I throughly enjoyed the course and the fact that everything was explained thoroughly. I always enjoyed Dr. White's personal experience with Data Science as well as other Data Scientists point of view.
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.
교육 기관: Andrew F•
Great introduction to Data Science!
교육 기관: Vincent Z•
This is really an introductory course, and there is not much to be learned, not a single line of programming or a single chart generated. But it can all be done in a single day, so it is a necessary evil to reach the good stuff in the specialization, I guess.
교육 기관: Nicholas B•
Extremely basic introductory course. Unfortunately you don't learn much about actual data science methods. Quiz questions tend to require you to memorize word for word quotations of supplied text, as opposed to challenging you to think about concepts. I would recommend this course for someone completely new to the idea of data science, but not to people who already know a bit.
교육 기관: Enas J k•
This course has very detailed information on data science and data scientists. The real-life examples and applications of data science presented by different data scientists are also amazing. Overall an excellent course for anyone who wants to venture into this amazing field.
교육 기관: Abdul W•
After completing this course you can easily understand and define what is Data Science and clear your doubt about Data Science.I recommend this course to all beginners.
교육 기관: longmen•
I have learnt about what the data science is and it's basic knowledge. I am glad I took the course. I will continue finishing the rest of the courses.
교육 기관: Kanchan P•
This is a very good introduction to what actually is data science! Lot of people gets really confused with the definitions and area!
교육 기관: Sergi•
Direct to the point. Increases one's passion to study Data Science by summarizing the main topics. Simple and brilliant
교육 기관: Amarjot S•
This course equips a person with all necessary knowledge required to get started in this field with confidence.
교육 기관: uzair k•
A very brief and complete introduction of Data Science from industry experts highly recommended course
교육 기관: Mahesh K•
It encompasses fine details to introduce data science and explore data scientists as a career.
교육 기관: Harsh R•
Amazing course to a roadmap to data science
교육 기관: Ferry T•
Great for introduction!
교육 기관: Irfani K•
Very good thank you
교육 기관: Chan H D L•
Very informative and presented by respected individuals with a passion for the field. The only critique is that the material might be a little outdated as it seems to have been created around 2014-2015.
교육 기관: Dwight F•
It does in fact answer a basic, fundamental question; what is Data Science?
교육 기관: Steven G•
I genuinely enjoyed this course, but the quizzes are absolutely irrelevant and petty to the point of absurdity. How is attributing a quote to Hal Ronald Varian going to make me a better data scientist? How is know the specifics of one person's research about houses relevant in the massive field of data science? Your quizzes need to focus on key concepts instead of minutiae
교육 기관: K M•
It's a decent course if you don't know why you want to go into data science but if you have an idea, then it's just listening to other people talk about why they like the field without teaching you much.
교육 기관: Anna R•
Broad review of the definition of data science. Can easily get the same information from a quick Google search. Week 3 was the most useful.
교육 기관: Roger A•
Many interviews, nice chats, but not so much content. I was expecting some more theory/practice, not so much documentary.
교육 기관: Ross E•
Most of the transcripts of the videos were from old or different versions of the videoes. This fails the basic principle one of the core of the five Vs: Veracity. None done.
There were countless errors in the IBM voiced-over, animation videos. For example saying that data mining is "automated" when it was just explained that data priming - which is often highly manual at the outset - is an important part of the first steps of data mining. It is absolutely NOT inherently an automated process from end to end.
The final "capstone" assignment which was essentially regurgitation was graded incorrectly. Especially with respect to the final reading. Students were asked to list the "main" sections of what should constitute a report to be given to stakeholders following data science based research. Firstly, dictating sections is stupid as you need to customise to your audience and NO, doing it that way should never be prescribed as universal. Secondly, even adhering strictly to what the reading said and ONLY what the reading said, the grading criteria was WRONG. How on earth did you list Appendices, CLEARLY stated as OPTIONAL as one of the 10 main sections? Not only that, you listed sub-sections as whole sections. For students that got the answer correct, I graded them as such and commented that I'm doing this because the criteria was in fact erroneous.
It's one MOOC. How hard is it to get the basics right? What happened to the IBM culture that used to make software engineers write all their code without a compiler to MAKE SURE what they were building was as correct as possible before compiling because of a focus on quality?
Amateur hour over here. Not inspiring.
교육 기관: SHANNON L H•
Was pretty upset that the answers on the final assignment were incorrect according to the course materials. I am an OCD person that is very by the book, who studies and seeks my answers directly from the materials. I am hear to learn and depend on you to have accurate learning materials and tests that follow the course materials.
I create procedure manuals for staff. One of the first things I do when I finish a new manual, is go through each thing, step by step, to make sure it is accurate. My manuals are for a handful of people, your learning materials are for thousands of people, many of which have language barriers, as English is not their first language. So this makes it even more important for your assignments/tests to be extremely clear in their questions and the answers correct according to the course material. When you have a tremendous amount of complaints about this on the discussion forums and no one of power is doing anything to correct this, this is a major issue.
I had started a specialization with Coursera a few months before and quit near the end of course two due to extreme frustration with these same issues. I love the idea of these specializations, and would love to take many of them. I hope and pray that the rest of this course will be a vast improvement over the last assignment in Course 1 week 3.
교육 기관: Krishna B•
Honestly, I just expected too much from this course. It ended before I could even fully realise it had begun. Grading seemed to be less along the lines of "We want you to understand this" and more along the lines of "We want you to memorise a specific quote from a puzzlingly long video that you won't feel like watching throughout, and will follow up with a reading which is more or less a transcript of the video."
Take up the course if you've never come across the terms "data science" in your life. Otherwise, it's just time and cognitive effort down the drain. This course is basically clickbait that claims to need 3 weeks of your time, but can be completed in a single hour if you're a fast reader and have a long lunch break at work.
교육 기관: Greice F•
- Texts have poor quality so they are hard to read and the references are not available.
- No extra materials are available.
- The quiz are pointless: you can answer without understand the text or the videos. You just need to find the key words on the text, no need to comprehend it.
- The videos are very boring. They are sometimes contradictory. Some questions are not answered and others are answered over and over again.
Finally, I thought the course poorly structured, boring and with low quality material. I could find better material on the internet for free.
교육 기관: Tiago F V C L•
The course itself is too general; you complete the course and it's hard to say you actually learned something new. The exercises are extremely easy, you could easily skip all the videos, open the text for each assignment and answer. Furthermore, the testemonials appear to be randomly picked students who say what they think they're supposed to say, or just give their own opinion; this contributes very little to the viewer's actual learning. An introductory video to data science would've had the same outcome as this entire course.