Kat is a charming teacher. I think she really has a passion for it and that comes across. But the course itself is extremely poorly structured. I found myself not caring about the data (oh no!) very quickly in. I think in an effort to teach how vague questions about data can be (a good lesson...) the course became very vague and scattered itself.

Exercises are unclear and I found myself unable to complete them or even know what was being asked. The online applet through Mode worked OK, but was frustrating to learn and with no ER diagram for the databases we were supposed to use, it was a bit overwhelming. The minute you start typing, it comes up with suggestions for a million connected databases or functions, and you don't know what belongs to the course and what is default etc etc. It's a very frustrating experience.

The PDFs for the coursework are underdefined, they don't always reflect the state of the database as you find it, and the solutions videos themselves are badly edited - there was one video where I sat through minutes of Kat solving a bug on her computer trying to get a graph displayed (nothing to do with the course!) before she gave up, ended the video, and moved us on to part two, where it picked up after she'd fixed the bug.

Course needs to be much tighter to be useful.

This course has a lot of important things to teach and mostly accomplishes those goals. However, the structure of the course leaves much to be desired, it expects you to know SQL skills that weren't taught in the first course of the series, and, most importantly, doesn't respect your time. For instance, the course has you reference code from screenshots for problems rather than text of the code (you can't copy and paste from a screenshot). Additionally, the final test expects for you to reference code from the lectures or already have advanced SQL knowledge so I ended up having to rapidly resume/pause the videos while the lecturer was scrolling just to get the starter code to work with (it also didn't tell you what table to reference for the test scenario).

Kat seems like an incredibly intelligent and kind person that would be great to learn from outside of this course as she has a wealth of knowledge, but there are just some basic fundamentals to a course's structure that this lacks that make this course much harder than it really needed to be. I learned a lot about what you can do with SQL and am better off for it, but there are just some basic things that can be done from a quality assurance standpoint that NEED to be done before this course is recommendable.

This course was an absolute mess. I am not sure that I learned a single useful thing throughout the time that I spent on it. The quizzes usually included questions that were poorly worded in a way that prompted incorrect responses. Even when that wasn't a problem, questions that asked which video covered a specific question occurred. These questions are lazy, unhelpful, and a terrible way to try to teach understanding of a concept. The videos were also not great, and frequently barely skimmed the surface of concepts that seem important. Even the final project included at least one problem that was worded in a way that made absolutely no sense, and seemingly asked for impossible to produce code. An unintended concept that I did learn while taking this class is to use Google to help you imporve your code, because 5 minutes on Google was more helpful than an hour of trying to decipher this nonsense.

If you need this class for the SQL for Data Science specialization, just try to get through it. If you actually hope to learn anything, skip this course. You can teach yourself everything it covers considerably better than they do.

I did have learned something from this course, but I really cannot love it. Here are something I like and dislike.

Likes:

1. I learned to format my code better by typing together with the solution video.

2. I practiced what I learned from the last course.

3. The instructor shared valuable practical tips.

4. I like that the instructor emphsised "think before type".

Dislikes (actually suffering):

1. Peer review. I wish there are instructions for making sharable mode link.

2. The practice excercises are actually valuable but the way how it was introduced to us was VERY confusing.

3. Like many others reivewed, this course is not well-organized.

4. This is the second SQL course I took . As the second SQL course of the specilization, the first course brought me from 0 to 5. I feel this second course expects me to jump from 5 directly to 60 in week 1.

I just want to take the time again to critique this course. I found the first in the series (SQL for Data Science) way better than this one. Make no mistake, it was really insightful and helpful. However, the practice of forcing people to comment before being able to watch the next videos just leads to a lot of non-sense in the discussion forums, disturbing all others who really want to discuss. Additionally, this course was way less engaging than the first one and made considerably less fun practicing. Especially, when tasks in the PDF are only described in broken sentences and when in the actual solution videos SQL code is copy-pasted so quickly that there is no way to catch-up. Yes, one could pause. However, this really disturbs a progressive learning atmosphere and destroys the joy of coding, at least for me.

