Pretty easy and straight froward, for someone who is already familiar with Programming Editors, and Git shouldn't take 2 hours for him to finish this course including its project, so I guess it's an exciting start for someone who is new for Programming.

This course allowed me to understand the relationship between codes, repositories, version control and especially with RStudio to discover the infinite possibilities of using R and the knowledge received in the course of safely undertaking data science

In this course was proposed the outline of the specialisation, showing in a practical and interesting way some of the principal points in the path to be a Data Scientist, I was wondering by the exposition and decide to finish the whole specialisation.

This was a very informative course and a good start to the Specialization. The course project I found to be very challenging, only because I am not familiar at all with Git and it took me a long while to figure out the right commands to perform tasks.

Some people might say that it has lots of theory, but I find that the theory is delivered in a way as succinct and impactful as possible within the short video time. Do read the written material to understand the intricacies of the in-material jokes!

Great introduction into the world of R! I have been completing this alongside the R Programming course and found the two go well together. Interesting to learn about version control and utilising Github, which I am sure will be valuable in the future

4.5/5. For a total beginner of data science, sometimes the lecture is hard to follow so I have to resort to several youtubes videos to complete the project. But the lecture is informative and well-structures, and the forum is very helpful. Thank you!

This first course of the specialization is extremely important for people like me who do not know nothing about programming, coding, computer data, etc.

When I completed the course, I was more confident to continue with my idea to start a new career.

Really intimidating, but very attractive introduction of what lies ahead by portraying a true picture of what you would be involved with as a data scientist in future. Looking forward to the courses ahead in the specialisation. Thanks you so much!!

The course is very structured, simple and to the point. We get a very good introduction to all the tools that are used by the data scientist. This module is like a MAP of all the tools that we are going to learn & master to become a data scientist.

It was an interactive session. The introduction to the tools and the examples related to various models were relatable. I am glad to have joined this course. The peer graded assignment is a good option to learn different methods in problem solving.

The course is very good for the begineers I didn't have much knowledge about Data Science but this course gave me some of the basic ideas behind data science which is really helpful .Take this course before enrolling into any data science courses.

I got an overall idea that what I need to do before jumping into the bigger topics or even starting the real data science course. This is truely very important because people who don't have any idea about this topic needs to get an overview first.

Although the course structure is well designed, I would request the course designers to reduce the pace of the robot voice as she speaks very fast and an Indian I was struggling very hard to cope up with the speed. Please this is a humble request

I am not sure how to assess, I'm advanced in many cases and gaps in others. GIT is making me crazy b/c I can't see it but logic and flow of hub makes perfect sense due to extensive SAS/STATA coding experience and stats background overall pleased.

Great and very informative ! I strongly advice to anyone who wants to start learning how to manage a data and be involve in data science field. This is an absolute course to become familiar with the essential software and technique to get start!

This is the first course in the Data Science Specialization series by Johns Hopkins University taught on Coursera. It introduces all the tools necessary for subsequent courses on data science and gives a driving motivation for the specialization.

O curso é muito bom. Para alguns pode ser que seja de dificil aprendizado, devido a o fato de ser um robô. Para mim não fez a menor diferença, uma vez que o conteudo era de excelente qualidade. Obrigado pela oportunidade John Hopkins University.

This course is the right choice for those who want to get solid foundations of R and version control. I definitely recommend it!

The materials provided are of very good quality and they come in different formats: audio and written, with pictures.

This is the first course in my last few online courses of R where I learnt how to initiate Git and Github and do things in a very formal sequential manner. Very good for people who are not too technical in nature. Simple and easy to understand.

Nice course, very complete, although being new to it I would have loved a longer lecture on thisas well as a practic examn or something similar with the objective of developing this skills sufficiently for future courses fron the specialization.

I have tried to learn a couple of times but due to busy work schedule i always left in the middle of a course or tutorial. However this course due to its interactive nature kept my attention. Finally i completed my first course in Data Science.

Course Structure is good. I could able to gain the basic knowledge & ideas about tools & questions Data Analysts work with, then could also get practical understanding about the sharing & version control tools.Looking Forward for other Courses.

Thank you very much for this course, this course helps me to have a good understanding on how a data scientist works and what are the different tools needed to work and collaborate with a different professional to work with a specific dataset.

Guides students through the basic tools all data scientists need and sets them up to both learn and apply them. A very good introduction that not only covers the theory behind data science but also shows how it can be used in the modern world.