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
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: Deleted A•
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: Sabyasachi M•
This is a very good course about the basics of data science and how python can be used to facilitate data cleaning and handling. I am a beginner with very limited knowledge of python (I had read some basics). The course takes you step by step through the use of python libraries and commands mostly used in data science. I would like to point out here that the assignments post course completion were a bit challenging for me as I am a beginner, which is good. This is because I had to research and learn a lot of stuff to complete the assignments apart from the course material. Looking forward to more such courses and assignments. Kudos to the teaching staff and Coursera team :)
автор: Tanmaya S•
Excellent course that throws you to deep-end
Good explanation of basic concepts and learning through challenging problems. This course really pushes you to utilise open resources and refer to forums and standard text which, in my opinion, helps learner utilize full potential of MOOC's. Excellent course for understanding applications of python, but be ready to scavenge forums and refer to the documentation for hours to solve assignment problems.
It would have been really awesome if some more exhaustive guide regarding fundamentals was also provided which could improve understanding of functions applied in assignments even more
автор: Vijay P R•
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•
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•
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: Deep D•
As I was looking for an advanced python programming course with an emphasis on data wrangling, this course fully met my expectations. Assignments and quizzes were challenging and quite close to real world analysis tasks. Videos were concise and to the point and that's what I wanted. I won't recommend this course for a beginner in python as well as for a beginner in data analysis. I think this course will be great if its content is supplemented with a brief refresher of fundamental concepts of some commonly used statistical testing such as hypothesis testing, Ttest, chi-square etc.
автор: Feng H•
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•
"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•
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..
автор: Roger S•
This is an excellent Pandas bootcamp but be prepared that you have to invest more time into the Labs than in other Coursera courses. You should know some Python. I found the Python-Specialization from UMI a good basis. Some prior knowledge on working with data can be helpful.
After some introductory videos you have to find your own way for solving the Labs. I found this very realistic. Later nobody will ask you how many Python functions you know by heart but you will get tasks and you have to find a way to solve them with Google, Stackoverflow etc.
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•
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•
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•
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.
The course has sufficient rigor to prepare you for what is coming in the rest of the program. My opinion is based on my experience with the many Johns Hopkins Data Science courses I completed on Coursera.
The auto grading system can be improved. The feedback on failed submissions is sparse and you have to go to the discussion boards to figure out the solution.
Warning to students who tend to get trapped into figuring out a solution on their own:
PLEASE go to the discussion often when doing the assignments and you will save a lot of time!
автор: Aryan M•
The assignment this course has is just awsome ,as it takes real the efforts to come across the solution but thanks to the discussion section of the course, the faculty is always there to help and question get answered real soon... But i believe that there is need to add more content to the teaching section of the course ... A special thanks to Prof Christopher he is so good at teaching every concept he teaches is as clear as a crystal. But still if there was just more content it would help a lot while working out assignment question.
автор: Sergio P d R•
It is a good course for introduction to data science in Python. I was looking for something to get started with Python and Data Science. I found this course a bit challenging given that I did not have any knowledge of Python, but it was not difficult to catch up with the good friend Google.
The course is well structured. Short videos that give you a first insight on the topics, however to complete the assignments you need to search and read more deeply. This is good because is how it works in the real world and in a job.
автор: Cathryn S•
I started this course a few months ago, but realised I needed a bit of Python to do it, so went back and did the Python for everyone class.
I've learned a lot, particularly about data wrangling in python, and how to approach problems. Its a good start to data science using Python.
And I was extremely grateful to the tutor for his help. Doing a MOOC, I don't really expect much support, and I think this is the first time I've ever asked a tutor something - its great to know that help is available when you need it.
автор: Vaibhav S•
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•
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•
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•
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: Jeff G•
Great intro to Python for Data Science. I have a database and programming background and self-taught Python. I could get by but didn't always understand the nuance of what I was doing (which often led to frustration and far too much time on Stack Overflow). This course is a good overview of the language, including numpy and pandas, and more importantly, it supplies much needed context. Instructor is easy to listen to, and the supplied jupyter notebooks allow you to follow along and play with the code.
автор: Noureddine C•
I found this course very good.
I learn a lot about different aspects of data science : 1) epistemology, 3) tools (Pandas and NumPy in Python) to clean and analyse data, 4) some statistical tools, 5) ethical and/or methodological issues.
When I was doing assignments, I learned how internet communities are powerful in this era of information/knowledge society. Some plateforms as "Stackoverflow" are just wonderful.
One last thing: thank you for accepting my application for funding (in full) for this course.