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Отзывы учащихся о курсе Introduction to Data Science in Python от партнера Мичиганский университет

Оценки: 22,015
Рецензии: 4,934

О курсе

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....

Лучшие рецензии


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


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 .

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4276–4300 из 4,863 отзывов о курсе Introduction to Data Science in Python

автор: Joe R

Jul 25, 2020

The course itself is not so bad. But tasks are frustrating! Solving them gives some value but they are mixed with tons of meaningless problems. Some tasks are not clear and autograder gives little information. But I need to say that I learnt more about Python and Pandas library.

автор: Rishab M

Mar 21, 2020

I personally feel that this course should had been divided into a 8 week course instead of 4 and material should be added on that ,

eg: the problems asked in the exercise

The exercises are way too difficult and require the use of many functions not taught in the video lectures

автор: John B

Jan 08, 2017

Classes moved very fast, especially in the video materials. Functions were introduced briefly without time to digest. While I ultimately did learn the topics through my own research, I feel the class would have been much more beneficial with slower, more indepth explanations.

автор: Ignacio

Feb 14, 2020

Los ejercicios son muy dificiles y hay que hacer mucho reaserch en los foros para lograr llegar al resultado. Las pruebas son diagramadas de tal forma que a veces es dificil llegar por errores pavos al minimo resultado esperable para aprobar los assignments (ej run_ttest)

автор: Nick R

Dec 09, 2018

Content was well paced and well presented but the auto grading submissions took a long time to get used to and were very stressful. The recommended time to complete the assessments was also very optimistic, most assessments took me easily double the time suggested.

автор: Pierre D

Sep 21, 2019

A bit surprised by the low volume of teaching material, and the energy required for completing each assignment.

But a posteriori, it forced me to really engage in the learning. I will probably remember more this way, than if I had listened to dozens of video...

автор: Daniel E

Sep 18, 2017

I found some assignment questions quite unclear. This, together with the grader sometimes marking answers as correct even though they were wrong, forced me to spend many hours trying to find the underlying problem to incorrectly answered questions down the line.

автор: Hitesh B G

Apr 22, 2020

The professor is going too fast and the concept isn't getting cleared. I wish he used some digital board to write atleast what is trying to say or write how the different functions in pandas,series,numpy works.

Although, the assignments were of high quality.

автор: Bharat T

Apr 18, 2020

Although the course helped me learn about Data Science. the session taken and the assignment were different and had to understand the expectation in the output.

But overall it helped me understand how can we proceed with studying Data Science through Python

автор: Ji W P

Aug 27, 2017

Lectures were OK. The pace moved really fast, and I thought the hardest part was that the directions for some of the questions weren't really clear (and I spent sometime trying to figure it out but gave up --- still passed though!!). Thanks for the course.

автор: Mohammad S R

May 13, 2020

For the beginners, It's little bit hard to cope up with the submission according to the lectures. Lectures seems easy but when I go for submission, it seems much difficult and requires more study than the lectures which are not mentioned in the lectures.

автор: G V S J

Jul 15, 2020

this course is definitely not for beginners, I as a beginner had a hard time completing the assignments as I had to read most of the functions used from pandas documentation and it took me a lot of time. please introduce a more beginner-friendly course.

автор: Alberto E C

Feb 26, 2017

From my poitn of view more lessons are needed, achieving exercises require a deep search on stackoverflow and other courses. That shouldn´t be the goal of the course, I expected the lessons to give enough knowledge to fullfil the questions of the exams

автор: Leyla H

Sep 28, 2018

Too much information to absorb within 4 weeks course, requires to spend lots of time offline in learning and researching the Python codes to resolve problems in the Assignments. WOud recommend for hte proficient programmers but not for the beginners .

автор: RUNJIA W

Apr 07, 2018

The teaching process is too fast, especially the assistant teacher who appear at the end.

The assignment is 40% related to the course. And a little bit hard.

The first week assignment is related to the week two, but i did not study week two at that time

автор: Sai S P

Sep 14, 2017

The explanation provided and the expertise needed to complete the assignments were way apart. People with great grip on python and having basic knowledge of pandas library will find this relatively easy. The assignments are challenging and hence good.

автор: Dhruvin S

Jul 10, 2020

The instructor is nice and course content is very good. But with respect to what he explains, the coding is way too fast to catch up! Also, not all for beginners. One should have intermediate knowledge in python and at least beginner level in Pandas.

автор: david a

Nov 23, 2017

Good course but the assignment grader can be annoying as it is very sensitive to data types and data formatting. I get that this is one one of the constraints of auto graders but on a course that is centered around data it can become very frustrating

автор: Tracy S

May 25, 2017

The course was easy to understand. The reason i'm giving 3 stars is more on the preparation of the entire set of courses. They kinda develop as the course goes. The other 4 courses of the specialization were not even ready after this course was done.

автор: Samuel A

Sep 19, 2018

I spent over 150 pounds on this course which is suppose to be less than 40 and last for a month. I work and studied this course at the same time, I would advice to check your price policy because it is definitively not for those in full employment.

автор: Marko D

Dec 21, 2017

I found the assignments strangely difficult, and their difficulty wasn't sourced in the right place . For example, when solving assignments I never went back to see the lectures, but spent most of the time googling syntax, method signatures, etc.

автор: Chhavi

Jul 05, 2018

Looking for some more references for practicing lambda and list comprehension.Assignment auto grader is a pain, it does not give clarity on the answers submitted. Having some detailed explanation on the assignment and approach used will help.

автор: Eric S

Aug 18, 2018

The lectures dont include almost anything from the programming assignments, I had to look for everything on stack overflow. The explanations are great and I learned a lot on the assignments, they are just 2 different things most of the time.

автор: Julien B

Jul 31, 2019

The material is good, but the assignments are incredibly messy (perhaps that's what you're supposed to learn!): errors are never fixed, it's still using pandas 0.19 (this isn't even mentioned) and you can see the course is simply neglected.

автор: Thomas H

Dec 12, 2017

Interesting perspectives on data from knowledgeable professionals, but lacked some hands on learning that I was expecting. Timelines to complete technical assignments were ridiculously shorter than the actual time it took to complete them.