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

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

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

Un-reliable platform. Make screen shots of all completed quizzes

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

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

Only one week. Not much depth.

Boring and useless course.....

NO se puede tomar en español

A little devoid of depth.

Too theoretical.

not worth it

too general

boring

This is a great course if you need a concise background in data science. The more you explore the resources and extra materials the more you will learn. The instructors are well versed in the field and certainly have their hands full constructing software and analysis for what is quite possibly the number one research medical hospital/college in the country, Johns Hopkins. Any certificate or credentials from this institution is indeed most valuable and highly recommended. The material can be a little dense since it is a "crash course", but if you retake your tests and use them as a review of the basic core components of each lesson, you will get what it takes to get a team off the ground working on a real time project with precise goals and applications. Use the variable speed on the videos to slow the lectures down when needed. A great introduction to the varying data sources you will use as a data scientist.

I think the course is apt to begin getting a feel of data science management and needs. I have realised during the course that it is a fairly complex discipline for a beginner with no exposure to statistics and the terminology.

Initially it might seem like over the top, but with some research and reading of suggested materials , one shall be able to get a hang of it in due time.

I also believe the instructors have had to work hard to make sure the upper level course can be delivered as close as possible to the level of a beginner.

My only suggestion is if they could add a list of sorts for statistical jargon , explained in layman terms, which would actually enable quicker absorbance.

A quick, efficient and effective introduction to the notions of Data Science. I liked the fact that it fused traditional analysis techniques with modern tools, infrastructures and approaches without taking sides (ie inferential statistics and hypothesis testing versus machine learning and deep learning algorithms). This helped towards getting an all-around view of the scientific field. Note that some experience with statistics will be required to assimilate information so I'd suggest that (if you have never taken a similar course) you have done some prep-work or you are kind of familiarised with the field.

For an introductory course, this was really fantastic. It's really high-level, but it gives you a framework to understand the world you are entering into (or considering entering into). This is the first course in the Executive Data Science specialization which is built around topics like hiring a team of data scientists, and managing data science projects. So, this would be a great first class for that. But, it's also a great start for someone moving on to getting elbows deep in R Studio, Python, Hadoop, etc. I think. This is a really friendly introduction to the world of data science.

Really should be retitled to "An Executive Overview of Data Science." The course covered all the critical Data Science components that Executives or Senior Management should be aware of. Corporate america still does not understand, nor recognize the critical components of properly funding, supporting and committing to a Data Science effort or program. This course outlines the needed core components for a successful Data Science journey that could impact the top and bottom line.

great for existence human and android based life-form simulation internal lifestyle...

The course improves life within the simulation 10 fold at least(when combined with the other specialization courses) ...

Perfect learning tool for those who have worked professionally in research field sin our simulation and yet now have a touch of "the turrings" or you know : CBI...

Special thanks to the designers of the course.

Top scores for coursera.org &John Hopkins ...

This was a great course for me, a data analytics professional with an MPH earned 25 years ago based on more traditional statistical methods and tools. I took this course to learn more about the expanded concepts of data analysis that the data science field offers, as well as understand the tools and framework this broader field encompasses. Really enjoyed the format and pacing. Looking forward to taking more in the Executive track.

The course was very enlightening. Very well structured and examples very straight-forward and easy to understand. The only thing I would suggest, and I suspect this is more of a Coursera thing rather than from the course itself, is that when you are following along with the transcript in a lecture, the video window becomes unworkably small. If there was a better split between text and window, that would help immensely.

A Crash Course in Data Science by Brian Caffo, Jeff Leek, Roger Peng with Johns Hopkins University is amazing. I found this essential in understanding the role in successful organization along with building the structure, data science toolkit, defining success as we separate hype from value. I look forward to learning and exploring further with "Executive Data Science Specialization". Special thanks to Coursera.

My name is Jose Antonio from Brazil. I am looking for a new Data Scientist career.

Please, take a look at my LinkedIn profile: https://www.linkedin.com/in/joseantonio11

I did this course to get new knowledge about Big Data and better understand the technology and your practical applications.

The course was excellent and the classes well taught by teachers.

Congratulations to Coursera team and Instructors.

Regards

Great, clear overview of the standards, principles, terms, and applications for data science - geared toward executives, managers, and professionals working with or directing colleagues and team members specializing in data science. A great snapshot for organizational leaders seeking to get a better grasp on how to make critical decisions about data science investments, resource allocations, applications, etc.