Mar 16, 2018
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 .
Dec 10, 2017
Wow, this was amazing. Learned a lot (mostly thanks to stack overflow) but the course also opened my eyes to all the possibilities available out there and I feel like i'm only scratching the surface!
автор: Liam G•
Jun 24, 2019
This was a superb introduction to Data Science in Python. Before I started this course I had completed a few introductory Python courses, but never felt confident enough to perform standard analyses in Pandas. This course has changed that and I am now confidently using it in my day job as a Data Analyst, helping me to automate some workflows, analyse data much easier and so on!
What is really great about this course is that it sets you up on Jupyter Notebooks to follow alongside each week's lectures, and then gives you an assignment to complete each week in a notebook. It really helped me get to grips with using notebooks, and debugging code and so on!
As a Data Analyst, and budding Data Scientist, I cannot recommend this course enough!
автор: Rahul S•
Jan 26, 2018
A well rounded course that gives a good introduction into the scope and use of python in data science. Lectures were kept concise and to the point. The assignments were really useful as they used real world data and gave a good understanding of using python from the data cleaning stage to arriving at meaningful results.
One negative I may point out is that the time that is shown for assignments doesn't really reflect the time it takes in reality as people need to do quite a bit of self study for a lot of the questions. If you could increase the time showed, it would really help working professionals like me to plan their time for it accordingly.
A really good course with good course materials and helpful teaching staff!
автор: Antonin P•
May 15, 2018
Course is great. I have learned a lot, but I am affraid that the assignments are not for everyone. It is sometimes hard to find a way how to make an automatic grader to pass your programming assignment. I had to use a forum a lot, not to find a solution, but to find a trick how to convert my result to the correct format and so... In first assignment, it was poorly described how to submit it, for instance that the function can´t use variables from previous functions. However, thank you a lot for the course, I have learned Pandas and general Python even though I didn´t use them before. But I regret a bit of the time searching throughtout a forum when my results was right, but the grader didn´t let me pass through.
автор: Milan V•
Sep 02, 2019
An excellent course. Given the restrictions inherent to this kind of format of teaching (e.g. very short 'lecture' videos), I do not think that the course could have been organised any better. In other words, one gets the feeling that one has extracted the maximum of knowledge possible, within the limitations of the Coursera platform. This is probably in part due to the 'hands-on' approach to the programming assignments, which I though to be very well thought-of. I would also like to praise the course staff for being very active on the Discussion forums, and trying to answer as many student questions as physically possible. In the future I will definitely continue with other courses in this Specialisation.
автор: Loïc B•
Aug 27, 2019
A very good introduction to essential Python tools for manipulating data. I recommend taking this if you either know some Python but are new to data science, or if you have at least a basic grasp of how to manipulate data with other software. Users without prior knowledge in Python or data wrangling will find this course too hard.
Prof. Brooks is very clear, and the Jupyter notebook environment helps tremendously. I liked a lot the format of assignments as well, though meeting the requirements of the autograder can be tough sometimes... Another point on assignment: the version of pandas used for the course and the current updated version now differ a bit, so that some syntaxes may differ on a few functions.
автор: Benny P•
Sep 20, 2017
As others said, this course is fast paced, has only brief information in the videos, and has challenging programming tasks that requires students to get the required information elsewhere that was not given in the intros. Whether you like it or not depends on whether you are able to learn by yourself (with guidance on what to look for) or do you want to be fully nursed. For me, I LOVE IT! The material has enough information that I need, and I don't mind searching for references myself. The programming tasks are also challenging as it requires you to be really careful in reading the specs, and that is good. If you're not able to enjoy this course, maybe you need to take other introductory courses first.
автор: Paulo E N•
Oct 13, 2017
I really appreciated this course. The assignments are excellent, but they took me more time than the announced.
The ability to submit your assignments and have them automatically corrected, even if you are note paying for the certificate, is great.
I just think that maybe it is a "too hard" introduction. You must already know python, and, I'd say, should have already studied a little of pandas. The explanation of pandas is really quick, but full of valuable real world tips.
For the assignments you'll need a lot of pandas knowledge that isn't the videos, so prepare for a lot of searching in StackOverflow and in the docs. I believe it is purposeful, so the assignments mimics a real world problem.
