Reviews & Feedback for Data Analysis with Python by IBM

4.7
stars
12,289 ratings
1,779 reviews

About the Course

Learn how to analyze data using Python. This course will take you from the basics of Python to exploring many different types of data. You will learn how to prepare data for analysis, perform simple statistical analysis, create meaningful data visualizations, predict future trends from data, and more! Topics covered: 1) Importing Datasets 2) Cleaning the Data 3) Data frame manipulation 4) Summarizing the Data 5) Building machine learning Regression models 6) Building data pipelines Data Analysis with Python will be delivered through lecture, lab, and assignments. It includes following parts: Data Analysis libraries: will learn to use Pandas, Numpy and Scipy libraries to work with a sample dataset. We will introduce you to pandas, an open-source library, and we will use it to load, manipulate, analyze, and visualize cool datasets. Then we will introduce you to another open-source library, scikit-learn, and we will use some of its machine learning algorithms to build smart models and make cool predictions. If you choose to take this course and earn the Coursera course certificate, you will also earn an IBM digital badge. LIMITED TIME OFFER: Subscription is only $39 USD per month for access to graded materials and a certificate....

Top reviews

RP

Apr 20, 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.

SC

May 06, 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.

Filter by:

1551 - 1575 of 1,760 Reviews for Data Analysis with Python

By Prasanna S

Sep 30, 2020

The labs are very good. That is the most redeeming part.

The instruction videos are quite simply, very monotonous and boring - you don't see the instructor and there is no attempt to make the learning stick.

You don't get timely or quality responses in the discussion forums, so sometimes you feel like you are on your own.

The final lab assignment required you to get on to the IBM cloud and set up your account. I get why they are doing it, but it was clunky. You are required to set up on the free option, but the set up is overkill for a relatively small assignment.

Overall, I probably will not do another IBM course.

By Michael F

Jun 10, 2020

Solid overview of the applicability and mechanics of various analysis techniques. Video content was thorough and reasonably well rounded.

Labs could use improvement. Lots of technique shown which allows for a monkey see monkey do approach to learning but not much context or explanation of why an individual approach is used or clarification of the intent of the code. For individuals already familiar with the various packages this is probably okay but without that context the take away value of the course is somewhat limited.

By Sarra A

Dec 21, 2018

I understand the course isn't officially started yet, but it could've been better. There's much to be corrected in the labs as well as the quizzes. The amount of information was a lot, and I'm thankful for the notebooks I have now with steps on doing things, but the material could've been presented in a more cohesive way, this was hard to follow. Also the labs were more intimidating than anticipated (also with many errors). I think this course should be split into two classes instead with more explanation in both.

By Bahar T S

May 01, 2020

The course material was helpful, however the labs had several mistakes which I noticed they have been talked about in the forums since long time ago. Also I had strange experience with final assignment grading. At first I failed by a reviewer , I checked my answers and I was sure they were correct, I complained about it and my complaint went nowhere. By resubmitting it again I got full score! I think it would be better to have a more efficient way for grading the assignment accurately.

By Brett W

Sep 17, 2019

While the lecture material is well presented and certainly can be followed, the slides are littered with spelling mistakes, and many in important places (code that couldn't run as displayed.) Even the final assignment had formatting issues, and without the discussion forums suggesting removing the confidence interval, it was taking an excessively long time to run. These are generally minor issues that can be ignored, but as a mass, they are embarrassing at best.

By Samantha R

Mar 07, 2019

The course content was relevant and quite useful. Its the structure of the course that I didnt like. These are the things that could be improved:

QA before sections are finished does not work - one should first go through the section then the mini QA should start

If one is paying for the course, the slides should be made available for download. Its nice to have reference material for afterward because one forgets things. Even more so if you pay to do a course

By Daniel Z

Jul 14, 2020

Many typos, some code does not match text (e.g. text says test sample of 10% but code has test sample of 15%). Where there are questions embedded in the video they often interrupt a sentence which breaks up the flow of the material. Complicated concepts or uses of code are often mentioned very quickly and the related slide disappears from view too quickly.

My peer reviewed assignment was reviewed twice and both times scored incorrectly but in different ways!

By TAN H D

Jun 02, 2020

Some of the instructions were not clear enough, with a couple of typos here and there. Alot of explanations can be given to the code, e.g. what is for what. Also, before the video quizzes, needs to let learners look at the screen, pause before flashing out the quiz. Overall, good experience. Aside from having some difficulties trying to understand some parts of the module, but able to pick up Data analysis thanks to the course.

By Liam M

Jan 18, 2019

So far the other courses in the Data science specialisation contained a final graded assignment. I found them really useful. This course didnt. Also, instead of telling us about all the tools available in the libraries, maybe explaining why we would use them would be better. I could code these functions myself if I understood them, but just using a library seems like it could lead to laziness and a lack of understanding.

