This course is no good.

Unable to run the assignments at my comfort. Half the time there is some issue in submitting the code in jupyter and with hard pressed timelines at work this does not take me anywhere. As a data scientist with little programming background, it is difficult to enable our journey with this course.

Sorry to say. This is a big disappointment for me.

This is not a course. The videos and resources provided do not provide sufficient insight to properly learning Data Science or even getting through the assignments. Content and assignments have rarely anything in common. I would have to spend more than 12 hours to solve one of the assignments. Do not recommend, you are better off leaning out of google.

This course is a didactic nightmare. I do not need someone to read loud what he is typing. I need him to explain what he is typing . The programming exercises would benefit from a clear definition what is expected and an easier access to the raw data. I found something in the forum by chance and in case of questiones the forum was little help for me.

I highly recommend you delete this course from Coursera. I can even imagine how poorly organized a course can be. The assignments are unbelievably complicated and it is unlikely for even data scientists to solve them. It is not more than a waste of time. I just wasted my time on this course

You will not learn any thing from it! that's all I can say

The descriptions of assignments (especially 4) are not very clear. It wastes our time searching what's wrong (you can see the same question is raised up through the years in discussion forum), which always is just because the formatting issue that is not explicitly stated or different interpretations. The assignments should be extensively updated.

Waste of time. If you know python, you'll probably learn nothing new here. If you don't, the professor goes into WAY too high a level, and quickly, for you to actually learn anything. Moreover, he barely touches on why any of this is important, does not go over scikitlearn or numpy, both very important in data science / machine learning.

The courses/videos do not cover most of the topics which are needed for assignments. Have to Google or read lot materials in order to pass. Furthermore the videos are extremely boring as well. This course is not main for the learners who just started to learn Python, as this will demotivated the passion of a person to learn Python.

1. Very difficult to follow and I had to redo this course multiple times to understand the concepts.

2. Feels like the tutor is just reading off a screen and not explaining a topic from his standpoint.

3. The assignments and course topics are disjointed at times.

4. Examples provided are rather complex and needs to be simplified.

Un curso poco práctico, los vídeos son demasiado largos, dando vueltas sobre los mismos conceptos básicos y los ejercicios son bastante complicados en relación al temario (se espera que se busque por internet en páginas como Stack Overflow). No se trata nada de algoritmos, es casi todo limpieza de datos y cambios de formatos.

The pace is too fast! I can not keep up with the course content :(

I had studied "Python for everybody" specialization and "Python3 programming" specialization before. I thought I am now ready for this course but ....

I am going to study some introductory books or find other tutorials first and then come back to this course.

The videos are extremely short and do not feel as if they have the assignment in mind, the lectures do not teach you much compared to what you teach yourself trying to get through an assignment. The majority of time completing this course is spent reading through documentation and other external resources on your own.

It's a really good course for those who start working with data, but I must warn you that for those who has a beginner level in programming that can be a tough one. I really like the approach when you are given the basics and algorithms but you have to investigate the topic yourself to solve tasks - it's the most effective way to learn something. However I understand why some people may not like it.

I would like to mention the forum support - all the questions are solved very-very quickly, thanks a lot to the teachers!

The thing I didn't really like was the last assignment - 4 Qs out of 5 are the same... So if you manage to solve Q1 - others just require some boring data preparation, I understand that it happes in real life, but why here, it only takes time and annoys you?

I would recommend this course for those who has already worked with Python and knows all the basic classes and structures. If not - it's better to take some introductory course (it will be useful anyway, better to start with the fundamentals) .

PS: I really don't understand the comments here of people wh0 complain that they had to go to stackoverflow or read documentation - that's what you do when you code

This is a hard course. It takes much more time than what is listed. It is frustrating because you need to do a lot of work on Stackoverflow or other sources to find solutions to assignments. The lectures aren't lectures, just quick talks about what can be done with Pandas, scipy and numpy. That being said, the professor treats you like a grown-up professional, gives hard real world problems with dirty real world data and asks for you to come up with questions to problems. That being said when you're done you look back and think, darn that was hard but I can actually apply data cleaning with python/pandas to data you might have lying around. As Poe said, It was the best of times and the worst of times, I couldn't decide if I loved the teaching style or hated it, but all in all I can say I learned a lot, though I complained a lot along the way.

