This is a shallow introduction to SQL. Python API is shown, but not used in the assignments. The videos are OK at best, and many times, the examples are not the best, in that they don't really show why one would use, say, a left join instead of full join operation in real life. The earlier weeks need more exercices. However, the final week is quite good. At least the exercices and final quiz makes you think a little.

The criteria for the final assignment is too strict to follow. If I am able to get the right result, why bother in what way I accomplish it? I believe there are many ways to build up the code without using all those DESC method or LIMIT method, and maybe it is a more convenient way. I got 99% for the course and it really makes me annoying that I have to submit over and over again for what I think I have achieved.

This was a very helpful course - reason I'm not rating it a 4 is due to a few bugs and it was quite frustrating to submit the assignments at times, especially when working in DB2 and having to drag the tables below your query scripts and then screenshot for submission. There also seems to be an issue with the bonus week (advanced sql) whereby students are not issued the honors recognition after completion.

It is supposed to be a course for beginners, and all related with SQL is good since the tools are provided and I had no knowledge at all about the topic, but once the module 4 begins, all seems to be delivered for people who already handle Python, Pandas and have possibilities to pay the IDBM tools from IBM. I had to take Youtube courses apart to understand a little bit about the course rhythm.

I wanted to like this course more, but wow was it dry. There were a lot of small nuisances with having so many logins to access course material that made things frustrating at times. Although, the point is to get you accustomed to an IBM centric workflow, that when you start to learn it, its not bad. I did enjoy the final project, and found it to be the redeeming quality of this course.

Warning for those whose native language is NOT English: These IBM Data Science courses are in DESPERATE need of review by a native English speaker. If English wasn't my first language, I can only imagine how much I would have struggled. It is pretty unbelievable that they expect people to pay money for courses that have so many many grammar, syntax, and audio transcription errors.

Great content wise. They find a way to teach you something new that you may not come across on other SQL courses. However, I am giving it a 3 only because connecting to a database is pain in the butt. After applying all the tips by staff, and other peers from the discussion forum, I was still out of luck. Only deleting the old Db2 service and making a new Db2 helped me.

The course itself is really good, but the assignments are really broken, it requires a lot of extra work to get some of them to work and it discouraged me from finishing it, it requires some updating to get the links and images working again, plus, I finished the Honors module and got no notification or acknowledment so I don't know if I'm missing something

The course was Ok, buh then the explanations were a little difficult to grasp and when it was time for me to complete my final Peer graded assignment I faced a lot of difficulty as compared to the other assignments before now. There was a lot of difficulty accessing the IBM Db2 Database. Whenever I tried I was prompted to enter my Credit card information.

Though the course content is good and covers the essential portion of SQL and also lets you try your skills on real-world data, the course video feels outdated and monotonous and makes it less interesting to watch. In Majority of videos, the instructor shows screenshots of code and its output instead of running which feels utterly passive.

The online tools are a bit cumbersome - which wasts time - compared to other Coursera courses I've taken. For example, the University of Michigan Python courses use a much more user friendly online tool, a Runestone interactive textbook, which is a much more accessible and easier to use online tool that allows for more learning time.

The overall content in teaching is good. However, the infrastructure is poor. Most of the time wasted on building up the connection between ibm-db2 and the jupyter notebook. The failed in connection repeatedly came up for several months. I finally finish the assignment with sqlite. Totally lost the confidence with the db2.

All in all an ok introduction to SQL, have found other courses much more insightful and easy to follow. Course felt too fast at some points for someone without a Computer Science background. Too much attention on how to do things on the various IBM tools and writting SQL using Python rather than learning SQL itself.

The course itself was really cool. But the dataset of chicago public schools is bad (I had to change the name of all columns from lower to uppercase, and the leaders icon is all "weak" so db2 considers it as 4chars long, which is false, so I encoutered a lot of errors that i shouldn't have during this course

overall good course but my issue is that there are no notes provided to review just the videos and the labs, notes would've been a great addition to this course..also there is an issue of incorrect grade given in the peer reviewed assignment, i hope this gets rectified because it ruins the fun in learning.

Lecture slides are required. Please note that so much being taught in a small video may slip out of mind and to quickly go through so many syntax would have been possible only if lecture slides would have been provided.

It is not possible to look back into videos again if i want to confirm some syntax.

The material is fair but Week 6 should be reviewed. However, it took much more time than needed just because too many technical problems with Watson. The cloud service wasn't reliable and some packages were incompatible so many students had to find workarounds. The staff wasn't very present.

The information in the class is outstanding, the problem is IBM Jupyter Notebooks' kernels fail within 10 minutes, and must be reloaded constantly. The final exam requires 10 answers via Jupyter notebook trial and error, and it took me nearly 3 days of constant refreshing to get this done.

This course is not a complete overview of SQL by any means. You will only learn the most basic functions. The value here however is that the course guides you on how to write SQL queries in Python. To round out your SQL skills, you will need to take a more in depth beginner course.

The course content is very good. The so-called teacher-student "communication" is dreadful! I would never imagine that paying money for the course, I would be so explicitly ignored by the teaching staff for weeks! I even passed the deadlines due to multiple tech problems.

I felt a bit let down with the final assignment. Frankly, I was expecting a, way more Python proned task but instead the assignment was incredibly simple, pretty much what I would do in any RDBM. No Pandas, no MatPlotLib, no ScyPy whatsoever.

Overall the course is okay.

Some quizzes include questions about materials not yet introduced. The material could be much more interesting with more interesting and interactive examples. Hands-on Labs should include new materials rather than letting the students rewrite given queries in sql.

Some of the instructions in the course are not as clear as those provided by other Coursera's courses. There are some sections with outdated screenshots and typos. This disrupts the learning process and requires extra time to guess and sort out the materials.

Decent course. The SQL code is somewhat different and you need to practice it a lot. I do not think you get enough practice to really know SQL just from this course. There is only a few labs and even in there you only actually type a little bit of SQL

Less / inactive response on Discussion forums. Lots of issues that has been reported over months but not fixed. Course content is good. But Week 3 assignments, which was important for me, took ages to finish owing to error on practice environments