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

4.5
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Оценки: 21,840
Рецензии: 4,899

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

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

SI

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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4576–4600 из 4,829 отзывов о курсе Introduction to Data Science in Python

автор: Guobin X

Jul 18, 2017

I have to say, as a new data analyst, even though I have started my work. It is still difficult to complete the assignment. The assignment is far away from the lecture video, which makes the assignment painful and you may lose interests in the process. Even the assignments are not written in a understandable way, so you have to go to forum to clarify each question in the assignment. So please make the learning process me more enjoyable and easy for the starters. Data science is a great career and and I believe it is the future.

автор: Thomas M S

Dec 10, 2017

Overall I have to rate the course sub par, so 2 stars.

The lectures seem disconnected from the assignments. If you're not already proficient at Python you'll spend your time on stackoverflow.com looking for ways to solve the questions. The assignments took me a lot longer than scheduled.

I did learn a lot by doing the assignments (using stackoverflow). I credit the course with "forcing" me to do the assignments.

Sophie (staff) was the saving grace when I really got stuck. Without her I would possibly have thrown in the towel.

автор: Chathuranga A

Apr 05, 2020

Course materials were too brief to work on the assignments. You have to do lots of your own homework to get through the assignments. It is almost one can do assignments without referring to any of the class materials. It is obvious course cannot explain all the material but they could have organize it better by making clear focusing the assignments. Also it would be much useful if they can add comment in the Jupyter codes. Assignment 4 was very poorly explained. It is not tough at all but the explanation made it worse.

автор: Lionel V H

Jan 11, 2017

Videos are fast-paced, material is limited (no real slides or extensive doc). Exercises are sometimes not clear in their statement. Activity on the forum compensates that. Exercises are however close to challenges you face in real life. Finally, the start date was delayed and there is no clear visibility on when the other modules are started. So, the course could be better given, provide more material and be better coordinated. I followed one Python course at Rice University which was by far better given.

автор: Muru Z

Nov 01, 2019

Pretty bad experience, this course let me feel like listening a people read a book. Professor just simply go through the material with relatively high speed, the connection between each part is unorganized, the graduate student even goes through the material with higher speed. Assignment sometimes confusing and autograder add even more barriers on my path. Assistance answer question quickly in discussion form which I'm appreciating, however, can't compensate for the disappointed quality of the course.

автор: Wahid C

Jan 29, 2017

The course lectures were subpar and didn't cover the material in the assignments. Googling for answers and checking stackoverflow for code is a great way to get tips, but it doesn't teach you the core material. I would have rather had links to supplemental readings that the materials were based on. I would not recommend this course as an introduction course unless you've had significant experience with Python data structures and know how to work with lists, dataframes, and iterate over those.

автор: Martí S L

Mar 30, 2017

Really disappointed with this course to the point I'm quiting -in spite of having paid for the grade-. It reminded me of my days at the university where I found being a great scientist/engineer didn't mean you were a great teacher. And this is the real problem, even things that should be easy to grasp are difficult to understand -just the opposite of prof. Bill Boyd who makes learning a joy-. Because of this I would only recommend this course if you already have an intermediate level in Python.

автор: Josselin G

Sep 13, 2019

The professors are very clear and the speed if good enough so that if you have a computer science degree you won't get too bored.

But, ohhhh my good the grading is terribly frustrating. If you've left uni and spend more than a couple of months in the corporate world you will find it terribly frustrating. You had to fiddle around for hours around data format and some other potential issues.

For interesting python problem with a nice layout and helpfull solutions, discovery go to checkio.org.

автор: Martynas V

May 03, 2020

This course was extremey hard. The pacing was fast, it seemed like the instructor wanted to end the lecture as fast as possible, I had to rewatch a 5-7 min video three times with frequent pausing to just get the idea of what is going on. The assignments were really hard, especially final questions. I would suggest making longer lectures with slower pacing taht would cover all the material you need. I have just finished this course and feel frustrated instead of motivated to learn more.

автор: Schmidt, L

Jan 22, 2019

i really liked the lectures and i learned a lot of new stuff but the autograder was very annoying to me. i spend hours on transferring my answers to the correct format. There were no templates or good describtions for the right format provided so you had to read through the forum and talk to the stuff alot to figure it out. This time (many many hours for me) had absolutely no learning-input and it was very very annoying. I doupted many times if i would finish the course...

автор: Henning L

Jan 12, 2017

I felt like the test-candidate for a new course. While the course-work and the presentations itsself were excellent, the "homework" was a real pain as very often the Auto-grader didn't work and it took me hours to get a project which was correct, to be accepted as the right solution. Cannot recommend it to be honest unless they improve their systems. Also it was said that the other course specialization start soon but it seems they don't and I paid for the full package....

