I recently completed the "Tools for Data Science" segment at IMB, and I must commend 'Aije Egwaikhide', 'Svetlana Levitan', 'Romeo Kienzler' for an outstanding job. Their expertise and passion made complex topics accessible. The hands-on sessions were invaluable, and the choice of tools aligned perfectly with industry standards. The collaborative learning environment enhanced the overall experience. Thank you for a stellar course! Rating: ⭐️⭐️⭐️⭐️⭐️ MD. NAIME MUNSHI

Excellent course. It gives you an overview of several data science tools and software. For each of them, a lab teaches you the basics and get you familiarized with the environment, user interface, and so on, without going too much into detail. It is up to the student to dig into more details if they so wish.

A typical excellent class where it takes you a few hours to understand, but it could take you months or years to specialize in the tools if you wanted to.

Adequate time and information (particularly step by step with screenshots for setup of notebook etc.) was provided in the video and related printed material. This is unlike other courses that I've take so far. So definitely appreciate the instructors and others who helped in creating the material. Although some of the DSX and Dev Cognitive Lab screenshots and steps were outdated due to the new version available, but the helpdesk of IBM was quick to respond.

Very good course for non Data Science people to have an understanding of different tools which are worth to use for Data Science field. I would highly recommend this course for any one who want to start in this field. I really enjoyed this course and kept noting all the key points. I hope those key points will serve as a reference as I move on in this field. Thanks to my Organization due to which I was able to do this course without any cost.

In this course the variety of Open Source Data Science Software Tools have been described and basic examples of their usage demonstrated in the labs. The key thing to know about this course is taking good notes from the videos. IBM Watson Studio is explained with a rich palette of tools available for a Data Scientist to choose from. Can see learning just a few of these tools to start so that a good comfort level is achieved for a student.

I have found the program very hands-on, and I like that. It is important to know the basics, and to know your tools, to be able to perform a great job later. This course will teach you how to use the basics for Jupyter Notebooks. Also, it will introduce you to the IBM Tool to make your Data Science journey better. You can always use Jupyter, R Studio, and others separately, but it is nice to have everything in one place and in the cloud.

The course was outstanding; I have the last tools needed to get started in Data Science.  If a student is not already familiar with the tools; they will experience gaps.  They will come to rely on the tools that IBM recommends to gather data, and create data models for accurate results.  But truly understand the logic behind each algorithm is key for students to fill in the gap thet may happen during the course.          

The content is very rich and covered a wide range of data science tools. Although I have no programming background, but i understand the tools used for Data Science very Cleary. I hope this course will help me to cover the future courses. Though I had to struggle to complete this course, but it is really an amazing learning experience for me. I am very happy to complete this course. Thanks, the IBM team and Coursera.

The course is good but sometimes the exercise texts are not very clear and some of the lessons are very straightforward, leaving many doubts. The course should have a larger series of exercises and an automatic correction system that facilitates the review of the exercises. In addition, it would be interesting to have a module on how to use IBMDB2 without the online platform, but through Jupyter on the computer.

This course plays an introductory role in the entire program, so that it is not difficult, rather easy to follow. However, especially if you are beginner to the field of Data Science, you will find that each class is insightful and exercises at the end of each module are interesting and fun to do. Now that I have completed this course, I find it as if an interesting and refreshing holiday was over. Have fun!!

Without any prior knowledge of data science, I completed this course on my own. Although it was not easy, I am glad that I did it with several attempts. The pleasure of accomplishment from hard work was beyond words and could not be replaced by anything else. Moreover, it gave me the courage to challenge next course.

Thank all the teachers and everyone involved in making this course available to the public.

An amazing review of available tools for data science an data analysis. Many tools are reviewed, including tools for programing with different languages, cloud for online storage etc with some handy works to get familiar to them. The practices include the procedure of creating personal accounts, free profile in the IBM cloud. One ends up having a nice overview of many available tools for data science.

Excelente Curso!! Es un curso bastante denso, contempla una cantidad enorme de herramientas para la ciencia de datos, tanto herramientas de código abierto como herramientas comerciales. Tiene unas introducciones bastante buenas sobre los principales lenguajes de programación y bibliotecas utilizadas en la ciencia de datos, y te introduce muy bien en el uso de los Jupyter Notebooks y el uso de Github.

Tools for data science is a well-designed, self-paced, intensive course that includes components of theory and practical exercises. I found the course both stimulating and challenging. The ready availability of course materials helped me both to see and experiment with many open source and some proprietary tools. This course is an excellent way to prepare for further training as a data scientist.

Good Course! Goes through the basic tools for Data Science. The course assignments are fairly easy, especially if you have worked on any of these tools before. The IBM resources on the cloud that are used for this course are fantastic, although they are slow to load at times or confusing to navigate. But with some practice, it is easy to master them and take advantage of these open source tools!

Excellent course, clear and summarized. I think that if you want to promote the use of the IBM platform for data science, you should implement a different access to the platform for academic purposes, which is not mixed with paid use of it. Whenever I wanted to use the platform, it required me to access payment information and did not allow me to use it for not paying. Thank you so much.

Good Day

I am personally thankful and grateful for this opportunity .

Thanks and Warm Regards.

ABHIJIT SENGUPTA

Portfolio URL : https://about.me/abhijitsengupta

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Kolkata , India

Skype : abhijit.sengupta357

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+ 91 6290750012

I'm mostly a marketing and brand management pro. With the AI explosion, I decided to learn more about data science. This course has been an excellent primer while diving deep into tools and methods. AI is being integrated into many of these tools, so knowing a programming language will become less important in the future. This means domain experts can be data scientists in their fields.

I did not know about Cognitive Class Labs. I was trying to install all these different packages in order to be able to work with them and make progress but I have always had difficulties. I am super excited that I finally realised that there is a much easier way to work with all these amazing tools on line without any problem :-) Thanks a lot Coursera and IBM for this amazing course :-)

The course was well structured and I got to know the importance of all the included tools and how they work. One thing, I'd like to add is the tool limitations and errors we get usually. Well, I figured out after googling and researching, but then as they were usual errors, it'd have been great if we had a cheat sheet or something to avoid those errors time to time.

It was a very good introductory course to the Open Source tools available for the practice of Data Science. The pace is normal and the contents are enough to understand and fulfill the requirements in the final project assignment. The IBM Watson Studio presented some issues but they were solved in less than 24 hours by the IBM Engineers. Kudos to the support team!

I like it. I've learned so much from it. It was exciting also to grade other students. The only problem is the tools. Though it's free, I had a problem connecting with it. So if you encountered problem with the tools you can just go to discussion. There you can ask question and seek answer for your problems. Goodluck and hope we hope we can all achieve our goal.

It is very useful to know the IBM cloud platform and practical. The cloud platform is very complicate and may do many things. It looks like a forest for me.

Some videos is old interface. If there are step by step instructions, it will save me some time to quickly start. Assignment is easy, but take time to get used to the environment and to know where am I.

I have to give it 5 star cause it was so explanatory and exciting, though the video instructions need to be upgraded cause the web interface as at April 19th, 2020 isn't the same as the Video instructions. So that needs to be upgraded!!! But you work your way round it if you pay attention!!!

Nevertheless, it's a wonderful course and very exciting!!!!

Good Course. Will suggest the learners to do optional labs and hands on with Jupyter Labs using Kaggle notebooks and explore IBM cloud and Watson Studio features such as Data Refinery to get the maximum out of this course. This course can easily take 25-30 Hours if you are a beginner and complete all hands on Kaggle exercises including GitHub.