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Opiniones y comentarios de aprendices correspondientes a Introduction to Data Science in Python por parte de Universidad de Míchigan

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25,787 calificaciones
5,739 reseña

Acerca del Curso

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....

Principales reseñas

YY

28 de sep. de 2021

This is the practical course.There is some concepts and assignments like: pandas, data-frame, merge and time. The asg 3 and asg4 are difficult but I think that it's very useful and improve my ability.

PK

9 de may. de 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

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351 - 375 de 5,690 revisiones para Introduction to Data Science in Python

por Aryan M

10 de jun. de 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.

por Lukas K

18 de oct. de 2021

PROS: Great course to getting started with data cleaning/curation! The course makes it possible to start work in real project with Python (Pandas) when it comes to data engineering activities. The main functionalities in the Panda libs. are covered which gives confidence to continue to built skills in the data engineer/science area. The instructors responded quickly in the forums. Highly recommended!

CONS: If you haven't worked with Pandas before, double at least the time estimates provided by the lecture instructors / course notes.

por Sergio P d R

28 de mar. de 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.

por Cathryn S

5 de abr. de 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.

por Vaibhav S

14 de jun. de 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.

por Kv K

9 de abr. de 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.

por Harshit J

12 de mar. de 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.

por Vipul G

20 de abr. de 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!

por Jeff G

28 de feb. de 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.

por Noureddine C

22 de jul. de 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.

por Karl R

24 de sep. de 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.

por Melissa C

27 de feb. de 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.

por Dibyajyoti D

6 de ago. de 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.

por Chong O K

4 de oct. de 2020

Overall good! The assignments is challenging and comprehensive enough to let students think out of the box and reinforce what has been learned. The assignment questions mimics the questions asked in real-world Data Science projects that indirectly teach student on asking Data Science questions. The instructor can explains the concept in easy & intuitive way and teaches with coding example. This course will definitely horn your basic Data Science skills in Python especially using Pandas library.

por Alan E

21 de nov. de 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.

por Pieter J S M

9 de jun. de 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!

por Ajit S

28 de may. de 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.

por Bala G

21 de nov. de 2016

This course was excellent...I first found the course odd since the instructor went through the material quite quickly in the lectures. It took me a while to figure out that the material was available as a course download. Once I found that it was easy to follow along with the instructor...need two monitors ideally for this to work. If you cannot step through the Jupyter notebook as the instructor goes through the material, you will be lost...and you will not get the most out of the class.

por J H

2 de mar. de 2021

It is not a beginners course in Python, but a beginners course in data science. I found it was very good at teaching the data science parts of python and was a good course for those who are comfortable in Python and willing to not rely on the instructor to hold your hand, but rely on your abilities to take the tools given and determine the best way to put them together. I like how the last assignment had messy data and a realistic example of how you may use the tools in real life.

por Vinayak N

16 de feb. de 2019

Awesome course for anyone looking to venture into the field of Data Science. The instructor puts forth various concepts lucidly and concisely without any irrelevant extraneous details. Beware though, if you are pursuing this for the sake of learning statistics, you might be disapppointed. The instructor adopts more of a tool-based approach teaching you pandas to solve your problems the way you want to. That said, kudos to Coursera and U Michigan for putting this course together.

por Nikolaos K

28 de dic. de 2020

Excellent course. Very well-paced, with good examples and useful code. The instructor seems very knowledgable in the subject meterial, and communicates perfectly. Some basic knowledge of python, data structures and maths is required in my opinion, to have the courser work well. Quizes and assignments are challenging, but that is good for a course, it makes you research the subjects on your own and go beyond the lectures. All in all, a very good course that I would recommend.

por Kevin B

16 de jun. de 2019

Great course overall. I feel like the final output for run_ttest is incorrect though. There are two regions that belong in the university town buckets, but are missed due to capitalization differences, Illinois -DeKalb and Florida-DeLand. I made the region lowercase before merging and got (False, 0.011132653194002319, 'university town') as the output. When my grade came back as 5/10 I knew if I removed the cast to lowercase it would be correct. Thank you for everything!

por Sudev N

10 de sep. de 2020

Very useful course. I would suggest more assignments as they are where you do the brunt of the learning (by looking things up, and learning WHAT to look up), the lectures are very bare bones in my opinion. This could be intentional, but I still came out of the course with a solid understanding of pandas and how to manage data in a real-world environment. A great touch was making us import things straight from wikipedia, etc as it is representative of real data. THANK YOU!

por Derrick G

13 de ago. de 2019

There are plenty of how-to videos and tutorials on YouTube to get caught up on the basics, and there are lots of Data Science classes on coursera and other platforms that go deep into theory and stats. This is the first Data Science in Python class that I have found to strike a balance of practical and theoretical at an intro level.

The video and audio quality is great as well. Start here. Then move on to the deeper and more specific courses on stats or machine learning.

por Liliana p 1

6 de feb. de 2020

I like this course!

If you have little experience in using python commands to work with data, go for this course!

Actually, it has assignments within which you learn a lot more that the videos. It has notebooks of the commands thaught in videos, that you can follow and return to when necessary.

There is a discussion forum that lets you see what answers are available for your questions.

Overall! I'm quiet happy I finished the first course!

Can't wait to start the next ^_^