Good Riddance! On the positive side, the course covered very important aspects of SQL and forced me to learn by myself several methods in SQL. However, the course structure was very bad, and I won't be surprised if many students have left the specialization at this point, not because of its difficulty, but because of the contents. Here are some of the main problems of this course - the instructor isn't correlated with the presentations, the Mode tasks are poorly drafted and there isn't a clear guide how to use this platform (which is essential to the final project), many questions in the tests are very ambiguous. Basically I would recommend US Davis to restructure this course in a way which will be in the same high level of the first course by Sadie, and in a way it won't be so frustrating to learn it.

I had to resubmit my peer-review assignment because 1 of the graders did not know how to access my work. There is absolutely no guidance on how to create a shareable link with SQL Mode (platform for the project) or how to create well structured SQL Mode reports...

Concerning the course's content, even though the excessive difficulty of the exercises given in class was good as a way to improve our way of thinking, it was many times too much, as it made it difficult to learn and progress. Many times the questions are also poorly phrased, making it even harder...

Also, AB testing was just briefly touched at the end of the course, without giving all the foundations necessary for the students to be at the same level when going for the final project (peer-review assignment).

The use of mode made the experience for this course a bit clunky; also the final assignment could have been outlined more in line with the rubric. A model to emulate is the use of SQL lite in the first course. To add I was hoping that there would be a way to programmatically determine A/B testing vs. using an external tool; perhaps the third week assignment would be to code up a SQL significance calculator then in the forth week use that model to the data. These are the reasons why I give this course 2 stars. This of course might be very difficult given that SQL is not a functional language (I personally haven't tried this). The instruction, exercises and the design really make me stop and learn key concepts and the professor's recorded demos were excellent.

honestly, this course feels like navigating through a foreign city without any knowledge of the landmark.

class is confusing. more query statements introduced without any proper introduction to the query made this class is lacking sense of continuation from the previous ones.

the training/examples are not streamlined with Coursera's built in quiz feature. using app.mode is a new thing and the intro to the app isn't well explained.

training instructions are confusing and the solutions aren't helping, for example, we need to find what's wrong in a query, while we're confused and trying to find the solutions in the solutions videos, why not throw in graphs into the mix and make us more confused..

This course was not taught well and not structured well. I did not understand a lot of the tables used during the class. For example, the teacher could have explained what the line_item was compare to a regular item instead of us guessing. The overall course title ( Learn SQL Basics for Data Science) implies a beginner level course but the teacher within this class immediately comes out and says you need to be really good at SQL prior to coming here which is definitely misleading. In one of the solution videos, the answer was out of order. I don't want to sound rude, this is just constructive criticism. It has potential to be better.

The explainations was god enought but I think assigment/practice structure of the course was really insufficien because of theset: 1. Starter codes in PDFs was screenshot and not a code text which I can directly copy to start. This makes really hard to complite the assigments and may take too long time. 2.The questions in some assigments and in the final project was not so detailed and understandable. I couldn't be sure about what the assigment wants from me. 3. Maybe you should use a better data analysis platform instead of a Web based platform which might increase effectivness and be easier.

This was the second course in the Learn SQL Basics for Data Science. It felt like big steps were skipped in between. What was even more frustrating was that the instructor said multiple times that material should have been covered in previous courses and/or to search Google if the learner was unfamiliar with any topic. I’m certain some areas were not covered and telling students to search Google is just lazy. I also felt that the instructor did an excellent job of showing her knowledge on the material but failed to properly explain what she was doing or why.

This was good SQL practice but overall the course quality was poor. Instructions were at times unclear and unpractical (e.g. expecting students type dozens of lines of starter code instead of letting them copy-paste them). The video lectures were useless as they tended to be more about data science as a whole. Kat Glaeser is simply a poor instructor, with many glaring editing and speech mistakes in her lectures. I'm disappointed I paid for this course while there are hundreds of higher quality and free exercises and videos elsewhere on the internet.

