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Opiniones y comentarios de aprendices correspondientes a La caja de herramientas del científico de datos por parte de Universidad Johns Hopkins

4.6
estrellas
32,498 calificaciones
6,934 reseña

Acerca del Curso

In this course you will get an introduction to the main tools and ideas in the data scientist's toolbox. The course gives an overview of the data, questions, and tools that data analysts and data scientists work with. There are two components to this course. The first is a conceptual introduction to the ideas behind turning data into actionable knowledge. The second is a practical introduction to the tools that will be used in the program like version control, markdown, git, GitHub, R, and RStudio....
Aspectos destacados
Foundational tools
(243 reseñas)
Introductory course
(1056 reseñas)

Principales reseñas

LR
7 de sep. de 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.

SF
14 de abr. de 2020

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.

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151 - 175 de 6,822 revisiones para La caja de herramientas del científico de datos

por Randal N

2 de ene. de 2018

Great introduction to data science and the associated tools. As someone new to data science this course provided a simple, yet firm and comprehensive foundation for the rest of the courses in the data science specialization. Definitely worth doing this course if you are thinking of pursuing any endeavors in the field of data science.

por Jonas H C W

21 de ago. de 2020

I thought this was a very fun experience. It was easy to follow along and it didn't take up too much of my time to pick up some interesting concepts. Though I do recommend that you watch some videos on YouTube with explanations on Git and GitHub, because that will really help make version control systems so much more understandable!

por Yanal K

7 de ene. de 2016

First experience got me hooked. I love coursera. This course, even though an introduction taught me a lot and showed me an error of my ways in everyday life. One question in the 3rd Quiz was very confusing to answer. But that's about it. I hope the rest of the specialization carries on forward in a similar maybe even better pattern.

por Sandhya M

29 de dic. de 2019

The course was completely new to me. But the step by step instructiona made it easy for me to complete the course succefully. Linking of R and GitHub is like a magic to me ,who is new to programming. The Video on Control Version is fantastic and can be helpful for even professors like me who give group projects to their students.

por Shelly L

19 de nov. de 2017

I think this course did gave me a full impression regarding data science and guided me how to install basic tools successfully. Also, I found that the help guide and links those are introduced during lecture are very helpful, such as "Github help" and discussion forum. I used them a lot when finishing the last peer view project.

por Daryl B

31 de jul. de 2020

This was an excellent course. I always wanted to know how to use GitHub and this course knocked it out of the park for that. Also learned how to set up R & Rstudio on Debian 10 vs. Windows and/or Mac. I'm a FOSS guy so this course provided sufficient guidance around how to build my Data Scientist toolbox on that platform. Nice!

por Egor M

23 de jul. de 2020

A short introduction to the primary tools and concepts for data analysis with R. The lectures cover a fair range of topics from installing the software to experiment design and types of data analysis. Relevant and informative examples are provided for each section. All in all, the course is a wonderful introductory experience.

por SZE P L

6 de jun. de 2021

This is a great course to startup a Data Scientist journey. Learn how to setup the tools to be ready for R programming and the concept of data analysis. A minor negative comment is that the robot voice is really annoying sometimes, but it is well explained in the Welcome notes and videos. OVERALL, good course to be enrolled.

por Lucho B

31 de oct. de 2020

It was interesting, including the presentation itself in the sense of the automation of the generation of the course. I will probably copy that idea for my future courses, otherwise the content without major problems. It catches my attention that they do not explain or at least indicate how to install these tools with Linux.

por Selwyn L

1 de may. de 2018

I liked this course. The material that you learn was pretty basic, but the community helped you digest the more indepth concepts (I am new to RStudio and GitHub). What some people will find as a flaw, I liked the fact that I had to go and look for the answers online and it wasn't just given to me in the course notes/slides.

por Mainza H

29 de oct. de 2017

This course has really helped me understand how to value peoples work and share what i think and share my work with others. The lectures are very good and helpful. From the knowledge i have arquired i view things differently, more like a data scientist and i am motivated to complete my specialisation as a data scientist.

