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Kursteilnehmer-Bewertung und -Feedback für Introduction to Data Science in Python von University of Michigan

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4,946 Bewertungen

Über den Kurs

This course will introduce the learner to the basics of the python programming environment, including fundamental python programming techniques such as lambdas, reading and manipulating csv files, and the numpy library. The course will introduce data manipulation and cleaning techniques using the popular python pandas data science library and introduce the abstraction of the Series and DataFrame as the central data structures for data analysis, along with tutorials on how to use functions such as groupby, merge, and pivot tables effectively. By the end of this course, students will be able to take tabular data, clean it, manipulate it, and run basic inferential statistical analyses. This course should be taken before any of the other Applied Data Science with Python courses: Applied Plotting, Charting & Data Representation in Python, Applied Machine Learning in Python, Applied Text Mining in Python, Applied Social Network Analysis in Python....

Top-Bewertungen

PK

May 10, 2020

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

AU

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!

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251 - 275 von 4,873 Bewertungen für Introduction to Data Science in Python

von 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.

von 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.

von 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.

von 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..

Atte

Ricardo

von Roger S

May 22, 2020

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.

von Zak

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.

von 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.

von 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

von 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.

von Madhu

May 02, 2020

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!

von Aryan M

Jun 10, 2020

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.

von Sergio P d R

Mar 28, 2020

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.

von Cathryn S

Apr 05, 2020

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.

von 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.

von 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.

von 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.

von 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!

von Jeff G

Feb 28, 2020

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.

von Noureddine C

Jul 22, 2020

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.

von Karl R

Sep 24, 2020

There are a lot of negative reviews for this course, and I would say it's not for everyone, depending on what kind of learner you are. I learn best from trial and error, this course is very assignment-centric, requiring creative thinking about how to solve the problem rather than following a procedure. This is not the best course for learning the optimal way to perform specific functions, but it's a great course for those that are trying to learn Python as a new skill by solving well-designed problems.

von 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.

von Dibyajyoti D

Aug 07, 2020

This was a really thought out and well planned course. Gave me a proper exposure on Pandas. The best part about the course is its assignments and the fact that it makes you think and even lose your mind. The discussion forums are a bliss and the work that Yusuf Ertas puts in is phenomenal. I've seen him responding in almost all of the doubts put forward. Above all this course taught me to read in data how ever challening it maybe into a dataframe and encouraged me in making my code more pandorable.

von 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.

von Pieter J S M

Jun 09, 2019

This course was very much helpful to understand Pandas as a Data Science tool. I started to understand the way you need to think, whenever you use Pandas. Especially the assignments were very good. A very small exception is the assignment in week 3, in which you have to clean your data frame. That was a bit too extensive, I think. I rather used that time and efforts to learn to apply more statistical methods.

But overall: this course exceeded my expectation and I am very much helped by it!

von Ajit S

May 28, 2017

This is a very helpful course. The main advantage is that you will learn a lot of new ways to do operations over data. And this is an intermediary course that assumes that you already know about statistics, mathematics behind data. From my experience I want to tell that if you are taking this course don't just rely on the video this course provide (however videos gives you full context on the work that has to be done), you have to do your own research and reading from external sources too.