Apr 12, 2020
It serves perfecty its aim that is giving a first glance of the open course tools for data science. Of course each tool is briefly touched and it hands over the student the duty to deepen each tool.
Sep 15, 2020
Absolutely Loved this course!! Challenging at times to keep up with all the terms and processes. The course provided great insight into Data Science. Would highly recommend it as your first course.
By Anton S•
Jun 8, 2021
yaa mayan lah yaa
By Tandeka B•
Apr 20, 2020
By Ritik k•
Nov 27, 2019
By Jonethan R•
Mar 20, 2022
By lavesh b•
May 5, 2020
It is too basic
By Sandipan D•
Nov 27, 2018
By Yadder A•
Feb 23, 2019
It's too easy.
By JM E•
Apr 22, 2021
By Abdullah A A•
Dec 26, 2018
not clear it
By RITIK K•
May 26, 2019
By Igor L•
Oct 2, 2019
By Farzan B•
Oct 20, 2018
Jan 16, 2020
By Sanket B•
Jun 10, 2019
By Osama H•
Jul 4, 2020
By Chakradhar K•
Apr 7, 2020
By Omer Z C•
Sep 30, 2021
By Humza A•
Mar 1, 2019
By Dominic I•
Feb 11, 2022
Outdated material that has not been updated...
The first week is mainly memorization with no hands on/interactive items.
The second week gets better, but the instructions are a bit outdated for JupyterLab functions such as the 'insert' tab which is nowhere to be seen. Items of the markdown lab simply don't work, as when it wants you to copy the html code to Jupyterlab the code is actually compiled into a link (hard to explain but basically means you would have to separately look into creating HTML hyperlinks).
The third week is mainly about IBM's own products such as Watson Studio, but the course is obviously outdated in this aspect with items being called different names and payment verifification required to simply creat an IBM cloud account. Sadly for me, any payment method selected was declined and so the process was highly frustrating.
The fourth week peer reviewed project was something that I had originally thought to be a compilation of materials earlier learned that would have to be put together and peer reviewed. It turns out that the peer review project requires skills that have not been covered in any other lesson/lab. Specifically elements of the markdown language like creating bulleted point lists, links, and the like.
I feel like this course should be labeled as intermediate just because it's outdatedness in many aspects would require a person to have moderate experience with tools/troubleshooting in order to get from beginning to end of the course.
Given the cost of this course (40 dollars a month as of the moment), I would not reccomend anyone else take it if they are planning on learning and enjoying the learning process. Instead I would reccomend only those who know how to troubleshoot outdated materials and simply wants a certificate.
For anyone else, although not completely related, I would definitely reccomend you go through free courses with free certificates on Kaggle as it is much more hands on and intiutive, with a much more advanced grading system that makes it not just easy but FUN to learn.
link to kaggle courses with free certification: https://www.kaggle.com/learn
By Léonore F L•
Jan 10, 2021
This course was presenting students with some interesting and rich information about the tools they could use, but it should not be the second course of the certificate already.
It is dealing with concepts that are far too complex yet for students who just started to learn about Data Science. These concepts are not properly described and students have to go through the course with only a partial understanding of some core concepts they would need to understand what is further explained in the course...
So many things are still really unclear to me now that I have finished this course. It took me quite some time to complete it because I felt demotivated. Now that I have started the next course on Methodology, I feel much better and I see what it is like to have things explained in a pedagogical way! Analogies, repetition, examples... All this is very important to help students navigate a topic as new and sometimes as foreign as Data Science. I was not convinced at all by this course "Tools for Data Science" and I do not think that the little knowledge I gathered will stick, as it is not built on solid foundations. I cannot be able to remember what tool will be useful for doing what if I do not know what I can / would do with data science.
The labs were good! A nice way to get proper training!
NB: I know this class is designed by IBM but when it comes to tools, it feels like the company is really pushing their tools to the center of the stage. They of course mention alternative options, but they are not dwelled on at all, and whenever they can give limelight to their products, they did it. It can leave students wondering on the impartiality of the course.