por Nanette H

15 de feb. de 2016

Great course! Explains the details of what is in the content of the rest of the certificate while not being too detailed. Showed which classes will be related to the content of each part of the introduction. Did a great job of setting up all required tools for the the R programming course (which I am currently taking).

por Haripriya R

3 de jul. de 2020

I loved the course - the different kinds of formats of presenting the information really helped me in choosing the medium in which I wanted to learn! Thank you to all instructors and the links to all the material provided. I loved Hilary's name analysis and Nate Silver's take on US elections - thanks so much once again!

por Ayush R

2 de abr. de 2020

before completing the course I thought that I know all of its content, but as I proceed further I realized I was wrong and got to learn many thing, the most fruitful thing that I learned here was integrating Git and R Studio, the final assessment practically brushes up all the learning taught. overall am very satisfied.

por Kiel A

20 de mar. de 2016

Really solid introduction to the subject matter. This course gave me a better understanding of how to go about finding the questions which need to be answered, which is fundemental to the study of data science. Also, it gave me a wonderful tutorial on where to find help and how to ask for help which I found very useful.

por Raksha S

24 de mar. de 2020

This course is just amazing! I had the best experience learning it at my own pace, and the interactive learning session was an added fun to the whole course! I am looking forward to learning so much more! The slides had very illustrious graphs and teaching was in such simple words that I could grasp everything so well!

por Shannay R

3 de mar. de 2020

An excellent introduction to R, RStudio, Git and GitHub. The course content is well designed and touches upon various topics in a crisp tone. The course lowers inhibitions and allows learners without any coding experience to test the waters.

Definitely recommended for all enthusiasts looking to venture in Data Science

por Jose P M L

9 de jul. de 2020

Very nice introduction to the subject. If you know RStudio and Git you can easily go throught it in a couple of days. You might really wanna go deep into R Studio features like markdown syntax and take a good look at Hilary Parker's work to see how a data scientist think and go through her process. Her blog is amazing

por 20e

12 de oct. de 2017

I got a general idea about the work of a datascientist which laid a stepping stone for my further study.

Further more, I think the lesson of "getting help" is quite helpful and practical for me and I enjoyed the whole class.

I would recommend any one who is interested in datascience to take this course at the beginning.

por Ващенков В В

21 de feb. de 2019

Info is compressed but it is still available for understanding and useful. But I think new students can have some difficulties with git or github, because theres some not so obvious commands like swap branch, commit changes etc...But it is also good for students to learn use Google and look forward for tutorials :)

por Francy G B

12 de jun. de 2020

Este curso me permitió explorar algunas de las múltiples herramientas que tiene R y conocer su utilidad en la utilización y/o procesamiento de datos. Además el interés por seguir aprendiendo más sobre el manejo de R, puesto que es una excelente opción, para apoyar el análisis de datos en procesos de investigación.

por Marko N

1 de dic. de 2015

The new graphic is really nice and helpful. Even the fact that you can retake the quizzes after 8 hours is really nice. I have noticed that there wasn't any possibility to download pdf files of the lessons (or I didn't see it), the last time I took the course there was this possibility and I found it so helpful.

por Tejaswini P

30 de may. de 2020

I found this course very interesting. The progression of course from week 1 to week 4 was very well paced. The study material provided in form of notes, powerpoint presentations and videos was adequate for understanding the topics. I would definitely recommend this course for people interested in Data Science.

por Jekabs B

12 de mar. de 2020

Well designed course; great for first in sequence. On a couple of parts I had to struggle to figure out how to complete an installation or proper launch of a program, but between the instructor's instruction, classmate's comments, and google searching, all was completed. Thank you for designing a great course!

por Ravi K M

27 de may. de 2018

This course serves as a introduction for all the remaining 9 courses to come. You will be learning GitHub, R studio and a bit of command line to be familiar with the tools needed for Data Science. I highly recommend this course for anyone interested in Data Science. The professors teach the concepts very well.