автор: Abid-Ul K

May 07, 2020

The course assignment was very hard—maximum time I didn't have any clue what I was supposed to do. The course instructor was not up to my expectation. I didn't understand what he was trying to teach me. The pandas version in this course was ancient, which Showed exception most of the time with the functions. I wouldn't suggest anyone take this course if really wants to learn anything. For a newbie like me in Python, I had to go back and forth to Stackoverflow now and then.

автор: Omar M

Mar 29, 2020

I couldn't get through the class. The problem sets bore no relation to the lectures. I understand that the point of that is so that you teach yourself, which is more "real world" but in this type of work there are multiple ways to solve a problem, and if we never see the right (optimal) answer, then it's very possible that what we came up with on our own is a super inefficient way to do it. I think the course needs to get the lectures a little closer to the problem sets.

автор: Curtis J G

Aug 03, 2019

The videos were fast, but informative. The exercises were nothing like the videos, I had to accomplish several hours of self taught learning. If the certification did not look good on a resume or linkedin profile, I could've accomplished the same outcome with just hours of reading stack overflow, watching youtube videos, and skyping with other students in my masters cohort. Would like to see the exercises in the same realm of difficulty as the tutorials.

автор: D R

Dec 09, 2016

The lectures and explanations need more clarity and better instruction quality. The assignment questions were often nebulous. This resulted in lots of time wasted with the grader. The discussion forums were the best part of this class. I'd encourage the course instructors to take a look at the University of Washington's Machine Learning class. Stylistically, pedagogically and content-wise - that's a much, much better Data Science class.

автор: woody

May 06, 2020

The pace is far too fast. I can't see anyone managing with this unless they are already somewhat familiar with the content. Assignments and quizzes are extremely difficult. When learning it is nice to have at least some easier questions that allow you to practice implementing what has just been covered. In this course it felt like all questions required you to link together all aspects of what had been covered so far in complex ways.

автор: Michael S

Apr 27, 2020

The auto-grader in this class SUCKS. It runs an outdated version of Pandas from 2016. Some of the lecture content also includes deprecated functions. The course content and auto-grader both need to be updated to comply with Pandas v1.0.x. It is EXTREMELY frustrating to spend hours getting code to run properly on my machine, only to upload it to the course site and have the auto-grader tell me it's incorrect or unexecutable.

автор: Mohammad

Jul 20, 2018

It does not matter if you have intermediate python level of experience. You should not go through the material so fast and not explain properly what the specific code does. I understand that we should seek outside resources if we don't understand something but thats not an excuse for providing fast answers to what a code does and not provide explanations to specific code. All I saw in this introduction was fast typing lol.

автор: Neelkanth S M

May 27, 2020

The course content, which includes tutorials and assignments, is exception for beginners to hone their skills in python data science stack (numpy, pandas and matplotlib).

However, the automated grading process, I find, is ambiguous. Here's why:

First, we are not provided with a snapshot of expected output.

Second, the feedback doesn't support debugging; as a result, test taker will make clueless trial & error attempts

автор: Daniel D

Jan 29, 2020

I agree with some reviews saying that course was mostly limited to self-learning. Videos were rushed and learning mostly limited to self-studying. Assignments descriptions were confusing and not well explained, not to mention that it takes hours to figure out why correct solution is not accepted. I'd say writing code (correctly) takes 4 hours but then you need 8 hours to figure out why your answer is not accepted.

автор: Kertész J

Sep 10, 2017

I have previous programming experience, sill I find the course is very challenging for the following reasons:

- course videos are very short (40mins per week), partly related to the required assignments, not covering all topics

- you need to spend most of your time (for me 10-15 hours per week) googling and reading Stackoverflow, and you might pick up a solution which is not appropiate for your current issue

автор: Ted H

Jan 09, 2017

The assignments were tough and they really tested your knowledge of python. That being said, the lectures were absolutely useless. I spent 90% of my time trying to figure out python through stack overflow. The jupyter platform is also very frustrating. For whatever reason, error messages kept coming up as I was trying to complete the assignments. At one point, I lost all my work because of this error.

автор: Muhammad H

Jun 04, 2018

Lectures aren't helpful. Assignments are challenging which is great but there is a difference between challenging students to make them learn more or to challenge them to such extent without providing enough resources that they go weary of the material. It is important to understand that students take courses generally to learn new material, not to revise what they have already learned or forgotten.

автор: Stephen F

Jul 25, 2017

The content is really good, but their explanation of the topics is insanely terse; by both the professor and his graduate student. I had such high hopes for this class. I am personally able to follow the content because I have experience using pandas and only using this class as a easy way to fill gaps in my knowledge, but to the uninitiated their coverage would confuse a otherwise simple tool.

автор: K G P

Apr 12, 2020

The course is quite tough and is not really beginner friendly to someone who is seeking to start learning about python or data science. It's just that it is on another level. Hard to grasp onto the concepts. The assignments also are very difficult for a beginner. All in all I don't mean to be negative but this really isn't an introduction to data science course, it is on a very advanced level.