FC
Invalid date
It would be nice if you could update the material since some tools have changed either name or the way they look compared to the videos/images. Very good material though, I enjoyed the course much.
FD
Invalid date
Some of the lab assignments had instructions that didn't line up with how the programs actually worked. This was particularly the case for modular flow where auto-numerics seemed impossible to use.
By Chirag G
•Feb 1, 2019
Course is outdated.
By Suraksha S
•Apr 2, 2020
Its a bit outdated
By Anton S
•Jun 8, 2021
yaa mayan lah yaa
By Tandeka B
•Apr 20, 2020
old information.
By Ritik k
•Nov 27, 2019
outdated content
By Jonethan R
•Mar 20, 2022
Outdated guides
By lavesh b
•May 5, 2020
It is too basic
By Sandipan D
•Nov 27, 2018
Videos outdated
By Yadder A
•Feb 23, 2019
It's too easy.
By JM E
•Apr 22, 2021
Needs update
By Abdullah A
•Dec 26, 2018
not clear it
By RITIK K
•May 26, 2019
good course
By Aditya G
•Jun 26, 2024
not great
By Igor L
•Oct 2, 2019
Too easy
By Farzan B
•Oct 20, 2018
Too easy
By Nahim A R
•Jan 21, 2023
Not Bad
By 손승건
•Jan 16, 2020
not bad
By Sanket B
•Jun 10, 2019
its ok
By Aurobinda B
•May 19, 2024
good
By Osama H
•Jul 4, 2020
nice
By Chakradhar K
•Apr 7, 2020
cool
By Omer Z C
•Sep 30, 2021
By Humza A
•Mar 1, 2019
A
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Outdated material that has not been updated...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The second week gets better, but the instructions are a bit outdated for JupyterLab functions such as the 'insert' tab which is nowhere to be seen.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The third week is mainly about IBM's own products such as Watson Studio, but the course is obviously outdated in this aspect with items being called different names and payment verifification required to simply creat an IBM cloud account.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.