Outdated

Too easy

If this course exemplifies how IBM does business, I do not wonder, if they would go out of business soon.

If you are interested in Data Science and Data Analytics, but just starting out, the Google Certificate Program on Coursera is a better fit for you! The actual insights into Data Science as a Science here is quite low compared to the length of the course. You can see that the course was designed by someone who is a Data Science practitioner but has no idea how to conceptualize an online-learning-format...

The content of this course, in part, is quite interesting. However, it is by no means a beginner-course and gives you hours and hours of highly software-specific content which, if you do not use or need the software which is featured, does not add any value to your path!

The graded tasks made it unbearable for me to follow the Course. They require you to access third-party websites where you have to manually login, create an account, verify it at least 3 times (with your credit-card as well, which did not work for me, so I was unable to continue, if I wanted to have the certification at the end)... Please review your strategy.

It was a lot of overview. I honestly felt like I only learned definitions and what IBM tools look like and didn't get to dive into any real projects or examples. I was very disappointed in the limited opportunities to do anything real with the hands-on projects. They were too simple, like how to create a Jupyter Notebook, or play around with nodes. When I tried to code alongside some of the instructors on the optional GitHub sections, I didn't have access to their repositories or data, so I couldn't really do anything. In other videos the programmer completely skipped over important steps as if we had used the product before, or failed to provide any context so we didn't know what the goal was - so it was just some random exercise that barely made sense and wasn't much help to me for applying it to other real world situations. I don't feel anymore prepared to use these tools, and I got a 100% on every project and exam. I was expecting a whole lot more. I hope the next courses are better and I actually get to learn how to do something worthwhile.

The second module of this course appears to be poorly designed, with little effort put into pedagogy. The material bombards learners with a plethora of technical names and terminologies without providing adequate explanations. As a result, students are only taught what to do, but not why they are doing it. As a learner, I found myself simply following instructions to click here and there without understanding the purpose behind my actions.

Despite the course's introductory claim that no coding or programming experience is necessary, I feel that I haven't gained any significant knowledge from this module. I've only memorized a list of tools and programming terms, without grasping their meanings or applications. It seems that the course designer assumed that learners already have some familiarity with the subject matter, which is not the case.

Furthermore, the lessons themselves are delivered in a tedious and confusing manner that fails to engage students. Overall, this module leaves much to be desired in terms of its instructional effectiveness.

This course is not practical at all--it's a detailed overview of concepts that, for beginners, are meaningless until you begin working within those constructs. Furthermore, the online IDE is not functional--it will not load and indicates it is under maintenance or gives an error code. So, in order to complete the practicals of this course, you have to set up your own environment, for which there are no instructions. Fortunately, my husband is a sr. software developer and was able to help me troubleshoot setting up Rstudio, wherein the links, libraries, and other resources are all out of date.

Furthermore, I'm now 5 weeks into this program and have not learned anything. Fortunately, I know I am interested in programming and data science already after working in other resources (e.g. Data Quest) that provide actual hands on education, rather than a computerized voice reading script that contains erroneous details with no immediate practical application.

Such a disappointment. I expect more from IBM.

There are issues with the final exam preventing people (including myself) from passing. These issues have been raised going as far back as a month without any moderator intervention (from what can be seen on the forum). Despite there being 20 moderators to this course, there appears to be just 1 active moderator and they havent responded to this issue. There is no way of contacting staff to raise this as an issue to be fixed except to raise it on the forum. In doing so, you break the Coursera Honour Code (as Ive just discovered). Im currently unable to complete this course due to this issue and Im hoping this one star review brings the matter to the attention of the staff responsible for the course.

This course should be combined to the previous course. Totally unnecessary and fruitless. Being able to distinguish "open source" and "free access" is hardly anything useful for a data scientist, while important things like "WHAT'S THE BENEFIT OF LEARNING MORE THAN ONE LANGUAGES" are never picked up to motivate the learners. Before the course, I had no idea about Julia, Rubic, or C++, and after the course, I still don't.

On the other hand, this has nothing to do with the instructors. I believe they are just following some designer or superviser's order to read the script. I appreciate your work and effort, despite I don't like this course. I also thank Coursera for their financial aids.

Very poorly designed. The course, from week 1, video 1 uses terminomogy and talks about things that are only introduced in the later parts of the course so for someone with no prior experience it's really hard to understand and follow. Also, the videos are based on an older version of IBM Watson Studio interface so it's difficult to follow the video and do the exercises alongside. There are some optional videos and assignments but these are tested in the practice quiz. For those who opt out of them it's impossible to proceed with the course unless they complete the quizes.

I am really starting to regret investing my time and money in this course. I expected much better from IBM.

The entire IBM watson studio is is a massive disaster in this course. Everything went fine till the watson studio came into picture, after that there is no learning , your precious time will be wasted to configure a broken system (which will not work in the end) and that has almost no relevance to what you have signed up for.

From there onwrarsds the videos and the content do not match and you will get completely derailed from your learning because someone wants you to use their product . This is not learning but almost shadow selling practice.

I was in for the entire course , but will now need to think if this is worth my time.

Hands-on parts do not work at all, after more than three weeks trying to solve all issues with the IBM Cloud I decided to drop the course due to being charged and not getting decen support to resolve the account settings issues.

