many typos, errors, mislabeled... just felt like a sloppy product were paying for. I was very frustrated as well by certain features not functioning... for example, after following specif instructions to share a notebook, just as I have done many times while working on this certification... testing the link comes back as unshared no matter what I do. This and the SQL course have been the worst so far in this Data Science cert but at least this course ended up marked as completed. If I wasn't already this far invested in the cert I would definitely quit and use free resources while I built my portfolio.

-1- The training and quizzes are full of errors. You need someone to actually review the content before publishing.

-2- The education focused more on the mechanics of how to run certain commands to obtain results rather than explaining why a data scientist would want to run these certain commands and how to best interpret them.

-3- I would embed more but perhaps smaller lab assignments rather than going over many concepts and making the person go through the steps (with minimal explanation) at the end of the module. This is particularly applicable for weeks 4 & 5.

Not a very good course. The information given in the videos was not explained well and key concepts seemed to be brushed past. The graded assignments were very dumbed down and did not reflect the difficulty of the videos. This was quite lucky though as the videos were not very good either. It seems like the graded assignments were dumbed down so that the course could actually be completed without further background reading.

More information should be added, longer length videos, and get rid of the peer-review system. Lazy.

I would not classify this as a BEGINNER course that only requires Python and Jupyter Notebooks knowledge as advertised. Statistical knowledge should be recommended before enrolling in this course. In one video, they just threw out acronyms like SLR and MLR before these were even explained. In addition, with the amount of plots that they made us do in this course whose syntax are very unfamilar, I feel that should be after the Data Visualization Python course in the Data Science track.

There were so many typos and errors about the very topics they were teaching. It is as if they don't actually care that people are trying to learn this and just view this course as a way to promote their Watson Studio. Normally I would forgive these errors, but there are programmers so paying attention to detail is paramount. Also, misspelling method names while you are teaching those very methods and then never showing how to spell them again makes for some serious confusion.

The final peer graded assignment has considerable coding issues. Regplot does not execute in the Watson Studio despite proper coding. During submission one question does not have the arrangement to upload JPEG file for submission so all you can do is post the code. The Q8 is dropped out of the blue with no reference availabe in any of the courses.

The course itself is very informative but it is very evident that no one is reviewing whether everything is working properly.

Unfortunately it's a bit rushed and the statistics module should be expanded and taken apart. The scripts in some "on-screen" quiz don't work and no matter what you type it just doesn't go wel. The quizzes are really hard and the whole module should slow down, and take the most important subjects and develop them. This is, ofc, a crash course and you can't expect more than this, but so far, it's the only downside to a brilliant professional course.

Thanks Coursera and IBM for providing this condition for all Enthusiasts.

In my opinion, in this course, Python did not learn in the best possible way.

I'm very sorry that your website does not verify Iranian users,

Your goal is to provide education for everyone,

Why should we, who are interested in education, be influenced by politics?

Isn't education the best way to help deprived countries?

I feel that this policy has no place in educational justice.

This course is not friendly to new beginners in Python. Especially the weeks 3-5 are too intensive without any real explanations of the logic behind the code shown. Linear Regression, ridge regression, etc are too advanced for new joiners who struggle with basic python. Also, there are some erroneous slides present in a couple of videos that add to the confusion. Would not recommend this course to any Python beginners.

Bad final exams, little to none explanation of information, lazy test and text writing. I was not interested in this course, I did not manage to learn much due to lack of theory and explanation why do I need to count these scores, what do I achieve with them and how do I choose methods. I feel like authors of this course are well educated on theme but did not care much to explain it to new learners

Course content not explained properly. Instructor introduced the topic and very less explanation on the topic provided. I have to study the topics with external help to gain the proper understanding. I would suggest to the course designers to redesign the course content with emphasis on explaining the concepts. All the topics covered under this course are lacking on explanation part.

Excelente curso, muy pedagógico, ilustrado, teoría y práctica hacen posible el aprendizaje. El feedback es fundamental y no lo proporcionan. Los script deberían aparecer al inicio para ir desarrollando el proceso, los codigos están desactualizados, hay funciones que no están vigentes en Python, librerías y funciones desactualizadas retrasan el avance, optimización y resultados.

Course starts off great up till and including module 3. From Module 4 (model dev) course gets a bit hectic and needs to be broken down smaller sections with more explaining. Important difficult concepts are packed into modules 4 and 5 more time and explaining is required here and quite honestly i have processed nothing from those modules 4 & 5 and i redid the modules twice.

This course was riddled with errors, it was honestly really hard to follow. It's also extremely frustrating that the errors were pointed out by others for a really long time (several months for some), and none of it were fixed.

The subject matter was also extremely difficult to follow and the explanations provided were insufficient for beginners.

The final assignment code had some major issues. I kept getting the error 'NaN, Infinity, or big data type' whenever I tried to compute inspite of my code being right (I cross checked my code with my peers assignment as well). The videos miss out several critical bits of information. This course was a very frustrating experience for me overall.

Course started out alright but towards the end if became more about simply plugging in data into imported functions without a deep understanding as to the underlying mechanics. The part about pipelines was especially rushed.

Labs should provide new examples for students to work on instead of asking students to slightly modify code.

The devaluation of this specialization course reached the lowest when ADVANCED STATISTICS was introduced to all students without MENTINIONING in the course outline. It should have been ONLY for ANALHYZING the dats , instead of trying to cover whole of modeling and evaluation in a few slides which is never enough.

DISAPPOINTED.

This course is okay. The practical exercises are very easy. Therefore you don't learn that much. It's mostly choosing between one right and two ridiculous answers and copy-pasting code that was introduced immediately before the task. I'll probably have forgotten most of it by tomorrow. There are better tutorials on youtube.

Worst course I’ve ever taken on Coursera. It starts off ok, but quickly goes downhill. Many concepts very quickly or poorly explained; lab assignments filled with typos and errors and in some cases not connected to content in videos. I finished the course, but it was painful and I didn’t learn much. Very disappointed.

Rather poor way to get hands on learning. The "lab" does not offer an effective way to learn. This course was a poor substitute for a real instructor. Also, the last two weeks' material became more complicated but the information supplied to learn it did not increase nor provide clear or different explanations.

This course is not for anyone without pre-existing knowledge of statistics and basic python. Although I made it through the course, I ended without feeling confident I could apply any of the learnings on my own. Other more interactive coding courses I have taken have proven far more useful that this one.

Concepts were not explained in detail. Exercises were also very easy. Overall it was not enough for people who're looking to learn the concepts in depth and apply them to some real-world problems. Since it's a paid course expectation was to learn something substantial from it, but I'm disappointed.

The course itself 5 star. But because the lab experience is so terrible, I minus 3 stars. Please fix or remove Cognitiveclass completely from future courses, it delays my learning and interrupt my focus on the subject, there are 3 more courses to go and I can only expect more bad lab experience.

A lot of inconsistency and errors of the code in the videos presented. Expected a better quality for a course from IBM tbh. Also the assignment does not leave any room for creativity ut is merely a "code-along" exercise which does not require a lot of thinking...

Instructors seemed more like customer service reps than teachers. Their limited knowledge was a real drawback. The listed instructor does not teach this course. There really was no good information once the course hit pipelines and hyperparameters.