Sep 08, 2017
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.
Apr 24, 2018
This course was a good intro especially in setting all the necessary software for future courses. I suggest to read the manuals, books and other readings the profs suggest. The resources are helpful.
Oct 16, 2019
This course is perfectly suitable for people who have passion in R or data science, and has some basic concept of statistics but not a specialist yet. I am a undergraduate student majoring in public health .I choose R for my first scientific tool because of its various utility and applicability to data analysis. But I also want to try to learn some Python in the future. Thank you professors, and my dreamy school--JHU!!
by Dhiraj K•
Nov 05, 2016
To start with, I have enjoyed this experience of online learning a lot and this is my first online course. The structure of the course is very well designed. The platform is very user-friendly. Although it was just a basic introductory course, it is just a step towards learning more interesting things from a renowned university and very good professors. Looking forward for more quality courses. One step at a time!
by Lourdes M S V•
Dec 26, 2019
It is a great course for begginers in Data Science. The videos are clear and easy to understand for non-english native people. I think it is overwhelming the first step with the tools: R, RStudio, Git and Git Hub, but, if you dedicate enough time to read the material and manuals, you can do it. The fourth unit was delightful. I learn a lot and I want to say thank Coursera and JHU for this opportunity.
by Ron L•
Aug 10, 2018
I have had a Github account for about a year now and I have never used it. Version control is an important part of programming and data science process so being forced to use it by via assignments was a great touch. I am comfortable loading repos now and I have the tools to use Git to have it on my local machine. A great introduction to what is turning out to be a pretty exciting and beneficial class!
by YI W C•
Sep 26, 2019
It is a great intro for a beginner if you want to get to know Data science in a broader way. I highly recommend people who are interested in data to join the course. Besides, the course doesn't have to spend many time every week. The content of the course is organized well in a slow path and can also gain more confidence after taking the course, which may be helpful for the following learning.
by Clare G•
Feb 17, 2017
Very well received by this beginner. I appreciated the time taken to offer an introduction to the command line, which was focussed on the immediate commands needed to continue with this course. Many other data science courses either overlook any kind of command line tuition, or they point you to an overwhelmingly large other tutorial on the subject which would take you 3 weeks to complete.
by Charles D•
Jul 05, 2016
This is a nice course on getting and installing the data scientist's tool box. In the future, this course should be improved with an example of creating files in Git and pushing them to GitHub. Although issues were addressed by peers in the class, going through an example before the course project will very much help future students with no experience. Great course. I highly recommend it!
by Christopher A C•
Mar 28, 2016
This is a wonderful introductory course. I allows one to get an idea if they would like to continue towards the specialization. I would suggest taking this course with the R-Programming course. I have a very basic knowledge of Data Analytics and I could have taken the first two course simultaneously. However if you have a incredibly busy schedule just taking this course would be fine.
by Francis S P•
Oct 29, 2019
I recommend that beginners, coders new to data analysis and anyone seeking foundational experience with Git, collaborative coding or the R programming language start here. It does not dive deep, but does introduce interfaces, basic syntax, routine operations and some commands in the technical setup portion, and also goes into test design and glosses the general field of study nicely.
by Justin A•
Jul 15, 2019
Excelente curso. Brinda una introducción a la ciencia de datos (Data Science) y las capacidades de este campo. Se configura RStudio y se aprende a utilizarlo, junto con los repositorios de GitHub, y se muestra la manera correcta de obtener ayuda con los problemas que puedan presentarse. Al final, se crean archivos con RMarkdown, y se introduce Big Data y el pensamiento estadístico.
by Sheri M W•
Jun 07, 2016
This class is a great introduction to the tools needed to begin working on data analysis. The assignments provide just enough instruction to cover the basics and propel you toward uncovering additional information on your own. The assignments are structured in such a way that you must pay close attention to the lectures; then analyze and apply them on your own. Great course overall.
by Arijit D•
Dec 27, 2017
Beautifully set series of lectures that gave an in depth view of what Data Scientists are thinking of in this modern era of human excellence. The slide font to be slightly increased and the sound quality too.