Interrupted the course due to bad teaching approach.

It's basically that you are thrown tasks to solve with little introduction of the ideas and methods.

Then the "teacher" shows you how they solved it with tools never mentioned before. Resulting in frontal teaching with low level presentation skills.

The course seems like it was meant for offline groups which interact a lot with each other.

It's one of these "if you are good and invested a lot of extra effort" classes that bad professors at university did to weed out students they deemed unworthy.

This was a very disjointed course and unfortunately the worst Coursera course that I have made so far.

The teacher was good, it seems that she knows a lot about the SQL concepts explained in the course, but I don't think the concepts are well explained. You can learn something from the exercises, but only once you see the solution. Before seeing the solution, it is often hard to understand what you have to do.

To sum up, I would not pay again for this course, and I would not have finished it, if it wasn't needed to get the certification.

The lecturer is clearly friendly and passionate. However, as other reviewers have noted, this course introduces more complex areas of SQL with no explanation. The videos before the assignments provide little insight into how to do them afterwards and instead I found myself skipping them and then just watching cluelessly as the solutions were quickly banged out. I appreciate the efforts of the instructor but I feel this course needs to be a) refined and b) simplified for those of us coming off the first data science course.

there are so many things that I'm unsatisfied with. One is inappropriate guidance, Second is videos are full of unnecessary time-wasting frames. they should delete some parts of some videos and join them together to make a qualitiful lesson. 3rd thing is mismatching questions between the provided questions in the final assignment workbook and the questions for grading in the final assignments. there are so many lack of things to make this course to be considered as an intermediate level course.

There are some real strenghts to this course; it introduces some important concepts, and the instructor goes over them in sufficient detail in the explanation videos. However the reliance on Mode without sufficient updates has led to problems such as tables not matching either instructions or assignments, some assignments not being completable, or the final project not being reviewable by peers. I would strongly suggest more integrated checks-on-learning during videos.

The concepts and material were very good but the professor did not teach the course well. I had a hard time learning because the solution videos were not helpful. Many solutions were not fully shown, she constantly made mistakes, and she corrected her mistakes while explaining distracting me from the overall material. She did a very bad job at explaining and I was confused most of the course. I did not like the professor and I took her concepts and learned on my own.

The concept of AB testing is probably the only good topic of this course. The instructor keeps referring to tables used in previous assignments which makes it very inconvenient for learners because if you can't remember what that table looked like, you have to constantly go back and look at it. Also, the instructor assumes that everyone taking this course knows what type of data would be required for analysis in certain scenarios. Overall a poorly designed course!

If you come from the last course of this series, i would say stop this course. They expect you to know many things you didn't learn in the first course, and the teaching style is not helpful. I will not continue this certificate due to the quality of this course. Some of the answer they give out are wrong and the explanation is not good. I will change to a different certificate. I wonder why this course has so many bad reviews, so I know it.

This course was not a very smooth transitions from the basics class. It moved very quickly and assumed you knew a lot of information/had skills that were not developed in the first class which made it very frustrating. There were times you were supposed to follow specific directions but the buttons they said to press weren't there. It was very frustrating and difficult and I didn't get as much out of it as I would've liked

The course did not prepare me for the final project at the end, it was very confusing. I appreciate the structure of the first course where i got to query after given a speicfic question, this way I got instant feedback and know what I did wrong. The seoncd course asked me to query in a different website and the prompt was very vague I didn't know what was asked most of the time. This course was really disapponting .

Definatelly, not a beginner course. The gap between that course and a previous one is huge. I like the idea that the instructor tries to implement every day thing on the course but really missed it. Also, you can clearly tell that is totally unstractured and hasn't any flow. I don't think I will continue this spesialization, propably going to take another one.

Interesting Course. had more opportunities to practice, but would recommend that the incoming student have more practice and experience before starting. Still rather disorganized and some parts (i.e. explinations and subject videos0 in need of review by creator (i.e. gaps in explanations, vague directions and instruction, etc.). Am grateful for extra practice.