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A Crash Course in Data Science(으)로 돌아가기

존스홉킨스대학교의 A Crash Course in Data Science 학습자 리뷰 및 피드백

4.5
별점
6,923개의 평가
1,312개의 리뷰

강좌 소개

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...
하이라이트
Basic course
(76개의 검토)
Well taught
(48개의 검토)

최상위 리뷰

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.

MD

Aug 28, 2016

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!

필터링 기준:

A Crash Course in Data Science의 1,279개 리뷰 중 1126~1150

교육 기관: Naveen R M K

Nov 11, 2015

Good One.

교육 기관: Efraime C

Sep 29, 2018

I

n

t

e

r

e

s

교육 기관: David C

May 06, 2020

Great!

교육 기관: 陈逸凡

Oct 27, 2017

内容深度不足

교육 기관: Mark G

Sep 27, 2016

Great\

교육 기관: Aniket M

Jun 20, 2020

Great

교육 기관: Pappu T

May 24, 2020

Great

교육 기관: Himadri N B

Aug 02, 2020

Well

교육 기관: Rohan J

Jun 26, 2020

cool

교육 기관: Swarnava G

Aug 23, 2017

Nice

교육 기관: Yakshdeep D

Apr 15, 2020

V

교육 기관: AHMET E

Nov 28, 2017

t

교육 기관: Naren

Mar 02, 2017

v

교육 기관: Jatin P

Oct 19, 2015

G

교육 기관: ram s

Mar 20, 2016

I want to give 3.5 stars but there is only option for 3 or 4.

Given that it's geared more towards wanna be managers in this field. I would have expected lot of case studies, and links to additional material for individual reading plus a mini write up or a project at the end.

For MOOCs to compete with a degree program or an onsite instruction few of the things I think that are needed are

Interviews with industry practitioners which is a big plus.

interviews/postings from people with similar background as the 90% of the MOOC students of this program who made it... this motivates the students from dropping from the middle of the course/specilization programs

links to additional articles that the students can read at leisure

writeup/project as assignments that the students can pursue and publish (not necessarily for grade but as a mind jogger)

One more thing that I think should help (not specific to this course) is that the student with the best grade should be offered one free course and think this will motivate the students to complete the courses.

교육 기관: Nate A

Jan 06, 2016

I wanted to like this course but It felt entirely too academic in terms of both the subject matter and the way the specifics of "data science" are presented. The course content reminded me of my time a few years ago when I was enrolled in a Ph.D. program at a major Tier 1 research university. The professors were great, but the content was esoteric and incredibly focused on research based "data science" and less on business analytics or more practical applications of data science for the working professional. I felt myself re-watching the videos to try and understand the content because there were many instances where the professors' spoke about some fundamental aspect of data science but failed to provide some real world context. I liked the course but I would not recommend it as a crash course for the working professional, more like a crash course for someone who already has a degree in statistics/math/engineering who is looking to further their studies in an academic setting where research is the main goal.

교육 기관: Margaret K H B

Mar 31, 2018

I felt the explanation were in between data science for beginners and someone who already had taken a statistics course. I feel that it was important at the beginning to give more real life examples of the usage of data that were compelling. And then take those real life examples and break it down for us using a single inspired project. That would have helped me better understand some of the principles that seemed a bit abstract for me.

교육 기관: Prasun B

Aug 19, 2020

I liked mostly Mr. Jeff Leek and Mr. Roger D. Peng's clear and well-composed presentations. But I am disappointed with the certificate format because there is a big note at the bottom which was printed not once but twice and therefore some part of went out of border. After all the hard-works to get such a certificate doesn't feel good at all. Same experience with the "Psychological First Aid" course certificate.

교육 기관: Puranjay M

Jul 23, 2017

I think the course structure could be improved to give a better balance between the reading materials and spoken content. Though I understand it is a crash course better correlation between real life examples could help augment the course. For the amount of time spent the course does give a quick overview, but if you are looking for more business specific knowledge you will have to take additional courses.

교육 기관: Siddharth M

Feb 26, 2017

The first week gave me a good insight into the data science process. I now understand the situations in which Data Science can best be applied. However, I still do not fully understand the statistics aspect. It would help me if the instructors would provide examples in detail of supervised vs unsupervised learning. I seem to understand the theory behind it but I am not sure how valuable it will be for me.

교육 기관: Shyam S

Feb 11, 2019

I personally found it difficult to understand some of the language used, which I think could be simplified better. I personally learn better, when I'm not being overloaded with loads of facts & info, however I did like that we could do some reading at our own pace, then get shown a video. I like the videos, and the quizzes.

교육 기관: Santiago J S

Sep 27, 2017

Good starting point, maybe too short. Hope next courses on the specialization become more extense in content. I've always have issues to follow Peng's line of thinking, it's like kinda in some way he is doing some sort of improvisation or so, I love his books, but his lectures are very hard to follow, even the short ones.

교육 기관: Pavan M

Nov 09, 2018

This course is very basic and completely theoretical. The grading of questions is not proper. The passing mark is 80% but there are only 4 questions. Answering 3 questions correctly gives you 75% and answering 4 questions gives you 100%, then where is the passing mark question.

But the content is good.

교육 기관: Aydin A

Jun 03, 2016

Was expecting more of the how to's and a bit of programming or at least concepts of the programming/statistics, but I guess there are different interpretations of the idea of a crash course.

Definitely geared for people who work with data scientists but not in the data science field.

교육 기관: Sarge S

Feb 11, 2017

Brian Caffo's lectures were rambling and confusing, with excessive use of jargon without proper explanation. His graphs were overwhelming with information, and little effort was made to explain the graph. Otherwise, the other lectures were very good, concise, and clear. Thank you.