My teacher of the course has given his best and their could be no comparison of his efforts.
Thanks to team Coursera for setting up such a beautiful set of learning material.
by Jose A R N•
Oct 16, 2017
My name is Jose Antonio. I am looking for a new Data Scientist career ( https://www.linkedin.com/in/joseantonio11)
I did this course to get new knowledge about Data Science and better understand the technology and your practical applications.
The course was excellent and the classes well taught by the teacher.
Congratulations to Coursera team and Instructors.
by Nino P•
May 24, 2019
Not really interesting course, but good for start. You won't learn much beyond setting up github account and downloading R, but it fits well in the overall specialization. The feel is that this course is like the first day of school, you don't do much of work, but you still need to come. I do not recommend taking this course alone, but I do recommend taking the specialization.
by Mohammad K A•
Sep 17, 2018
The Data Scientist’s Toolbox Training helped me learn the elementary and essentials of data science concepts as well as it is interesting project submission and reviewing others’ submitted projects. It is an incredible learning experience from Coursera’s Data Science Course from Johns Hopkins University industry experts. I would like to rate my Data Science instructors a 5/5.
by kalluri v r•
Feb 13, 2016
The Data Scientist's Toolbox the second course that i have taken in the Coursera. I have completed this course in a short time but the course is awesome and providing info from basic and videos are helping a lot. I think to become a data scientist this is the best place to start pleased to complete rest of the course also. Thank you Coursera for providing such awesome course.
by dimitrios t•
Apr 06, 2016
The course has been designed in an optimum way so that no strong backround in programming or statistics is required. By the end of the course you will be familiar with the necessary tools (Rstudio, GitHub) for data analysis. Moreover you will have a sound knowledge of the basic concepts in data analysis. It is an excellent way to introduce the student to data analysis.
by Filip B•
Mar 11, 2016
This course is (as stated) suitable for beginners on the subject. It gives a very good introduction to it, and helps people learn more about what the data science is all about, how it works and which tools are usedby data scientists.
This course helped me to determine if the path I was thinking of taking as a career options is really interesting for me at this point.
by Rayne K•
Jan 27, 2016
So far this course is given at a pace that is just perfect. The instructors explain concepts in ways that make the subject matter easy to learn, particularly for someone who loves data, but is terrified of heavy mathematical concepts. I've taken similar courses at local community colleges where class size is much smaller, and have been very disappointed. So f
by Edmund J L O•
May 11, 2016
This course gives a wonderful introduction to the world of data science. You'l probably finish it with plenty of time to spare which makes jumping in the middle of the next course very tempting. I did that and i had a hard time. It would be best to familiarize yourself with the other commands in github and explore the many helpful sites instead.
by Igors K•
Mar 12, 2019
good tool tips but with some hard to make SSH and pull not working downloaded github desktop and take projects from RStudio and pull, using github desktop maybe add some tips for this program because to some person it will help like me, every have diferent PC and language.(Searched google every writing about some space not about solving problem)
by chitradeep g•
May 16, 2017
I would like to thank Coursera team for providing such a good opportunity specifically the mentors of JHU, for sharing excellent video lectures. I would recommend my friends, colleagues, and juniors about this course, who is having keen interest to grow into the field of data science. Looking forward to complete the upcoming series of sessions.
by Theresa B•
Aug 12, 2018
I really loved the presentation style. It cratered to all learning styles which I find to be essential for online coursework. The information was basic, but it never hurts to have a solid foundation before going to the next level. Since the next course really throws learners into the deep-end, this course is necessary to be ready to go.
by Pavel T•
May 15, 2017
That was introduction to Data Science specialization. Not too valuable as independent cource, but basic for whole specialization. Speaker briefly informs us about purposes and specific of data scientist job, indicates common mistakes and review tools for data analisys. Narrator is pleasant, seems like he is professional in this field.
by Scott C•
Apr 05, 2016
This course is a good, brief introduction to the foundational concepts of data science and some of the tools you can expect to use when doing data analysis with the R programming language. It's best suited to someone who intends to continue at least with the R Programming course that is also a part of this Data Science Specialization.