By Zachary G•
Jan 17, 2019
I have stopped going though the IBM specialization after this course - this review is for beginners (like me), who have no coding/programming background. Coursera disappointed me because instructors are not there to help - you post questions in the forum hoping that there is a more knowledgable individual who will help you with your question. And if there is no such person, then your questions will not get answered by anyone.
Secondly, it mentions that course is for beginners with no programming experience, but then some codes, syntax and computer science terms get thrown at you without explaining basics and then videos are rushed through, leaving student only confused and frustrated.
Thirdly, courses lack consistency, clarity and are overall are very sloppy - information gets thrown at you from all places with no specific structure (if you had taken courses on CodeAcademy, you will understand what I mean).
Lastly, I was disappointed by some videos from Zeppelin Tutorials where all that instructor did was just reading text from main zeppelin page! I could do that by myself.
I am reverting to learning with CodeAcademy which was my original choice, but I thought that maybe IBM will be a good name to showcase on social profiles. IBM here does not mean anything.
Oct 8, 2020
A lot of information given about the different softwares (open source or commercial tools) and the different processing steps. The Jupyter Notebook section is fine whether used on the IBM platform, from Anaconda or from a bash terminal. I spent more time than necessary to get familiar with the tools as I found some explanations really bad. Thankfully I used a lot of command lines at work to navigate through our system so I was able to survive through some of the poorest tutorials.
The RStudio section is horrible and mainly useless with no explanation whatsoever on what is done (you just have to type what you have been asked with no questioning as anyway there is no answering). That was bad but wait to see the Data Refinery section. I wonder how a video like that could be published by IBM.
At the end, I will extract and use the information relevant to what I want to do and forget about all the rest. This course is about teaching people about Data Science not about mainly promoting IBM Cloud Pak and its suites of softwares. IBM should clean up this course by removing the poor quality tutorials and update the videos as their platform and tools have changed quite a lot. I am now hoping that the Course 3 gets better...
By Aakash K•
Jun 11, 2020
This is supposed to be a beginner level course. In the introduction, it was clearly mentioned by you that no-prerequisite knowledge is necessary. This course was taught to us as if we are already some professionals in this field. A majority of the explanations went above my head. Also while demonstrating the registration to the tools, please ensure you update your course. The current version we are using and the version of the tool at the time of recording are quite different. You need to literally scratch your head in trying to understand.
For example, while using the Python environment in Jupyter notebook in Watson studio, your tutorial clearly shows us to select the Free version of the tool. But when I tried, there was no free version of the tool at all. I was given 50 units of asset after which I would be charged. Please upgrade your tutorial.
By looking at this course, I am not sure if you would focus on one tool at a time. Assimilating this much information for a beginner level learner is something un-comprehendable.
By Sobhan A•
May 6, 2020
I can say overall it's a good program. However by reviewing the first few courses, you will get a headache, but the rest courses are very useful. Some parts are really useless for a data scientist and are more useful for programmers, which I recommend you do not put a lot of time on them and skip them as much as you can.
Apart from the material, I think this certificate is really useful for you to get a job. But, if you just want to learn new concepts in data science and do not need a certificate, I recommend you to take other courses other than IBM. There are very good courses on @linkedin Learning.
In this program, IBM pushes you to work only on its platforms which is really annoying and I think this a considerable drawback of this program.
If you spend at least 4-5 hours a day, you'll be able to complete it in 2 months. The subscription is monthly and it's around $50 CAD and you can unsubscribe whenever you want.
By Hani H•
Mar 9, 2022
The IBM cloud interface has been updated but the course material does not reflect that change.yet. It's a minor annoyance but this was my first introduction to IBM Cloud and trying to follow the steps was frustrating.
Also a lot of tools were quickly overviewed but there was hands on activities for only two of them. Some tools didnt load correctly for a while (couldnt edit Jupyter Notebooks for a couple of hours). The material felt siloed and unorganized and we were jumping from one topic to the other without spending time getting familiar with the applications.
It would have been a great idea to introduce a couple of data sets at the begining of the course, let the students get famliar with them, and run this data through the tools to see the impact of each one. The current approach made the tools seem disjointed and independent of one another