автор: Karen Y•
Dec 01, 2016
This is a popular course series that many have expressed interest in taking. Rigorous and challenging course that offers excellent, high quality teaching of python pandas. The University of Michigan does not disappoint and neither does the delightful instructor Christopher Brooks. I highly recommend this course to anyone serious about python and data manipulation. Time and money worth spent. Interesting assignments and datasets are found each week. You will learn a great deal. Concise videos with sharp insights from an expert on pandas are seen throughout. Once you finish the first course of the series, it leaves you excited for the second course in the series. Rock on "pandorable" pandistas!
автор: Deleted A•
Jan 21, 2017
This was overall an excellent course, I very much appreciate everyone who has made this happen. However, the very last question of the very last assignment I found to be substantially more difficult than everything else, by a very large degree. Because of that one question I ended up moving my session twice and nearly dropped the course. https://www.coursera.org/learn/python-data-analysis/discussions/weeks/4/threads/1Fkg-ryCEeaIRw7T1E5tHA/replies/vK-NSNNOEeaBeg5U4yHl7A is what finally got me over the hump. The instructions were not very clear to me but the price ratio calculation was the key to success. My guess is that missed it somewhere. Anyway, thanks! I will be moving on to the next course.
автор: Vijay P R•
Nov 27, 2016
The programming assignments are challenging ( atleast for beginners),with each question taking about 3 hours to complete .Many topics in Pandas are covered , making us reading the docs and finding solutions,that further helps in learning . Excellent course , good support from other learners taking the course and very very informative . No other platform can give us a course ( and knowledge ) of this standard . Planning to take more courses from courseera . However a small feedback : The description for some questions are slightly confusing . Please make such questions more descriptive with examples .
автор: Aditya S•
Jun 27, 2018
This is one of the best courses on coursera by offering, the instructor Christopher Brooks has a great ability to deliver a lot of information/knowledge in a concise manner! He is a great teacher. I really learned a lot from this course, and reading the course blogs like : science isn't broken, following the data skeptic podcast, joining in on discussions. The discussion forum has great methods by Sophie Green , the teaching assistant, with great stackoverflow links added. This course has a steep learning curve, but as much as it was tough, by and large it was worth every minute investing in it!
автор: Max P•
Nov 16, 2017
This is an excellent start to Python, showing the basics of lists, dictionaries, tuples, Pandas Series and DataFrames, and numpy. The lectures are concise and hit the right elements to get a quick grasp of Python. The assignments are sometimes with real-life data, which makes the course particularly engaging. During the assignments, the hands-on approach really helps a student grasp the details and delicacies of the different Python and Pandas objects. As an improvement, I would say that some of the text within the assignments could be expanded to nip any possible confusion in the bud.
автор: Feng H•
Mar 10, 2017
As a python newbie, I found this course challenging yet so much fun to learn. Dr. Brooks presented the lectures in a very organized way and made them easy to follow. If you have experience in R, you probably would pick up Pandas real quick. Students are expected to devote a lot of time into the assignments and try to find the answer on your own. But with all the great tips and clarifications from our diligent mentor Sophie Greene, it's definitely achievable.
Will take the other courses in this specialization and definitely recommend it to anyone who's interested in data analysis.
автор: Praveen R•
Sep 16, 2019
"Introduction to Data Science in Python" is very good introductory course for Python DataFrames/Series and related data interpretation methods. I got to learn to read in excel/cvs/text files and clean them and extract meaningful data. The final assignment was very informative into how applied DataScience work. Overall its an intermediate level course with ample coding to do and experiment. It is a very hands on course which is most essential to understand fundamental concepts clearly. I am happy I took the course. Looking forward for the next course on visualization.
автор: Ricardo A L•
Dec 02, 2018
Es un muy buen curso.
Lo que lamento que es que el Autograder es Todo o Nada y es imposible tener menos de 100 puntos. El codigo puede tener cosas buenas o no tan buenas, pero no todo esta mal.
No logre aprobarlo en la ultima Q6 pero en general es muy buen curso.
Quizas por el tiempo que uno dispone , puede ser poco para profundizar mejor el estudio. Yo trabajo en area TI de Retail y en estos dias de fin de año es dificil..
Muchas gracias a todos. Quienes preparan el material y a los instructores.
Un abrazo para todos...menos para el implacable AutoGrader..