By Josep R C

May 20, 2020

+Useful course for beginners. You get to learn basic concepts although these are not enough to get to work on real projects. Another good point is the set of useful libraries and methods presented in the course.

-Downsides of the course are the amount of mistakes found in the labs which are supposed to help understand the theory seen in the videos, but in some occasions can even mislead and mess the students up.

By Carsten K

Mar 11, 2020

Great coverage of topic, but unfortunately comes with several imprecise (or even planely wrong) explanations in the videos. Video quality (style of presentation) is ok, but sometimes missing things are slightly missaligned or questions show up before the topic/sentence is finished - could use some polishing. The hands-on labs are great though - if the notebooks open or the servers are reachable.

By Felix S

Jul 01, 2019

Material to learn data analysis was very good but had quite a few bugs. It was very annoying to review the assignment of a peer because it is not possible to zoom into the screenshot. Furthermore did I need to flag a person because he had copied screenshots and his notebook was empty or only with screenshots but I was still required to review a second person to complete the course.

By Jackson V

Jun 06, 2019

Not as impressed with this course as the previous courses. My main complaints were:

-Seemed to be some gaps between the lectures and labs

-Some lectures seemed rushed through w/ simple questions, and did not prepare well for the lab

-Pre-written code in labs would produce errors

-Spelling mistakes (i.e. the week 5 "Quizz")

-No final project to conclude and summarize up our learning

By Chioma J E

Apr 10, 2019

The course was not detailed enough. I think the instructor assumed that people taking the course would know a lot about Regression, Correlation and some other statistical functions, that it was hard to understand or follow at times. Maybe consider 'dumbing' down down the statistical functions so that newbies can also follow.

Overall interesting course. Thank you.

By Nikhil B

Feb 25, 2019

This is an excellent course for beginners in the data analysis and data science fields as it explains deep technical concepts in layman terms along with the Python code for the same. However, not a perfect course for someone wanting to go into conceptual depth or wanting to expand their knowledge of analysis in Python beyond use of standard packages.

By Fares A G

Mar 18, 2020

Needs to rely less on the cognitive class platform, just host the ipynb files externally as the labs are inaccessible alot of the time. Course only covers regression models, I would've liked to see SVM, KNN and other algorithms. However the course excels in explaining the relevant maths related to regression and regression evaluation

By Mbongeni N M

Sep 09, 2018

It was educational, but when you pass a quiz, there should be an option to get answers to the questions you got wrong. And the practice exercises were filled with mistakes, particularly week 5. And the instructor was not responding to students' questions for week 5, which was one of the most challenging weeks. That was annoying.

By Yariv Z

May 23, 2020

A lot of un addresses subjects. Many mistakes both in the videos and in the labs.

Overall after viewing all the videos again and summarizing for my self everything, I felt a lot better with the material but I think the course is not organized. I also think that it should get into some mathematical subjects more thoroughly.

By Brisa A

Jun 28, 2019

A lot of errors make the course confusing. Also, the assigments and labs are "too easy"... it is clearly shown in the videos that there is much more to be done, but the course only demands you do about 50% of what is taught. How are we supposed to really learn without practice?? Give us real and demanding projects!

By Antonio P

Mar 06, 2019

The content was good, but there were numerous mistakes and inconsistencies (i.e. a chart would show a red line as a training set but the write-up would say the red line was a testing set). Also, I would have preferred to have shorter and more lab activities. The lab activities were too few and each was too long.

By Vyacheslav I

Nov 16, 2019

Grammatical mistakes, low quality videos, low quality slides and videos. Labs are okay, though no in-depth clarifications and explanations are given. Like "to do this you write this". Options? Explanations? What for? It's too much. Just remember how we wrote these lines and copy-paste them in you code later.

By Hemanth S

May 04, 2020

Course is a bit too short and way too fast paced for what it is trying to convey! Of course people will be able to complete the course without problems but, have to re-visit and brush knowledge on these a lot more. Anyways, it is a bit of confidence booster. You feel like you learnt a new course.

By Rakshita S

Jul 26, 2020

The reason I am giving a three to this course because compared to rest it was a bit fast-paced. Also, I feel we need a prerequisite of statistics before starting this course which was not mentioned anywhere.

Guess it is time for a lot of practice. Wish there were more assignments as well.

By Sisir K

Feb 15, 2019

Highly technical and complex in nature. Difficult for people just starting out with data science. The hands-on labs are more useful than the videos themselves. The quizzes in between videos felt a bit too easy and mostly comprised of examples (as questions) in the videos themselves.

By Raghav N

Sep 14, 2018

This course is definitely very helpful to people who are passionate about Data science and have basic to intermediate understanding of Python but this course can be much better if it includes coding assignments rather than quiz submission. It was a great experience.