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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
30,527 calificaciones
6,505 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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251 - 275 de 6,366 revisiones para The Data Scientist’s Toolbox

por Sreenivasreddy R

28 de may. de 2018

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.

por Lakshmi

17 de oct. de 2016

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.

por ABHISHEK K S

2 de dic. de 2018

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.

por Sumanta K P

22 de ago. de 2017

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.

por Abhijeet M

21 de may. de 2020

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

por Melody K S

20 de ene. de 2018

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.

por Daniel S

30 de ene. de 2017

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!

por Nirav D

2 de abr. de 2016

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.

por Carolina S

8 de oct. de 2020

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.

por SURJEET K S

17 de oct. de 2018

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.

por Ana D

30 de jun. de 2017

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.

por Syed M A T

28 de jun. de 2018

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.

por Pradeep p

10 de nov. de 2016

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.

por Jeff L J D

3 de oct. de 2020

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.

por Abbid A

28 de jun. de 2020

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.

por Dostonbek K

3 de nov. de 2020

So far, although I am studying computer science, I was too far from the nowadays-popular concepts Big Data, data-analysis (what I am very interested in) and This course covered and gave me the motivation to keep on studying the specialization

por RASMI

31 de may. de 2020

I really loved the quality of the content being provided. I appreciate the fact that the courses have been designed for being beginner friendly, but at the same time it ensures that the student gets to know about all the relevant content too.

por Dr. S M A T

12 de jun. de 2020

Excellent Course designed to learn insights relating data science using R software. basic Coding and analytics basics are taught in this course. Moreover learning relating how a data scientist can collaborate on GitHub is an added advantage.

por John

22 de abr. de 2018

This course was a lot of initial set up for the rest of the program. Basically just setting up programs and getting accounts ready for future study. All in all a good start, I expect material and course work will significantly pick up now

por Ajay S C

22 de ago. de 2017

its a nice course to introduce you with the tools required ahead in this journey of data science learning. It helps you in taking that first important step for moving confidently ahead in this great learning. Keep up the good work coursera

por Eugene V

30 de ago. de 2020

Content is not so engaging but I think the new format (text-speech) will help improve the course delivery. Topics are discussed thoroughly and if a certain topic will not be discussed in detail, links to additional materials are provided.

por Michael M

28 de may. de 2020

Exactly what I wanted from an introduction. I feel prepared to begin the more challenging courses in this specialization.

This course isn't so much a value-add on its own, but is designed to set students up for success in a specialization.

por Muhamed N A A

17 de dic. de 2017

Though it was a ground basic skills, but yet solid to build upon. This course helped me a lot getting a clear picture of what is data & data science and the necessary tools required to analyize & generate actionable data.

Thanks Coursera

por Hemanshu S

5 de dic. de 2017

This is really good course and overview about Data science. I had great start for course and Git and basic commands of Linux after several years.

This course will definitely give me exposure to think in best future stream of IT industry

por Lam Y H

23 de ago. de 2017

A great introduction to Data Science and the necessary tools required for the remaining course. Fairly simple, but more catered to a warm up for the remaining courses. Would encourage everyone to continue to complete the specialization.