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Learner Reviews & Feedback for Tools for Data Science by IBM

4.5
stars
28,168 ratings

About the Course

In order to be successful in Data Science, you need to be skilled with using tools that Data Science professionals employ as part of their jobs. This course teaches you about the popular tools in Data Science and how to use them. You will become familiar with the Data Scientist’s tool kit which includes: Libraries & Packages, Data Sets, Machine Learning Models, Kernels, as well as the various Open source, commercial, Big Data and Cloud-based tools. Work with Jupyter Notebooks, JupyterLab, RStudio IDE, Git, GitHub, and Watson Studio. You will understand what each tool is used for, what programming languages they can execute, their features and limitations. This course gives plenty of hands-on experience in order to develop skills for working with these Data Science Tools. With the tools hosted in the cloud on Skills Network Labs, you will be able to test each tool and follow instructions to run simple code in Python, R, or Scala. Towards the end the course, you will create a final project with a Jupyter Notebook. You will demonstrate your proficiency preparing a notebook, writing Markdown, and sharing your work with your peers....

Top reviews

ED

Aug 14, 2022

I love the detailing of every aspect of this course. The Labs, the free subscriptions and free trials provided by IBM Skills Network, everything has been so amazing. Thank you Coursera, thank you IBM.

MO

Apr 17, 2023

the best course for the beginner who is going to start his data science journey. This course tells you all options like tools, libraries, programming languages, etc. Highly recommended for beginners.

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3426 - 3450 of 4,596 Reviews for Tools for Data Science

By Karinne B

Nov 9, 2022

Gives a good high-level overview of tools used in data science and introduces some on-the-ground very beginning experience with GitHub and Jupyter notebooks. My main complaint is that often the quiz/test questions are not written well, cover content that is not mentioned in the videos, or are not necessarily measuring whether you are understanding key concepts but rather whether you can memorize what different IBM Watson Studio tools are called.

By Jarred P

Jul 1, 2022

It really feels like they are trying to sell me their product. This course is kind of an introduction to Juypter notebooks but I don't feel someone who has no experience would complete the final assignment easily. There also seemed to be a lot of information taught that seems too specific and not necessarily relevant for a new data scientist, felt like there was a lot of jargon that was not explained well and grouped up with other jargon.

By Adrian R

Mar 10, 2021

Some of the lab instructions are out of synch with the screenshots. Also some of the external sites references look and work differently then the screenshots or instructions. The section about the IBM tools is a huge dump of information that's somewhat confusing and doesn't appear very practical/usable to someone new to the field. The Git command line part looks very amateurish and is very hard to follow up by someone new to the subject.

By Miguel V

Jul 14, 2020

A bit of an overload on certain information. I could see how some people, especially those who aren't as familiar or comfortable with programming jargon, would get overwhelmed. Accessing Github and using it's commands was one of the major concerns of most students when I read the discussion boards. Perhaps some editing or reorganization in that topic is required. Other than that, I'm grateful that this course introduced me to JupyterLab.

By Yeh Y J

Jan 8, 2020

good technical guide but lack the context. For example, there is no explanation on why i need to convert to RDD, why would i want to move the paragraph around. There is no practical references that aid the understanding of the technical steps. This needs to improve especially for someone who has very little programming background who probably only heard of SQL, Python and R at this point in time. Scala, Jupyer, Zeppelin are all new.

By Diane A

Apr 4, 2020

i did learn how to do specific things but i found that there was not enough context. i.e. when would i use Jupyter? When would i use R? SOme concrete examples and exercises would have been helpful.

What was particularly unhelpful was the fact that the videos were out of sync with the tool so it took me ages to figure out what was wrong. The videos need to be updated!! i saw that i was not the only one who found this difficult.

By Abdulah H A

Jul 11, 2019

I think it would be better if the course focused on one online platform such as Skills New Labs rather than learning about multiple notebooks with multiple programming language with multiple work benches. It is to some extent confusing for someone with no prior experience in working with python, scala, or R. Nonetheless, this course has allowed me to understand more about available options which could be beneficial for experts.

By Ismayil J

Dec 24, 2018

Course provide brief overview of available tools used for Data Science. For awareness good, for getting working skills on any of them, no. At the end I get confusing feeling what to use in which situations, as if they all do the same thing. Possibly I would recommended to provide awareness bout all, but give in-depth practice, additional week, for one of the tools. It could be IBM's or Apache Zeppelin as more universal.

By Sahil V D

Jul 30, 2020

The course is too hectic. As I am coming from Mechanical Engineeering background, the words used in this course related to data science(and related software) went above my head. There should be some videos regarding the basics of the terminology related to IT WORLD( with practical example) in this course. Watching that Juypter notebook and other tools were so challenging as they were difficult to understand for me.

By Tyra J

Jan 20, 2020

I was really interested in the open source tools, but I feel like this would have been more easily retainable by taking a Python course first. Also the last week was all about marketing IBM Watson Studio as a superior DS tool but it's UX was super difficult to navigate. The video tutorials were outdated so I had to Google and eventually kept clicking until I found something as simple as opening up a new notebook.

