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nice

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BEST

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Good

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M

The course itself is good. But the amount of material covered is staggering large compared to the previous 5 classes. Why cram so much into this one class! The material is broad enough that it should be covered in 2 classes not 1. And as I've found in all the classes in this certificate program, there are not enough problems given to help students exercise all they are learning. There should be problem sets (with answer keys) given after each week that helps to drive home the important concepts. These could be optional, but I think it is imperative that students have an opportunity to work through more problems to help lock all of this important information in. There should also be links to places to go to learn more about each presented topic.

And the amount of errors in both the videos and labs is really bad. The class preparers (IBM) have done a horrendous job of catching and fixing the multitude of errors in the videos & labs that simply lead students astray. They have to find some method to get all the material correctly updated quickly and I suggested they should keep an ERRATA PAGE that lists all of the known errors that haven't been fixed yet. This would help them to keep an active punch-list of what has to be corrected and allow students to more easily check if a problem they are seeing is related to incorrect materials without having to scrub the forums to try to find answers. And the forums are not run very well. It generally takes a day to get any answers and the answers are not very thorough and in many cases just wrong. Students need a better way to ask questions when they get confused and the answers should be completely explained and relevant.

Although the labs were pretty solid and helpful, the assignments were equally terrible, lacking depth. it seems like the course developers didn't give much thought to the level of problems being asked in the assignments. Most of the assignments contained 2-3 problems that too with absolute basics. The last few modules felt a bit rushed without proper explanation of some concepts as in why it is being used. Moreover some topics were taught erroneously as one can see from the respective forum discussion of the particular week.

could have been thorough with the assignments with problems solving emphasis like we see in the real world scenario. something like a dataset is provided and some relevant questions are asked based on the data. would have been much more helpful for aspiring data analysts. 3 stars just for the quality of labs.

Good for some one just wanting to dip their toes in the know how of the data science. could have been much better with proper formalization of assignments.

It's difficult to rate this course, because based on other courses in the data analysis program I had low expectations. I am not sure this is good for a beginner, very poorly explained, the person who wrote it is knowledgeable, but he is not a teacher. You will struggle a lot if you don't already know a fair amount. I had to go to third party internet sources to understand a few things. But, this is pretty cheap and easy. I was looking to learn and to show a credential certificate, this supplies the latter, but not so much the former. The most disappointing issue is the time we have to spend with easily fixable issues, such as code not running, no upload buttons for some test answers. You have to search thru a lot of other discussion issues to find out what to do - after spending hours trying to figure out on your own - very disrespectful. I am ok with typos, but it does show the entire thing is very sloppy.

I am taking the data anlayst cert and this course is the first one in the series where I hit a wall with what I had already learned (I pretty much forgot most of it from my data science course and ml course on udemy), so i watched the videos a couple of times and did the labs. I have to say the udemy courses on data science and machine learning are far better and more advance (given that is all they focus on). Some of the questions on the quizes seemed like it was disconnected from the videos and relied on the labs to fill in what they didn't teach in the videos but even the labs seemed lackluster. The last question on the peer review always gets me and I have to say it usually takes me a day or two on the last few questions while the rest of the questions I can do in a sitting (maybe 1-2 hours). Over all I am not that impressed on how they are presenting and teaching the information.

Course content is good, but the modules (and in some cases the code itself) definitely need proofreading.

Also, students really should come to this course with a solid grasp of python, and quite a bit of mathematical background in statistics. This course will show you how to use various python packages to perform different kinds of regression (simple linear regression, multivariate regression, polynomial regression). The course does technically introduce the mathematical concepts, but very, very quickly. If it's been a while since your stats class, I would definitely recommend brushing up on the math (at least the Ordinary Least Squares method of regression) to be prepared to take advantage of the content in this course. I think Khan Academy has some good content that might be helpful for review.

Pros: The labs (guided worksheets that ran in Jupyter) were good, and were how I learned the material. The final project was also pretty good, with clear instructions and a reasonable challenge level. Cons: The video lectures were not at all engaging, and I mostly skipped those, or just skimmed the transcript. Occasionally there was a lack of alignment between the videos and the labs, such as a different method being used than that presented, or the videos on Python DB API which never showed up in the labs. Also, the multiple choice assessments were terrible - most questions were trivial, a few obscure, but almost none effectively tested either programming skills or conceptual understanding.