Very basic course, to be honest. The grading seemed to be dependent on memorizing exact quotes from videos. Looking forward to some of the more advanced courses in this series.

Videos often have disjointed or unrelated elements. Final week quizzes and mid-video questions often have useless or otherwise unhelpful reading questions. An example from week three's final quiz, "True or False: The Untied States Economic Forecast is a publication by McKinsey University Press." The answer is false and is covered in the reading, but the question has absolutely nothing to do with data science.

Too much introduction. There is no need to spend so much time on it. People that take this course usually understand what is data science. they need to learn real knowledge, not spend the whole week on introduction.

Too basic.

If you live under a rock and have never heard of Data Science, a Data Scientist or any terms related to this industry then this is a wonderful course for you.

For everyone else, it is a total waste of time.

This was a good introductory course, especially as someone with basically zero experience in the field. I've been struggling with where to begin (should I take a course on Python? R? What languages are even useful? WTF is cloud computing?) And this course gave me a good starting off point. That said, it wasn't technical AT ALL. It's really just a bunch of "fireside chats" with data scientists, talking about the languages they use, what concepts they're used for, what knowledge is necessary and what isn't, etc. If you're looking for a "roadmap" to continue learning on Coursera, this is it.

This is exactly what I feel the college experience gives students that online or self-taught learning lacks: context. AKA there are a billion courses on Python on Coursera, but none explain WHY I'm learning Python. This course does that. I'd recommend this course for anyone looking to start with data science from zero.

I liked this course very much. The way it is organised to collect different data scientists opinions about the same topic, make it very valuable to the ones who are starting the road to Data Science.

Very learning experience, I am a beginner in DS, but the instructors in this course simplified the contents that made me I could easily understand, tools and materials were very helpful to start with.

Very, very basic... completely useless and a waste of time. I feel like the only purpose of this course is to drag out the certification process so that it costs you more money...

Very nice course and it has a piece of very nice information taught by professionals. The content is related to the practical application of concepts which increase interest in you to proceed further

Good overview of data science, its history, and uses of data science.

I thought this course introduced the topic of data science very well. I think I have a much better idea how to describe data science and common terms associated with the field (like machine learning).

Excellent quality content! It's a great introductory course that really gets you interested in Data Science. I would highly recommend it to anyone curious in learning about what Data Science is about.

useless, wasting time

This course is not consistent with someone who would sign up for an entire certificate. This course is more suitable as a recruitment tool for a certificate program. Watching these videos was an absolute waste of my time.

Good for fundamental knowledge of data science and data scientists.

It is also inspiring for young people like me to get ready to step into the world of data science.

Great course

This is a great course for anyone willing to start exploring the field of Data Science. It starts with basic definitions with proper examples that helps one understand this field with a greater ease!

Friendly and gentle introduction to data science! Can't wait to go further...

It was a good introduction for everyone even novice.

I did not learn much from this course. I did not enjoy seeing the young data scientists talking about their jobs. I was not too impressed by Dr. Haider or the professor from NYU.

Dr. Haider misused some words, such as "judgmental" and "argumentative". Without any evidence or examples for support, he claimed that it was more important for a job applicant to have a sense of humor than technical skills.

This course should have named specific techniques used in data science, and how to acquire the knowledge. Regression was mentioned, but the explanation was inadequate. Perhaps the explanation should have been omitted. K-nearest neighbor was mentioned.

Many students want to know what courses to take next, what computer languages to study, etc. What are the computer programming languages of the future?

Students cannot learn everything. Would it make sense for someone to skip some things, and to focus on others? Should everyone learn Python? Does everyone need to learn SQL? What about Tableau? Is that worthless?

How should students set their learning priorities in order to achieve a basic or minimal skill set within 3 or 6 or 12 months?

Remember that most Coursera students already have a college degree.

The course was created several years ago, so I think it needs to be updated regarding developments of the last three years.

This was a nice and easy course, but the material was quite obvious and not new and could be included in one week lessons of another course.

Poor course overall, not much "meat". An introduction to the subject that could have been given in one hour of lessons.

For what?

The course doesn't teaches anything except for explaining data science benefits and examples.

Good contents and brief understanding about Data Science

It encompasses fine details to introduce data science and explore data scientists as a career.