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!
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.
автор: Swarnava G•
Aug 23, 2017
автор: Yakshdeep D•
Apr 15, 2020
автор: AHMET E•
Nov 28, 2017
Mar 02, 2017
автор: Jatin P•
Oct 19, 2015
автор: 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.
автор: 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.
автор: 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.
автор: 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.
автор: 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.
автор: 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.
автор: 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.
автор: 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.
автор: 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.
автор: 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.
автор: Edward W•
Sep 27, 2015
A good introductory overview of data science. Grounds you on what you can & cannot do with data science. I find defining the question really impactful. Teachers were enthusiastic and the brevity of the course gives it good appeal for beginners who want to "get their feet wet".
автор: Elizabeth R•
Jan 27, 2016
Good, simple, straightforward, and applied. It starts to introduce you to the language and platforms of data science, but it is most definitely not a standalone course if you want to be conversant in the field. Really just a "taster" to get you into the specialization.
автор: Cecilia B•
Nov 08, 2017
More lectures but each lecture should be shorter. More examples for each topic would be good.
However it is a crash course, so it is more of an overall description of Data Science, which also gives you suggestions to enhance your knowledge in other courses
автор: Achal J•
May 12, 2020
This course is pretty basic so don't expect much. Basically this course is more reading than understanding but the articles suggested are good. If you are serious regarding data science then this course may be of not much use to you.
автор: Saurabh G•
Aug 12, 2019
Not all lectures in the course are well done. The one on the data scientist toolbox is good and could have more details. The one separating data science from statistics is too confusing. May need to redo the video on that one.
автор: Evgeny K•
Sep 25, 2016
This course leaves you frustrated, as valuable information is only ad the end and at the beginning. It doesn't really answer questions of what are data science, big data, machine learning, how they interact and how to use them.
автор: Magne G•
Sep 19, 2019
Okay content, very mix of level of information. Could state better the terms used in the DS world. The quiz part is not well formed questions, more there to mislead than actuelly verify the knowledge
автор: Daniel W•
Apr 15, 2018
I am trying to work out whether or not to get into data science, I thought this would help but still undecided.
I liked the grounding of principles, tools and methods required for the discipline.
автор: Francisco P S•
Mar 29, 2017
The course can use more visuals instead of videos of the face of the instructor. It can also use more interactive examples as this is a more executive view instead of having scholar examples.