After completing the course, I got an idea on the tools that are used in Data science and also the hands-on learning helped a lot in improving the skills

Good review--I enjoyed coming up to speed quickly withe IDE for Jupyter notebook using Python. So much easier to debug code based on the "cell-structure"

The steps the video has you walk through and the actual platform are slightly different which can be confusing. Overall, great introduction to the tools.

Good hands on experience using jupyter notebook and open source tools! But the videos needs to be updated according to the new IBM watson studioplatform!

I think you need to update the assignments involving IBM Watson. The instructions were missing key instructions. Like "Save Version" instead of "Save".

A Discussion on Data Science Tools that IBM provide for Free(need to upgrade for more Resources); Which are very much sufficent to complete this course.

This course offers a very good introduction to all the tools used by data scientists, along with explanations of the various features available therein.

O curso é excelente, mas senti falta de mais exercícios práticos aprofundados. MAs super indico para quem está interessado na área de Ciência de Dados.

Its benficial as helps in upgrading skills as gives hands on expericience through various lab work assignments on important tools used in data science.

The course kept me motivated to go on with my pursuit of becoming a data scientist. Still learning and waiting to see what other courses have to offer.

The course is a basic introduction to a few data scientists tools, but not for practice. I Would like some project that could be written on the resume.

Course syllabus is good and covers almost everything as mentioned. But the software tools are upgraded and that need to be updated in Instruction sets.

It's good course. Really helped to understand overall data science tool available . Hands on experience helped me to get a feel of how the tool works.

Overall great course - sometimes lectures were not very refined; I liked the final assignment, which required to research commands on Jupyter Notebook

Interesting overview with easy to understand practical examples on the one hand but also too many shallow descriptions of existing data science tools.

A good overview but the videos need to be updated to reflect the way the platforms look right now as they've been updated since the course was create.

Text information in videos about RStudio wasn't always in correspondence with thing were done on screen, and in my opinion it can be improved overall.

it have lots of information however this informations is not enough to learn the fundamental even the general knowladge. and everything is mixed here

I feel very excited to gain more knowledge. It become very interesting as I go through each course. Thank you Coursera for your support and guidance.

It was overall a good course but it felt a bit outdated. I think it can be improved by including modern tools and not focusing so much on IBM Watson.

Good starting point into what Notebooks are, and what you can do with them. I only wish the assignments went more in depth into the tools and coding.

Good overview of tools that are used. Still basic information but starting to become more technical if you are apart of the IBM Data Science course.

Overall course was very short but it was good to know the basic knowledge of tools integrated with IBM Watson such as Notebook, RStudio, Spark.etc

A very good intro to the tools used in data science, good hand-on. The Data Refinery lesson could have been better explained, it was rushed thru.

The course material is not up-to-date as IBM Watson Studio is updated, therefore, all the steps are not valid anymore. It is very hard to follow.