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Opiniones y comentarios de aprendices correspondientes a The Data Scientist’s Toolbox por parte de Universidad Johns Hopkins

4.6
estrellas
31,369 calificaciones
6,670 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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6301 - 6325 de 6,527 revisiones para The Data Scientist’s Toolbox

por Shannon P

16 de mar. de 2020

This was a very basic introduction to the concepts of Data Science and the software necessary for future courses. Overall it was fine, but I hated the robotic voiced over videos and ended up playing them on mute to get through them. Also, considering the explanation that doing the class content and videos this way allows the university to keep the courses up to date and correct errors faster, there was still several out of date sections of the course and a number of errors, so I really felt the automated setup as an annoyance not a benefit.

por Amy-Louise S

24 de sep. de 2018

The lectures were very uninspiring for the most part and I felt that my practical understanding was poor. The forums were also not particularly helpful as I saw Moderators mocking students for asking valid questions based on their inexperience with Data Science. I spent most of my time finding better tutorials on YouTube, so really.... I have a certificate but don't owe much of that to the course in question. It only becomes worse as the complexity increases with the rest of the Courses in this Specialization.

por Sem O

11 de may. de 2016

The course is well structured and provides a good introduction, however, I expected a bit more from a course that costs 20 pounds than just a few clips on how to install and set-up software/create a github account etc. This information is available for free online on the websites of the respective software.

I understand that such an introduction is needed for the course, but then do not offer it as a separate 20 pound module. Instead include it for free with any other 'specialization' you can buy.

por Pradeep M V

30 de jun. de 2020

It shouldn't have been a stand alone course. Just a series of "how-to" instructions on installing RStudio, linking it with and using Github, which one can find easily with more detailed examples on the internet. This one can be combined with the next course (R Programming) in the specialization.

That monotonous bot voice is a serious drawback. Having an instructor is very important for a course especially when you are charging for the course.

por Tarik G

28 de abr. de 2018

I can see that the lecturer's intention was giving an overview by mentioning all different topics, however, it just got me confused. I wish it was more into a solo topic. It would be great if it was given only git/github lectures, so we, the students, can be more comfortable when it comes to uploading files in the following courses. I see in the discussion forums that github is a problem for most of the students in the forums.

por Sydney R

5 de feb. de 2016

You will learn some command line commands, git, Github, and what you will need for eventually using R.

I was a bit annoyed that this course is a requirement for the Data Science certification (which is what I am after). I already knew everything taught in this course and was a bit annoyed I had to pay for this in order to complete the track. I think 'courses' that are fully setup like this should be opt-in not required.

por Ignacio S U

23 de may. de 2017

The course is extremely introductory and even though it may lead you to references you may use to self-teach yourself, it is not worth taking a four weeks course for a one week content. At the end of the week you will have about three new programs installed in your computer and no idea on how to use them for practical situations. Although it's intended as introductory, it surpasses that barrier to mere spectacle.

por Daniel P

9 de sep. de 2019

In my opinion, the content of this course is too basic and little bit of topic for the data scientist specialization. Of course it is useful to be able to use git, shell etc. but I believe that most of the people already know those and the rest of the students can be redirected to relevant study material. All in all, there was about 90 minutes of relevant study in this course.

por Ben V

13 de sep. de 2016

Very very introductory. I didn't find the tooling aspects of this course particularly helpful, but I'm not in the target audience. It's length was misleading -- I completed the work in two days easily, but I am a technologist, and already had the tools installed. If you use GitHub and RStudio, the meat of the course is only about an hour of the lecture.

por Daniel J R

19 de jun. de 2018

Not very engaging videos. Superficial introduction to the mechanics of some tools without providing much context. Final submission did not work per video explanation. Need a more engaging presenter. Not quite at the level of Prof. Ng's Machine Learning course which I realy enjoyed and learned a lot from.

por Heather G

20 de mar. de 2016

This should not be its own course, as it would be pretty useless if you were doing it on its own without doing any of the other courses. The end of course project literally being just to make a Github account and download R-studio could be quickly covered in the first week of the other courses.

por Raj K P

14 de nov. de 2017

showing - doing things live in the video would have been great .. it seemed like explaining a PPT by an instructor. You could have taken one data set and have done all shorts of things and then in the midst thrown some quizzes to student instead of going though all the discussion in one go

por Lyn S

10 de ago. de 2017

Not bad, but certainly not good. I cannot believe there is a style of teaching where you never get to see the best way to do something. I can slog thru the programming, but I doubt it's the best way to do something, but I never get to see how something should have been done.

por Eric J S

6 de ago. de 2019

Very basic course. Poorly motivated, material presented without an effort to demonstrate why. This is not entirely out of place in this intro course, but it permeates the entire program. Difficulty poorly controlled, projects and quizzes much more advanced than lectures.

por George C

13 de ene. de 2018

I personally think that this course should be better interwoven into the other modules of the data science specialization. It's a quick primer, but aside from that, not very valuable in terms of the information that it's providing. I wouldn't pay $49 to take this course.

por Thiên P T N

30 de ene. de 2016

It is generally good course, but I feel it is just a combination of very little tools, skills and ideas. I believe it is quite complicate for me to understand, esspecial git and github. I think it is better to combine this course in other courses where you need it.

por valentine

27 de ago. de 2016

Would like to have seen more material using git and git bash commands. More repetition here would be helpful. Seems like a lot of this information will be lost or forgotten when it comes time to use it, especially as it relates to the Data Science Specialization.

por Roy H

17 de ene. de 2016

Dry videos. Most classes are someone showing how they do something their way, rather than guiding or teaching with the intent to have the student absorb and re-apply principles.

Very difficult for a student to absorb material from this video series

por Derek P

6 de ene. de 2016

Hard to follow with a lot of technical intructions right off the bat with inadequate explanation, a lot of "read more about this at <insert URL>." Videos were boring and the instructor was invisible just reading off the slides. Not very engaging.

por Alexandre B S

11 de feb. de 2020

This course should not be the first module of the specialization. Also, it lacks exercises and the content's explanation is not that deep and interactive, making the first course of the specialization boring and not caught student attention.

por Amouna

27 de mar. de 2020

I definitely did not like the robot voice even though the course mentioned that it could be annoying. I wish there was more instruction involved, especially for beginners like myself. It was still confusing to complete some of the tasks.

por Michael S

4 de oct. de 2020

Very disappointed in the quality of the videos. The voice-over is computer generated and takes too much focus. Luckily you can choose just to read it yourself. But this is not what I was expecting from Johns Hopkins and Coursera.

por Daryl A

17 de ago. de 2020

The course needs to spend more time on how to init and push an item from RStudio to Git. I ended up having to watch a youtube video on how to do it. And all the comments show that this course did not prepare students how to do it.

por Mehmet M A

19 de sep. de 2020

The robot voice is a bother. If it is something experimental, the course should be free: students are human beings, not guinea pigs. There are better books and tutorials for installing and exploring the software.

por Tarunoday S

6 de may. de 2017

This module should not be kept as a separate piece...The steps mentioned in the lectures does not properly cover what is asked in the assignments.The lecture content needs to improve to cover the assignment