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返回到 数据科学家的工具箱(中文版)

學生對 约翰霍普金斯大学 提供的 数据科学家的工具箱(中文版) 的評價和反饋

4.5
21,862 個評分
4,385 條評論

課程概述

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....
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Introductory course
(1056 條評論)
Foundational tools
(243 條評論)

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LR

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.

AM

Jul 22, 2017

Great Primer for what Data Science is about. It also provides the infrastructure of tools needed. This was what I was after, a way to provide other data scientist hardware and infrastructure support.

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126 - 数据科学家的工具箱(中文版) 的 150 個評論(共 4,269 個)

創建者 Richard E H

Apr 27, 2018

A good introduction to analytical processes and tools. The course by itself, however, is only a first step. I find many threads begun but not tied together. I anticipate that the remaining nine courses will expand and consolidate everything opened in this course.

創建者 Kevin C B C

Nov 06, 2017

A very eyeopening introduction to the discipline of Data Science. Hope this prepares me for R programming soon. :) I also realized how relevant this is today especially in the sciences, wherein one must have a good grasp in programming as an aid for research.

創建者 Roberto A

Mar 11, 2017

I found this intro course really useful as a warm up and to get into the "data scientist's mindset". The only (minor) point for development is to devote more time to Git and Github, as some of the steps were not particularly straightforward. Well done though!

創建者 Eduardo d S A

Feb 07, 2017

I really loved the course. My peers were amazing. They always help and when they review your project they make sure that you will understand what you did wrong, explaining why and how you might gei it right the next time. Mr. Peng you are amazing. Thank you!

創建者 Sandra N

Aug 22, 2016

This is a fantastic way for individuals to get a leg up if they want a competitive edge in an ever-changing scientific environment. It is important to be able to use certain programs and code to some degree in order to be competitive using today's technology.

創建者 Drew W

Aug 24, 2019

The course was well put together and documented. My only critic is that I would like the lecturer to go over Git and Github more thoroughly as I had to do some extensive outsourcing to be able to figure out how everything worked. Overall, a very good course.

創建者 Saurabh C

Jun 09, 2016

Best in it's Class. Short but so much descriptive with a constant effort to deliver high quality teaching with easy understanding language and concepts!

It's highly recommended to those who are new to Data Science, and want to make their Base strong( like me)

創建者 Rabindra T

Nov 27, 2018

Really nice intro to the set of tools to be used. Step-by-step instructions. It might be useful to have it called out that versions may change, but the basic video instructions will not. There were slight updates that made things look a little different.

創建者 Joe D

Feb 20, 2019

An excellent introduction to r, rstudio, and the basic concepts and functions of github (online version control for personal or collaborative programming projects). Great course, informative videos, lots to do and experiment with, I highly recommend it!

創建者 Rahul G

Jun 24, 2016

Extremely helpful. It was detailed and at the same time brief, made sure I am able to connect with the content and learn in ways that will be useful in career.

Also, the exams and exercises made sure that my concepts are deep rooted into me.

Great Course.

創建者 Ahmed M

Feb 11, 2016

Pretty easy and straight froward, for someone who is already familiar with Programming Editors, and Git shouldn't take 2 hours for him to finish this course including its project, so I guess it's an exciting start for someone who is new for Programming.

創建者 John A R B

Aug 13, 2016

In this course was proposed the outline of the specialisation, showing in a practical and interesting way some of the principal points in the path to be a Data Scientist, I was wondering by the exposition and decide to finish the whole specialisation.

創建者 Jessica M

Nov 05, 2018

This was a very informative course and a good start to the Specialization. The course project I found to be very challenging, only because I am not familiar at all with Git and it took me a long while to figure out the right commands to perform tasks.

創建者 Dev P

Oct 25, 2019

Great introduction into the world of R! I have been completing this alongside the R Programming course and found the two go well together. Interesting to learn about version control and utilising Github, which I am sure will be valuable in the future

創建者 Meihan L

May 16, 2018

4.5/5. For a total beginner of data science, sometimes the lecture is hard to follow so I have to resort to several youtubes videos to complete the project. But the lecture is informative and well-structures, and the forum is very helpful. Thank you!

創建者 Juliana C

Oct 06, 2017

This first course of the specialization is extremely important for people like me who do not know nothing about programming, coding, computer data, etc.

When I completed the course, I was more confident to continue with my idea to start a new career.

創建者 Yash S

Jun 03, 2018

Really intimidating, but very attractive introduction of what lies ahead by portraying a true picture of what you would be involved with as a data scientist in future. Looking forward to the courses ahead in the specialisation. Thanks you so much!!

創建者 Sreenivasreddy R

May 28, 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.

創建者 Lakshmi

Oct 17, 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.

創建者 ABHISHEK K S

Dec 02, 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.

創建者 Sumanta K P

Aug 22, 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.

創建者 Melody K S

Jan 20, 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.

創建者 Habiballah S

Jan 30, 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!

創建者 Nirav D

Apr 02, 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.

創建者 SURJEET K S

Oct 18, 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.