Apr 27, 2018
this is a challenging course if you are just coming out of the Python Intro specialization. Much self learning is required, however that is how most programming happens, so I think overall this is a very good course to partake it. I don't know if perhaps the questions could be worded more clearly, as much time was spent trying to understand them, and I had to resort to the discussion forums to clarify their intent. In any event, that might be also reflective of difficult demands in the business world, so I still give this course a 5 star grade.
автор: Marianne O•
Jul 15, 2018
This is an excellent course. The professor builds concepts very naturally, lectures well, and gives good examples. Most of all, the exercises are really designed to test comprehension and the final week's assignment is an example of a real world question using real world data that must be cleaned and interpreted to test a simple hypothesis and derive an answer. This course has made me feel like I have the tools I need to take on my own datasets. Even the optional reading/listening assignments in this course are interesting and thought provoking.
автор: thomas m•
Oct 29, 2017
Great introduction into pandas environment in Python.
First assignment was most difficult in my opinion. There were times i had no idea where to look but stackoverflow and the pandas documentation were great references, which once i understood how to better search and interpret, i was able to do what i wanted.
One thing i liked was there was ample struggle in this course. I've done other coursera courses and found that the exact problem statement and solution were posted online, which was hard to avoid when looking for more generalized help. I
автор: Leo C•
Jan 15, 2017
This was a very helpful course in getting comfortable with using the pandas library and different concepts in numpy in data analysis. The fact that the instructors and course materials do not give you 100% of the tools to complete the assignments is a plus. Every data analyst and programmer inevitably will have to rely on self-guidance.
This course by itself may not be immensely useful in the professional world, but lays a strong foundation for the student to focus more on plotting, analysis, and conceptual learning, rather than on code.
автор: Vaibhav S•
Jun 14, 2018
Assignments were bit tricky and more challenging than i expected.Most of the problems were based on topics that i was totally unaware of.But soon i realised that self gained knowledge is actually the true knowledge.I had to refer some text books also, for completion of my assignments.But still the overall quality of the content was good.And after completing this course, i have acquired one more skill, i.e. to search for the genuine sources of information rather than the fuzzy, confusing and more decorated one's.
автор: KARTHIK K V•
Apr 09, 2017
Definitely one of the best course I have taken so far.
The course started with refreshing the python basics and then it's a deep dive in to the ocean of Data Cleaning tasks.
Special Thanks to Dr Brooks for keeping the course straight forward and simple. All the concepts are made very clear during lecture and the assignments are a perfect application of these concepts.
Even though assignments are challenging, will feel the sense of accomplishment on completing these.
Thanks to the entire course team for the course.
автор: Harshit J•
Mar 12, 2019
This is an awesome course which slowly dives down into Python week by week. The professor has explained all the concepts in a concise manner. This course covers all the basics of pandas and numpy library and leaves you on the door step to explore them in detail.
Thoroughly loved the whole experience. Special mention to the Jupyter integration which makes it easy to code and execute.
Thank you to the entire team and specially to professor Brooks for making this special and providing a nice learning experience.
автор: Vipul G•
Apr 20, 2018
It was an overwhelming experience to gain amazing knowledge about python in depth and is perfect for getting started with data science. The assignments were awesome and traversing through the pandas documentation was quite exhaustive yet rewarding. The course offers great self learning and working on practical implementation of the projects. The idea that pandas can explore various data science approaches interestingly was given insight by the course. I thank the instructor for his awesome approach. Cheers!
автор: Melissa C•
Feb 27, 2017
Very good introduction to Pandas Series and DataFrames for Data Science. Fast paced course with good supplementary materials. The homework is progressively challenging. Sophie the Teaching Assistant is particularly helpful in the forums. I don't recommend this course for those without programming or python scripting experience. Also, the homework exercises took me significantly longer than the estimates projected, but I budgeted about double the time and was able to complete the course on time.
автор: Alan E•
Nov 21, 2017
I love all the features that pandas and numpy have to make routine data cleaning tasks easy. They are so much easier to use than core python, require less code, and work faster. I love these methods (e.g. list comprehension, mapping lambda expressions across data frames, pandas datetime functions, read_csv, merge etc... the list goes on...). Thanks for the great tools. I've learned a lot of valuable techniques from this course, and have started using them at work already, to great benefit.