The course had helped in understanding the concepts of NumPy and pandas. The assignments were so helpful to apply these concepts which provide an in-depth understanding of the Numpy as well as pandans
overall the good introductory course of python for data science but i feel it should have covered the basics in more details .specially for the ones who do not have any prior programming background .
By Deleted A•
The jupyter notebook made this a horrid experience. Plus Coursera really doesn't want you to bother them with your silly questions, relying on peer-forums. If you scroll through the week's discussion forums, many student posts go ignored.
You can't drop the course past the second (I guess) week so the system will keep on keeping on long after you've given up on trying to figure out the janky notebook thing.
Will not return to Coursera for any reason. Breathtakingly bad experience.
By Shreya B•
The course lectures hardly covered what was asked in the assignment. For someone who has a full-time job scouting through discussion forums is extremely time consuming.
By Girija S•
Too much content condensed into 4 weeks of course. The videos are very fast with ~1.5 hrs every week and do not cover what is being asked in the assignments at all.
By Patrick H M•
Slamming down some notebooks is not teaching. Despite this shortcut does the lecturer still miss to show and explain the difficult cases of the different concepts.
By Rachel B•
not everyone who is proficient and knows their craft, is also good at conveying their knowledge...
in short- underwhelmed by didactic skills
One of the worst course I ever take in coursera. The instructor just writes codes on front of us without explanation.
By amin s•
terrible course please improve teaching efficiency and give a proper realistic assignments
By José C V•
too fast .... needed to pause the video constantly
By Jeffrey D R•
Like many others, I give this course a high rating while lodging a minor complaint that there wasn't much instruction provided. The lectures were excellent, if brief; it's hard to imagine anyone having objections to the instructor. But in terms of teaching the material, it was a bit of a drive-by. The lectures show a few examples, while not explaining the syntax or the various parameters. You have to draw that out of web sites and cheat sheets. If you're not adept at doing that, proceed with caution here. In the end, I was worn out from the effort, but felt that I had gained a lot.
The assignments were challenging for me because this was my first hands-on experience with Python, much less with Pandas. I did not find Stack Overflow as helpful as the instructor suggested. Nor did I find much help in the forums, but that's not quite my style.
My bottom line is that the course was time well-spent, but it could easily have been a six-week course with a more deliberate pace through the various pandas mechanisms such as merging and grouping.
FWIW: My recommendation is to get to know Jupyter Notebook early and follow along with the lectures by opening the Week[x] files in the course download folder. You can pause the lecture while you go play with the code to make sure you understand it. Also, I recommend working with a local version of Jupyter and keep your files local. Otherwise, Jupyter loses connection to the kernel, and stops being able to save your work. The messages are disconcerting, and if you've worked yourself into a frenzy, they can cause panic and confusion. So do all the work on your machine and then upload the whole assignment when you are finished. You upload on the "Create a Submission" screen; it takes only a sec. You won't even have to worry about details like file paths; they'll be the same either way. Once you get the hang of Jupyter, you can settle into a work routine. Learn some of the keyboard shortcuts.
By Maria Z•
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
By Steven S•
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.
By Haikal Y•
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 :)
By Zhengyi S•
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.
By Florian M•
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?
By Mohammadmoein T•
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!
By Sourav S•
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.
By Jens L•
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!
By Hamdy M E T•
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!
By Oluwapelumi S•
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!
By YIJUN F•
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.
By Sean C•
This course is excellent if you're looking to learn how to use Pandas inside Jupyter Notebooks. Assignments are autograded and feedback can be received immediately. Course is a few years old and discussion forums contain answers to common questions
By Francis J A•
Great introduction to applied data science. The weekly assignments are challenging and varied, and students are required some independent studying outside of the lessons. The forums are also quite helpful in approaching the assignments.
By Carla F•
Um curso intenso e bastante prazeroso. Gostei de todas as etapas, os videos funcionam bem e estão construidos numa base introdutória, mas o desafio é pesquisar e pesquisar. Muito interessante mesmo!
By Pravesh G•
the course is designed very well. It covers data manipulation topics very well. It has excellent assignments which help in understanding the course concepts more better