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Отзывы учащихся о курсе A Crash Course in Data Science от партнера Университет Джонса Хопкинса

4.5
Оценки: 5,216
Рецензии: 983

О курсе

By now you have definitely heard about data science and big data. In this one-week class, we will provide a crash course in what these terms mean and how they play a role in successful organizations. This class is for anyone who wants to learn what all the data science action is about, including those who will eventually need to manage data scientists. The goal is to get you up to speed as quickly as possible on data science without all the fluff. We've designed this course to be as convenient as possible without sacrificing any of the essentials. This is a focused course designed to rapidly get you up to speed on the field of data science. Our goal was to make this as convenient as possible for you without sacrificing any essential content. We've left the technical information aside so that you can focus on managing your team and moving it forward. After completing this course you will know. 1. How to describe the role data science plays in various contexts 2. How statistics, machine learning, and software engineering play a role in data science 3. How to describe the structure of a data science project 4. Know the key terms and tools used by data scientists 5. How to identify a successful and an unsuccessful data science project 3. The role of a data science manager Course cover image by r2hox. Creative Commons BY-SA: https://flic.kr/p/gdMuhT...
Основные моменты
Well taught
(рецензий: 48)
Basic course
(рецензий: 76)

Лучшие рецензии

SJ

Sep 10, 2017

This is a great starter course for data science. My learning assessment is usually how well I can teach it to someone else. I know I have a better understanding now, than I did when I started.

JM

Jan 02, 2018

It is a very good course even if you are familiar with some aspects of data science work. If I have to make a suggestion, I would remark the importance of design skills during a data product,

Фильтр по:

926–950 из 952 отзывов о курсе A Crash Course in Data Science

автор: iair l

Dec 26, 2015

too basic, the 4 courses of this specialization could be just one course.

автор: Eduardo R L

Oct 07, 2016

1-week does not seem enough for a Crash Course

автор: Marcelo H G

Jul 12, 2017

Too much Superficial. Too fewer quizes. More external videos about hadoop, python, spark, data lakes. More paradigms broken. Need to explain what is On premise, rent and cloud.

автор: Arno B

May 04, 2017

very elementary. Takes approximately 2 hours to complete.

cannot continue with the in-dept material but have to wait until next week (and payment ofcourse).

автор: Nellai S

Jul 02, 2017

At some places, one lesson had the text and the next lesson was redundant with part of the information on video. you could club them in one an

автор: Hussain, C

Oct 21, 2015

Very general course. Doesn't give much insight into data science.

автор: Deepak G

Jun 28, 2016

Very short. Quality of the course is also not that good.

автор: Robin S

Jun 13, 2019

The only reason this course is two stars is because the content could be useful to a beginner in the field. The course itself, however, is of poor quality with un-engaging video content and an unedited book with multiple sections that are clearly derived verbatim from the sub-par video lectures. It could be drastically improved with a little effort and would hopefully provide more value to learners with genuine interest.

автор: Mohsin Q

Oct 31, 2016

They could have stated the audience of the course more clearly. I found most of the information irrelevant that added little value. Most of the things discussed are generic and would apply to any project.

автор: rahul s

Mar 19, 2019

not worth it

автор: Miroslav K

Sep 09, 2016

too general

автор: Alessandro V

Apr 22, 2016

It's too short, I think it should be a part of a course and not a course itself.

It is a repetition of concepts and examples from other courses by john hopkins univ.

автор: Seyyed M A D

Apr 19, 2018

Thanks

автор: Anus H

Oct 15, 2015

boring

автор: Hugh J

Jul 11, 2016

A little devoid of depth.

автор: Carol P

Feb 09, 2016

Too short to get any depth of information. Too expensive for the content provided.

автор: Caio R d S

May 05, 2017

Quiz should be open to all students... :/

автор: Tamer D

Sep 05, 2017

It would be great if slides were prepared and used through out the videos....

I was looking for something a little but more technical...

автор: Michael W

Sep 16, 2015

Only one week. Not much depth.

автор: Thomas W

Dec 28, 2017

All the course content is too basic to bother with. It’s just a bunch of common sense and a few definitions of vocabulary words that can already be found on Wikipedia. There is typically one page of reading stating basic definitions and intuitive ideas followed by a 10-15 minute video reiterating those basic ideas. For example, there is an entire unit just to explain that a report on a data science experiment should be clearly written, avoid unnecessary detail, and have concise conclusions. There is a page of reading to list these as bullet points and a 14 minute video to repeat these points.

This course is a waste of time. Thankfully, it’s short and free.

автор: Poon F

Jan 26, 2018

No much information presented. Disappointed that this comes from John Hopkins.

автор: Ismail H D

Apr 11, 2016

This course is very sparse on details, and just a week of content. The lecturer is not the best at explaining concepts.

автор: Cheng-Jiun M

Oct 12, 2015

it's a shame to split a one month course to four.

автор: Guy B

Feb 12, 2016

Very basic, for absolute beginners/ managers completely new to data (let alone data science)

автор: Vishal S

Nov 27, 2019

A LITTLE TOO THEORETICAL. THE INSTRUCTORS SEEM CHALLENGED TO PRESENT REAL LIFE EXAMPLES. Quoting favorite examples from historical pure play ideas (e.g. predicting heights of boys) are frankly a bit dated, not relevant for a business audience, and hint at real life incompetence of instructors. And what is with trying to promote books these guys have written?