It was really insightful, coming from knowing almost nothing about statistics or experimental design, it was easy to understand while not feeling shallow. Just the right amount of information density.
As a business student from Bangladesh who is aspiring to be a data analyst in near future, I love this course very much. The quizzes and assessments were the places to check how much I exactly learnt.
by Nedino L C•
I really like your approach on making people who are new in this field understand most of the basic concepts. I've been in software industry for so many years now and the reason why I took this course is because I am planning to include most of your courses on my team enabling program. Many thanks and cheers!
by Nafiseh A•
This course is full of great information and will lead you through the basics of data science in the best way possible. It'll also teach you how to use resources and keep yourself updated with information so that your learning process doesn't just rely on the course but also on your own effort and curiosity.
by Ahmad A•
The course was really easy to navigate through. I like the idea of automated videos since it allows the content to be up to date, but it seems that this was not the case (from the given examples).
Basic principles were also explained relating to data science, big data, types of analyses, and other concepts.
by D. C R•
The content of course was in depth and ease of understanding step by step. The question at the end of each session was refresher for the learning had in that particular unit. Over all it was an awesome experience and passionate to keep learning new things. All the best Team Coursera for a smooth experience!
by Aaron B•
The main purpose of this course is to get R and RStudio installed on your system, set up a GitHub account, and connect your RStudio program to your Git account. Some time is also spent introducing basic concepts about Data Science. This course is simple in scope, but very valuable and effectively delivered.
by Kunal P•
Learning experience is much better. I like how they don't give you all the answers in lecture which forces you to research/figure things out through lots and lots of practice. Thank you for all these courses and without hard work by these professors/staff this experience wouldn't have been possible online.
by Ulrike H•
The course provides a nice overview over the basic tools of a data scientist. The presented methods of the course are up to date. The course materials are concise. Jeff explains clearly and structured. I like the course and, although I've been working with data science for a while, there was something new.
by Ana M•
This was a great first course. I appreciate the video and having the written version together because I can go over immediately something that I might have missed or not understood well. The entire format of the course is great for learning on-line. And the material is well written and easy to understand.
by Ashja A K•
It was amazing to learn the things from john hopkins , good experience learn alot i will try to practice more and more so that i will never forget what i have learnt this is the starting of my skills i am pretty sure that they will allow me learn each and everything i want to learn reagarding datascience
by Dianne H J•
Course had a LOT of information. Really appreciated the hands on assignments (although it was kind of scary for me to be installing software in "terminal" mode on my Mac from remote servers). The lectures are done so well, full audio/visual and downloadable slides with supplemental links and documents.
by Rahul S•
Course is presented in very lucid manner and give you ample information to learn from scratch. Great course those who don't have any background in data science and willing to learn it. Pedagogy is highly appreciated and assignments are never like fun activities that John Hopkins are crafted for learners.
Great course for learners who want to step into the world of data science. Lessons covered version control using Git & GitHub and the functions of R and RStudio. Detailed instructions were given on bridging them all together to create the ultimate tool for collaborative data analysis. Loved the course!
by nethikunta p•
The course was very informative and I admired the way they scheduled and organized the course , it was very easy to understand and moving on with it.
at the initial I thought it was rushing through the content but as i started going on there phase of speed of teaching , I managed to get to there speed.
by The W B•
a really nice introduction for data science :) Although the Text to voice was a bit weird at first, I got used to it very soon. It's one of my first online Courses to complete and I really like the format. You can actually complete the course in less than a week if you have the time. Very worth it!
by Oliver G•
Ideal for anyone who has never had any experience in the subject of data science. The course lays a nice foundation of what you need to know for the next courses in the specialisation. I would say it is 60% conceptual, 40% technical, which for me is just the right mix to get started on the subject.
by Gauranga P S•
Learning Data Science has always been a passion for me. Thank you Coursera for providing such a beautiful, wonderful platform for education. Faculties are skilled and interact lucidly. Again Thank you John Hopkins University and everyone associated with it in making these course a successful one.
by Deleted A•
I think this course is really suitable for beginners like me, who have no concept of Git, Github and don't know what data science are doing roughly. Maybe for some experienced learns this is trival, but no one would be annoyed by it since they can quickly pass this context and turn to next course.
by Ravi V•
This course helped me a lot in getting the basic understanding on the data science and necessary tools like R, Rstudio, Git & Github. Now I found myself confident enough to pursue this journey of becoming a data science. Thanks to respective professors and Coursera. Looking forward to learn a lot.
by Cody W•
Good introduction to the specialization. It might be a little basic if you already have a lot of programming background, but it's nice to have the foundation in place before diving into the nuts and bolts of the software. Does a good job of gently introducing the user to Rstudio, git, and github.
by MITTAPELLI R K•
I would like to appreciate the efforts of course instructors to start a new way of learning for us and also for giving a complete course on the basics and fundamentals of the software. I strongly recommend everyone to use this course as a foundation to learn software like git bash and R studio.
by Felix N•
Very good overview of the basic concepts and tools required to delve into the world of Data Science. Explanations are easy to understand, lectures are easy to follow. There is far more detail and information involved regarding Git and R in general but are not necessary to complete this course.
by SARI R•
A very useful course with a lot to learn about the basics of programming and data analysis. I have learned a lot of things and also this course has enhanced my confidence level to a higher level. Thank you coursera and John Hopkins University for providing such a wonderful opportunity to all.
by Julian K S•
The course provides good instructions for installing R, RStudio, Git, and getting set up on GitHub. The course project offered a good opportunity to get a bit hands on with the software, but be prepared and willing to utilize outside resources (including suggested links provided in lessons).
by Karen L•
This was my first experience taking a coursera course. I was impressed with the thorough and well thought out content. The course material was easy to follow and it was easy to stay on track. This was one of the best virtual classes I have attended. I am looking forward to the other courses!
by Brandan W•
This is a very good introductory course to R, Rstudio, Git & Github, and lays down some a great little survey of foundational statistical analysis theory. I learned a great deal in this course. I would highly recommend it as a first step for anyone interested in learning about data science.