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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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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

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

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.

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376 - 400 de 5,722 revisiones para Introduction to Data Science in Python

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 Md. A A

9 de ago. de 2022

Awesome course. The lectures are very good. One thing that I liked a lot is that they taught regular expression which is very helpful in processing strings. Also, the assignments are very tough and if you can solve them correctly (not hard coding, and by yourself), it will boost your confidence a lot. And please remember this course is not for beginners. If you have basic knowledge of Python (list, dictionary, function, list comprehension, etc), it won't be that tough.

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 ^_^

por Sneha N

16 de abr. de 2021

This is a great introductory course to someone trying to start using python and Pandas for their data analysis. I have been Fortran and Matlab user all my life and recently I started working on big nested datasets with multi index and Pandas is definitely the most efficient way to work with such datasets. This course helped me understand the basics of Pandas and Regex and working on the assignments equipped me with skills needed to work with the big datasets I have.

por Paresh D

11 de jun. de 2019

Fantastic course.I have learned a lot.I really enjoyed playing with various data frames in the assignment.Discussion Forums were very useful.Special Thanx to Yusuf,who used to help me in clearing my doubts.The only thing with which I am dissatisfied is the teaching instructor.He has enough knowledge and is a genius,but his teaching style is mundane.I wish this course was taught by Dr.Chuck.I really like the way Dr.Chuck taught Python for Everybody specialization

por Abdul S

21 de ago. de 2017

One of the best courses I've attended in the Coursera. The programming assignments were tough. But I think in some assignments instructions were not clear or were not available at single place. Ideally all the instructions/hints etc should be placed inside the notebook for assignments.

Overall the course challenged my learning. And I needed to do lots of googling to look into stackoverflow, pandas documentation etc to reach the correct answers. Awesome course.

por Davide C

26 de nov. de 2020

Great course! You will learn using the Numpy and Pandas libraries, together with the Python Regular Expressions (Regex). The third and fourth assignments are challenging and put you in front of (relatively) complex real databases (which is great) and go also beyond the material discussed in the course, but this pushes you to search on Stack Overflow and read the libraries' documentation, which is a great way to learn. I would definitely recommend the course!

por Silvia P

22 de abr. de 2020

Wow! I've been looking for a solid course teaching me how to use Python applied to Data Science and not giving me only theoretical notions. I've struggled at times, but it's this struggle that let me master all the commands. When I felt stuck on a problem I would go in the Discussion section and read the post of my fellow course mates and I found helpful insights to apply in my code. I can't wait to go on with the whole Specialization! Keep up the good work!

por Yarema M

26 de may. de 2020

This course has been excellent for helping me understand the core functionality of the NumPy and Pandas modules. The lectures are very detailed and implore you to delve deeper into the subject on your own. My favorites, though, were the end-of-week assignments. These let me assume the role of a real data scientist, digging in huge amounts of data to uncover the important details. Overall, this course is a great introduction to the study of Data Science.

por Shreyashi G

12 de feb. de 2019

This course is a high level and precise introduction to the python programming skills necessary for any data analysis exercise. It is adequately paced which is great for anyone who has some prior knowledge of python. The assignments are particularly challenging which I thoroughly enjoyed. The lectures would effectively introduce a concept and the assignment to follow would test the understanding thoroughly - a structure which in my opinion worked great!

por Zhao J

25 de feb. de 2017

It's a great course! The assignment is amazing! It takes me several hours or even one or two days to finish it. I have to say the assignment is really valuable. Professor Brook is also great and the video is greatly filmed. It's worth taking if you have already learned some of python and want to know more about python in data analysis. I have already learned the book Learn Python the Hard Way and played with python for a while before I take this course.

por Gustavo W

19 de nov. de 2016

Really good course BUT be prepared for a very fast pace of the lectures. I'd placed in the "advance beginner" or "intermediate low" level, therefore, you need to have previous knowledge of Python. As in College, lectures and assignments are somewhat related, but you will spend some additional time investigating by yourself to get the appropriate responses. Again, just like College where Lectures are level 2-3 but assignments are level 7-8 (out of 10).

por Kevin & A

11 de abr. de 2020

The course is very good, but the assignment is a challenge for me. It took me a long time to finish my homework, but I learned a lot from it. Basically, the professor talked about the most important knowledge points, and the rest learned independently by extensively searching for information. I have learned a lot, but I am a bit worried about whether to choose the next course. After all, the time I can allocate to my studies is not that sufficient.

por Chirag R

27 de jun. de 2019

The course was pretty exhaustive and I felt like I learnt everything that this course intended to teach me. The assignments were pretty tough, given that I had no experience of Python before this, but that's down to me for not taking the "Python for Everyone" course, as recommended by our professor. A few more interactive and intermediate level problems could go a long way in making the course takers better skilled and equipped with Python.

por Joshua T C X

11 de jun. de 2019

This course is NOT for the those with zero experience in programming as it assumes some familiarity with concepts like object attributes, functions etc and requires you to spend some time reading up python/pandas documentation on your own. While I think that the professor could use simpler English to communicate more complicated concepts, overall it is a good course with good assignments that cover the key concepts required in data science.

por Zhenwei Z

9 de feb. de 2019

It's a great Course, covers a lot of stuff. It seems that the content allocation between lectures and homework is not well balanced. The lectures are quite short and fast, and the homework are heavy.

It would be great if the lectures can cover more details, especially the techniques that are used in homework. Also the if the homework can provide more instructions and descriptions and maybe some self-checking hints, it would be very helpful.

por Shabeeh B S

15 de abr. de 2020

Being a newbie to data science field and introduction to new libraries and logic this lab was indeed the most difficult that I have attended . To be honest I took more than the time required to complete the lab since I had to attend other classes on numpy and pandas distribution to get an baseline and now I still haven't perfected but have basic understanding but I believe I can put effort and bring out the best ! Thanks a lot Professor !

por Eunjae J

23 de abr. de 2017

Much harder than I thought. Very in-depth introductory learning of python.

Preferably better if you allow scripting in .py because notebook is rather heavy and hard to

debug while assignments..

Hope you cover a bit more in detail with language structure, as well as give hints for solving assignments, since many parts were pretty above course level.

I would say the assignments were hard even for an R practitioner learning python like myself.

por Mukesh K

5 de nov. de 2019

This is an excellent for those who want to learn python pandas. The course content is really good. The assignments are really helpful and they truly covers what is taught in the lectures. Had fun going through the video lectures and solving assignment. Though, in the last assignment 4, if a little bit of data description was added, it would have been good. Thanks for making the course and helping providing the content through Coursera.