By Surawut P

May 26, 2022

Sometimes, the link in lab activity not match the illustration pictures. Furthermore, IBM Watson is not friendly to use. When that happen, I almost always lost and can not follow the instruction. I feel frustrate when this happen, and make the course more stressful.

Apart from the examination usually ask about minor detail rather than main idea, the feedback is bad too. It is not explain why the answer is wrong.

By Kateryna C

Jun 1, 2020

It feels superficial, and I felt lost trying to do the assignments, as if I didn't have enough information to use the notebooks. I did a lot of outside Googling. If the purpose of the course was just to give a glimpse of what Data Scientists use, it did what it intended. But the experience was difficult, because I constantly felt I was expected to be able to do things that I hadn't been given the tools to do.

By Vimal O

Nov 9, 2021

On overall IBM data science professional certificate track: Pros: Content is just good enough, instructors are good. Cons: IBM watson and the platform given to practise on is awful and has terrible performance and reliability issues, most often doesnt work and had an impact on my test deliverables. I personally overcame those issues to some extent with kaggle's and google colab jupyter notebook environments.

By Vladyslav M

Mar 6, 2019

IBM Watson was updated and changed the design, it became harder to understand how create a notebook and etc.

IBM Watson is lagging, the code (Python 3.5) runs through time.

The final assignment is described incompetently, as there are bindings to the cells. In the beginning it is said that their number is varied, and then they give a binding of the context to them, because of which the evaluation is wrong

By Jeremy G

Aug 29, 2020

Course gives a broad overview of tools that are available for Data Science functions. However, I think it would be better to introduce more of this along the way particularly in the following Professional Certificate courses that focus on specific parts of Data Science. Its hard to connect the dots on what Tools are available when you don't really have the foundation yet on what you would use them for.

By Miranda C

Apr 28, 2020

I learned a lot in this course but much of it was a result of the helpful comments of my fellow students. Sadly much of the material, especially the videos on IBM Watson, was out of date and useless. I was happy to be able to google terms and read the helpful comments from other students and find my way through the course, but this course is inadequate on its own and in desperate need of an update!

By Vladimir K

Mar 20, 2020

I wouldn't say it's good introduction to open source tools for data science. It's rather IBM open tools for data science. They highly recommend you to use this cloud based IBM tools but then you will face with a lot of problems with that - Skill Network Labs notebooks is impossible to use because it will kill kernel after minute or two of idleness; it will maintenance work in critical moments, etc.

By Christopher S

Nov 21, 2019

The course has a lot of good material if you are learning about Data Science with no industry background. The hurdle to a better rating though is the outdated videos. They make the learning experience unnecessarily confusing when you are trying to apply the lessons in real world systems that have changed so drastically. With a few video updates, this would be a 5 star course for a beginner.

By Amine L

Jun 17, 2020

Too much information in a commercial format. I mean i get it that the course is offered by IBM, but a whole section presenting the different tools was maybe too much. The tutorials were not very informative and their pace was too fast. Also some vocabulary was casually used all along while never introduced at any point in the course so far. Really had trouble getting to the end of the course.

By Marcelo C O

Mar 11, 2020

The videos are outdated and do not reflect the platform currently on IBM's website. I think that it would be easy to solve, but it seens that isn't the interest from IBM. I couldn't use the IBM Networks Labs because it had been offline for many days. The support is nonexitent. Nobody sees what's going on in the forum. Despite this, the course appears to be mor informative and a basic level.

By Viktor H

Feb 13, 2024

Too much information that you should remember while practicing and writing some code but authors think that you must learn it by heart and answer where each button is located. I think this course (like the previous one) could be twice shorter. But for the sake of justice I will say that practice parts with RStudio and Jupyter can be interesting for people whithout any technical background.

By Sean C

Apr 24, 2021

This felt very salesy, like I accidentally signed up for an IBM sales seminar or something and couldn't get out of it. Don't feel like I learned the tools very in depth either. It was more of "look at all these IBM products that exist! They're great!" It was just really in your face, and I think it could be more up front what this course really is, advertisement space paid for by IBM.

By Jason H

Oct 2, 2018

Overall good but there were some dead links and ibm watson looks way different now than it does in the

lessons.It was hard to follow along because of the difference.I do understand that a data scientist is a problem solver so I took an extra 2 days to figure it out and in doing so developed some confidence in my ability.

For the price I would give it a 5 but this is an honest review.

By Baraa Z

May 1, 2020

In the end of the course (the IBM DSX section) there is a difference between what is presentated in video restructions and the real IBM cloud, it's called IBM watson studio, it went well for be but took a time (an hour) untile I've succeded to creat Jupyter notebook with the new updated clould, so I recommend you to keep updating the instruction videos according to the new updates.

By Kevin B

Oct 19, 2022

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.