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Вернуться к A Crash Course in Data Science

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

4.5
звезд
Оценки: 7,170
Рецензии: 1,367

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
Basic course
(рецензий: 76)
Well taught
(рецензий: 48)

Лучшие рецензии

SJ
9 сент. 2017 г.

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.

MD
27 авг. 2016 г.

Is really hard to summarize the potential of Data Science and being clear, but I think that the instructors have done their best, so that we can achieve the most from the Course.\n\nGreat Job!

Фильтр по:

826–850 из 1,334 отзывов о курсе A Crash Course in Data Science

автор: Rebecca T

22 авг. 2018 г.

Very quick and easy to complete. Doesn't go quite as in-depth as I was hoping, but it does say "crash course" right in the title so you can only expect so much. I will be taking more courses on this subject. Overall, even though the information wasn't very detailed, what I learned was very useful, and my research work at my job will improve as a result of taking this course.

автор: Kyle H

24 мая 2020 г.

Good fundamentals and big picture approach, the discussion of specific software tools would be useful to some but not of real interest to me. I do mechanical design and consume data that is developed analyzed and presented by others and this class allows me a deeper appreciation of the challenges of analyzing and presenting data from experiments on the hardware I design.

автор: Rokas N

20 февр. 2016 г.

The course touches upon most important topics in Data Science but doesn't go deep into the topics:

- Covers most important important topics in Data Science on high level.

- Course works as a "refresher" to follow the course you should know the basics in statistics and modelling. Concepts like parsimonious model would be used with expectation that student already knows it.

автор: Tatsiana A

25 апр. 2018 г.

Easy, relaxing overview of data science project management. As this is the first class of Executive data science specialization, I give it 4 stars because I believe (or should I say "hope") that someone who is planning to be executive data science manager should know what is statistics or machine learning, or what is the aim of exploratory data analysis.

автор: Nimrod K

19 июня 2016 г.

Quite basic material... If you have some technical background you might fund this course not so useful.

However, I think that it does provide the right information for non-technical managers in a simple and comprehensive way.

Personally, I wish it was a bit longer and deeper to feel like I acquired more knowledge to take it to the next level independently.

автор: Eric F

22 окт. 2019 г.

Pretty thorough for an overview, and it touched upon most concepts that you'd need to approach Data Science in any meaningful capacity.

My only gripe is with the literal last quiz, wherein no questions were asked based upon the materials, but upon additional PDFs attached to the quiz itself.

You cannot link me 4 PDFs and then claim it's a 4 minute quiz.

автор: Reinaldo B N

19 мар. 2016 г.

I have studied this course as part of the Executive Data Science Specialization. I think this set of four courses meet my objectives by providing a very nice overview on the key points of data science projects. They are good to give a flavor on data science and data science projects helping decide if you want to search for more in depth knowledge.

автор: Kelly F

10 апр. 2017 г.

Great course. Lot of complicated detail segmented and described in a way that was easy to digest. Thoughts for improvement are with the first few segments. The lessons didn't start with the "why". Why machine learning is used or what problem it solved. I had to google that in order to understand before the course which started with "what" it was.

автор: Dominique W

27 июля 2020 г.

I liked the course, but the quizzes were annoying because there are few questions and they include multiple choice question, but because there are few questions and you need to get 80% correct, you aren't allowed to get one question missed. It would be nicer to have more questions so the 80% correct would allow you to miss one question at least.

автор: Marcos A K

29 мая 2017 г.

The course is correct. I would like to go a little deeper in each and every aspect of the course. For example, they explain clearly the difference between statistical analysis and machine learning, although, a more detailed examples of when you only can use statistical analysis and when you only can use machine learning is missed.

автор: Árvai M

20 сент. 2015 г.

I really enjoyed this course, it gives me lot of new, interesting knowledge about data science, But there are some mistake about good (clean) programming. Please do not use comments, the comments show strange code, do not write big function etc... Clean code book from Uncle Bob helps me a lot of to write clean, maintainable code.

автор: Lorenz F

10 янв. 2018 г.

good, high level introduction what data science is all about. The section on the structure of a data science project could have gone more into details, maybe following the steps on a specific example. I also missed some insight into the step from the question to the search algorithm. Maybe that's part of the further courses.

автор: Alejandro R

26 февр. 2019 г.

I learned a lot, the instructors know how to facilitate knowledge but it's not so friendly to people who don't know much about programming, statistics, etc., and there are some grammatical mistakes in the translation to English and some formatting mistakes in some tests. But overall, I'm satisfied with the course.

автор: Thorsteinn A

1 окт. 2015 г.

Quick scope of data science. I particularly liked the discussion about fad versus fact towards the end of the course. Some questions in quizzes seemed a bit arbitrary. The course delivers what it promises; crash-course with the key ingredients for understanding more about what data science is about

автор: Kaustav S

25 мая 2017 г.

A pretty helpful course if one wants to get an idea about what Data Science is. But I was expecting a bit more hands on example in the end. Maybe not a graded part of the course, but still something to give the student a practical idea of how things look like when they are actually doing stuff.

автор: Shalini P

8 авг. 2018 г.

Some of the content and coverage was excellent and others mediocre. There isn't a consistency in the availability of slides that can be downloaded (available for some, not others). Also, when a quiz answer was marked wrong, I would have liked to know what the right answer is for the question.

автор: Srinivasa L

28 нояб. 2017 г.

A good course to start on your journey to understand DS and Machine Learning

I am familar with most of terminology through my experience. My learning is limited because of that but some one new to the filed would definitely learn more. I have taken this as part of Executive Data Science Program

автор: Heidi

17 мая 2017 г.

A good primer for aspiring or casual data scientists. I wish it were more technical so I could adopt some assignment solutions for my work, but for one week course the syllabus covered is perfect.

Wish I could save my progress for free to show only to myself that I've completed this course.

автор: Shardul N

5 мая 2020 г.

This course is an excellent starter course.

Just one thing, a few simpler examples for certain concepts may be better for understanding them, as some people (like me) who are not well versed with scientific terms and concepts find it a bit challenging and difficult to understand them.

автор: Rong-Rong C

1 дек. 2017 г.

Crash course is the correct description; vast amount of material covered in a few segments. As a result, this course is fast-paced and does not go too deeply into any particular aspect of statistics. It is nice to have a little knowledge of the subject matter but it is not required.

автор: Sergey G

21 июня 2020 г.

This course could be really usefull even for experienced Data Scientist to correctly organize a workflow in his\her DS team. The described technologies and some examples a little bit outdated in 2020, but most of the information is quite general and relevant for any period of time,

автор: Peter E

7 нояб. 2016 г.

I am a PhD biologist leading a team of data analysts. I found this course to be quick and easy to follow, well presented, and extremely helpful. The instructors are truly professional and they excel in this medium, I was very impressed. Thanks Coursera and Johns Hopkins!

автор: Marc-Eric L

22 дек. 2019 г.

It was very good. I am not a DS but have been exposed to their work. I would like to debate whether Hadoop is the best place to do the work today, but the point made still stands. The one thing that made me put a 4* instead of 5: I don't see how it is "executive" yet.

автор: Lucas B P

15 дек. 2015 г.

I left with a good understanding of the reach and dynamics of the field of data science. Even with experience in using data to answer questions in the context of an organization this has been a good way of mapping out the areas where that experience can be extended.

автор: Seraphim A

11 дек. 2015 г.

A very good intro to Data Science by three experts. Well-paced, with reasonable quiz questions and can be completed in less than a week. However, I would certainly not pay for it, because it is feels more like a well-designed ad for the spesialization that follows!