If you come here for hand-on labs and learning go elsewhere. Jumping through hops, and dedicating more time troubleshooting the account permissions is awful. Not a single step-by-step guide worked in regards to the IBM Cloud due to this... Staff did not solve my issue after three different agents tried, and basically gave up.

I do not recommend this course; however, as it's part of the Data Science Certificate it's unavoidable. The course is basically an introduction to an IBM online software that lets you use R, Python, etc. without having to download them. That's fine, but it could realistically be done in about five minutes instead of the two hours the course takes to complete. My advice is either don't take this class if you aren't going for the Certificate, or go through it as fast as possible if you are going for the Certificate. This course was a waste of time.

I hate to give this comment. Poor quality videos and study material. Not simply it misstated the fact that this is a Beginner course, there is also lack of effort in each of the videos made, making beginner very difficult to follow due to frequent switch of screens, making corrections in the video... The Reading/Lab section is also not helpful in terms of giving clear instructions. I only understood 10% of the materials from this course and learned everything else by myself on Youtube and other sources. The videos definitely need to be remade.

This course is a huge disappointment. It is more of a promo of IBM Watson Studio than an actual class. It would be much more useful to make a course about the Anaconda framework, which is a useful desktop framework that I believe many data scientists actually use.

The Watson Studio does not seem to be that good either. It is not exactly intuitive and it takes some getting used to before you can navigate through it. The instruction videos and pictures in the lectures do not help much since they are out of date. It is slow too.

The videos were fairly informative. They only instructions on how to install/access some of the programs and platform use, most of this information is incomplete or obsolete as certain platform were still inaccessible. e.g I had figure out how to download Jupyter Notebook myself, and lucky I did as that was the only way I could open the handout files in the course - the links they provided NEVER worked. Even the final assignment had two different sets of instructions, causing confusion and frustration among students.

Most of the videos are outdated and even the written lab instructions can use the incorrect terminology. This seemed to be more of an advertisement for IBM's data science tools than anything actually helpful. The section that covered the various languages and environments was decent, but a lot of the course feels like they're putting the cart before the horse... going through advanced machine learning programs before actually teaching anyone the fundamentals of data science is *not* the right way to do this.

Program information advises that this course is ideal for beginners with no prerequisites required. This is absolutely 'false'. Week 2 of the program is most certainly about programming, writing code, utilizing Git/Github and a video with an instructor going 90 miles an hour offering instructions on creating a new project that was totally confusing which lead to my decision to cancel my subscription of this course. Refer to Week 2 Discussion Forum for comments of other participants. Very disappointed.

Videos seem to be copied in from third parties. They do not have a logical progression and often overlap.

Many instances of the video showing an obsolete version of the software to the point that it is impossible to follow the instructions given, and the students must scour the forums or google to find their own solutions. This type of learning is not worth paying for.

Exercises were not educational. My only takeaway from this course was one sentence summarizing the tools given and markdown shorthand.

Very poorly organized. I was taken straight to the video section at the beginning of this course. Unfortunately, the videos dive right into coding in Python, even though the first course in this series had never discussed Python!

Also, the quizes do a poor job of educating someone like me who is new to Data Science. Important subjects are skimmed through in a very ad hoc fashion, and then the quiz begins, but you cannot reference the notes that cover that quiz.

Overall, very poor course design.

As an introductory course, (which it is supposed to be) this course is awful.

The videos consist of large amounts of technical jargon that are not understandable to someone who is a beginner. There is very little explanation of why or how something is being done.

Many of the instructions have not been updated for the most recent version of the tools .

There are many, many, many confused people on the message boards over the last few months, yet nothing has been done to correct it.

The videos are outdated for several months now. The content must've been good before, but now it is useless considering Watson Studio has been updated radically.

We're paying real non refundable money for something like this! This is not acceptable. This issue has also been raised in the discussion forums but nothing has changed.

I have been digging in the forums trying to follow the course but It is impossible to !!

I feel cheated, and so will you, if you enroll here!!

One of the most frustrating courses I've taken yet, mainly due to outdated materials leading to inability to follow instructions. One cannot create an account in IBM Watson Studio, and the UI's shown in the material are also not the updated UI, leaving the user to have to Google every other second to follow the instructions.

Week 3 felt more like a marketing and training effort by IBM, rather than the insightful instruction the former weeks were. Utterly annoying.

If you are looking for a middle-school level course with a (un)healthy side of IBM product marketing and advertising, this course is for you. Perhaps I have been spoiled by the good quality of Deeplearning.AI and Andrew Ng's excellent courses with their good coverage of the topics. They provide excellent slides you can download and annotate during the lectures, and WORKING labs that have a good balance in implementation difficulty and insight into the problem.

They push you to use non functioning IBM tools (they crash, you have to register but need to look for ways to by pass credit card requirement, etc) and advertise some products of IBM related to Data Science. The whole course is except GitHub and RStudio sections is total loss of time. If you do peer graded assignments in Watson Studio, it does not work, so you have to do it again with GitHub. I have never seen such an unnecessary course in my whole life.

The peer-graded assignment system is broken. I completed all tasks entirely and to the exact instructions. I have been deducted points for no valid reason by my peer. The staff response to me in the forums is that I need to "reattempt and resubmit". Where is the oversight to ensure peer-graded assignments are being graded fairly and correctly? What am I paying for? I shouldn't have to waste my time resubmitting due to incorrect grading by a peer.