This course is really good for getting your feet wet in Data Science! Foundational Data Science theories & techniques were introduced by Prof Brooks. It would be good if you had some foundational knowledge in Python so you can better navigate the course! (In the older version of the course, they assumed you knew RegEx - Regular Expressions & other nifty tricks like strip & split, but I saw that they'll be covering these in the newer version of the course, so a good introduction if you didn't know about these topics!). The course gives you the basic foundations, most of which are necessary to solve the course, but there are some methods & expressions that you'd have to Google for yourself. Similar to a college course, there isn't much hand-holding but still doable. In doubt, ask in the Discussions! The TA's are helpful :)

The contents of the course are concise and it fulfilled basic requirements for fundamental data manipulation. Specifically, the exercises are excellent as they are real problems, which has many untidy problems to overcome during the process, and it's such a pragmatic train on me. Two suggestions: 1 is to add the answers of the assignments, because even though students pass the assignments, there might be better codes to refer and learn; 2 is to strengthen the problem description, as there're several negligence in those assignments. Overall speaking, the course helped me sort out the basic manipulation about numpy and pandas systematically.

I did this course as a 2nd year CS student with limited exposure to Python before the course. I had a basic understanding of syntax and knew basic structures like Dicts., Lists, Tuples. It took me 30h to fully complete the course - I did it in 2 weeks. I would recommend the book 'Python for Data Analysis 2nd' as supplementary literature. The course material is very very limited, which is by no means a bad thing. It just requires you to find answers by yourself. I really enjoyed it personally and would recommend this course for anyone who is interested in Data Science! Just make sure you know your Python basics beforehand.

Honestly, I didn't want to rate the 5 star while I was learning the course, because the assignments of this course was challenging and the course videos didn't talk too much about the coursework. But after I finished the course, I found I have already learned almost all of the knowledge of the book "Python for Data Analysis" by Wes McKinney, which is also the recommended book in the course. And I can do data analysis work with python right now. You might think why do I have to register a course and then learn by myself, but what if this is a good chance to push you out of the comfort zone?

Awesome course for starting the journey with Data Science. It covers Regex, Numpy and Pandas in great detail.

Weekly assignments are so good that you dont even need extra practice as part of learning. These assignments will make sure you are well acquainted with frequently used things in Data cleaning /manipulation. Must do course for every person who wants to start the journey with Data Science. This course was suggested by my friend, who did this and other 4 courses as part of Applied Data Science course and was able to switch from being Mechanical Engineer to a Data Scientist.

This was indeed an amazing introduction to Data Science. I should accept that I found the assignments kind of challenging and had to spend lots of time on some of them, but that would only make you learn more. Also, a proper background with Python is required for this course. Make sure you have enough background with Python Data Structures. If not, I'd recommend the following course first:

Python Data Structures - Charles severance

Good luck on your journey!

The quality of the assignments is really good but the instructions for assignments is really poor.

I had to do read through the discussions to solve almost each and every problem. The assignments are really time consuming and challenging.

Also, I had to refer to stackoverflow for countless number of times to derive the logic.

The instructor has only touched upon the material but additional videos should be included by the TAs for the assignments.

Thanks,

Sourav

Excellent learning materials. Clear concise explanations, but with the focus and majority of time devoted to activity-based learning: exploring the docs, practicing skills, and developing solution code. Even better is how subsequent lessons not only build on previous skills, they actually help guide and refine approaches even further. Well orchestrated progression of zone of proximal development. Thanks for a great learning experience!

Great Course and Awesome Instructor. The course is very practical and hands-on. All assignments starts with messy data and leave it up to you to start cleaning and manipulating the data with some modeling objective in mind which is what a real data scientist typically do. Thanks for the course , it was a really cool experience ! I really enjoyed the course and it was a bit challenging sometimes!

This course is really wonderful and tasking. You'll get to know the core foundations of Data Science and useful libraries Data Scientists use to manipulate data. The assignments are very thorough and deep. Many thanks also to all the teaching assistants who were available to help, especially to Sophie Greene and also to Yusuf Ertas. I look forward to completing the specialization!

Overall the course is great for people who want to begin with data science. The skills it incorporate are very useful. The only thing to improve is that we could be given more hints when doing assignments. Sometimes we are not familiar with what can be done with Pandas, so it took a lot of googling to complete the assignment.

Excellent course, even if you have taken other Python courses or if you use Python regularly. This course provided a good introduction to many ways you will use Python in real-world applications. The assignments were challenging enough and some required research on your own, which is exactly what you do with real problems.