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Bewertung und Feedback des Lernenden für Introduction to Data Science in Python von University of Michigan

4.5
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25,768 Bewertungen
5,734 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

YY

28. Sep. 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. Mai 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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176 - 200 von 5,687 Bewertungen für Introduction to Data Science in Python

von Claude P

3. Juli 2021

More concise coding tutorials and less "search on your own on the internet" needed. It is great to get to know the online community and the course needs more coding example directly relat to exams.

von Tom M

29. Dez. 2018

A lot of self directed learning, bordering on excessive. Sometimes it takes some investigation to figure out why the autograder did not pass you. Overall, I felt I learned a lot, much on my own.

von Pamela T

2. Feb. 2019

This is a great overview for python, but the materials/videos/slides are very elementary compared to the sophistication of the homework. Required many more hours than the estimates.

von Saadman S

16. Sep. 2020

Statistical stuffs are really tough, it's hard to understand without any background also the assignment materials should be discussed more, they should be included in the course.

von Alice

20. Dez. 2020

Recent changes to the course made it a lot worse! Longer, less concise videos, difficult to find course notes, fewer mid-video working problems, and quizzes are pointless.

von Bárbara C G

2. Feb. 2021

The videos are ok. The assignments are extremelly centered in data cleansing. The debate in forums is very helpful, and the course staff answers regularly.

von Ryan V

10. Feb. 2021

Interesting material, poor instruction and not enough practice for things to sink in. Have to basically teach yourself everything through google searches.

von Colleen K

21. Sep. 2018

I learned a lot by doing assignments, but the course materials are not helpful. Stackflow and Python documents guide me much more than the course itself.

von Mohammed A H

26. Sep. 2020

During the course, the instructor was presenting with a background contains moving people which caused a big distraction to me.

von Sudharshan C

28. Okt. 2020

The assignments can be better structured. I found it tough to navigate and perform operations

von Sai S

23. Dez. 2020

Needs to be packaged in more interesting way..felt course contents and presentation vague

von Khairul A

10. Aug. 2020

Too fast explanation

von Matteo S

3. Nov. 2021

Issues:

1. The lectures are a chore to sit through. Dry, slow, and unorganized. The lecture on pivot tables was not used in any assignment. So why have it?

2. Assignments. Ooof. Lets break this down.

a. Autograder is poor. Aside from the oddities that just break it sometimes, the hidden test feedback is lacking. If my answer is off at the 15th decimal point because my dataframe is 226 rows and not 227. I need another assert and feedback telling me that. Instead of a lesson on logic a lot of these problems became frustrating cases of github searching for other peoples passing code and then working backwards

b. Assignments felt rushed. Each assignment had poorly written questions that frequently popped up in the forums asking for clarification. The assignments themselves had odd jumps in difficulty and assumptions. Some would build upon the lectures but other times they would jump and assume that we would figure out the middle. Oftentimes we did, but imperfectly, and the assignments penalized us for that imperfection. For example, if question says clean the data and we do using one of a dozen different ways why are we penalize if we have 224 clean rows, and the answer requires 227. If that level of end accuracy is required, then we need more guidance to achieve exactly that.

3. Forums. Useless. Filled with garbage, and the useful ones are unstructured mess. For one, the autograders output is small grey typwriter text which is undecipherable and the TAs always wanted it posted. This lead to long chains of code blocks and one line responses. I also think the TAs emphasis on posting zero code is wrong. The entire web is built on Stack Overflow, so why not allow code snippets in the forum?

von Brian L

3. Okt. 2020

TLDR - poor design of class makes for a bad experience and wasted time.

Longer - There is a disjunct between what is covered in the videos and what is tested in the assignments, and there are problems with the assignments (the autograder and the extremely dated pandas version supported) . The videos function as a partial reference guide, which is only very loosely what is tested in the assignments. If I didn't pay for the class, I would see value in the assignments themselves. Since I did pay for the class, I expect more value from the videos. For the 3rd and 4th weeks I proceeded more quickly by relying much more heavily on stack overflow and pandas documentation, to the point of sometimes ignoring the videos entirely. As-is the gaps between videos and assignments, on the one hand, and ongoing difficulty of knowing how to navigate the black box which is the autograder (using an outdated version of pandas) are shunted to the forums and other students, volunteers, and assistants. While the forum is helpful (always start there with the assignments, so you will waste less time on poorly designed / assessed questions!), it is poor pedagogy and a bad experience to offload bad course design onto it.

von Lucas C

1. Sep. 2019

Overall: I felt this course was useful but pretty time-consuming. The course had relatively limited taught material and relied a lot on searching & self-studying. If you have a fair amount of time it is a good choice.

Pros: You learn through doing assignments which are well supported by mentors/community. Also, you get used to studying through googling problems and learning from websites such as Stackoverflow.

Cons: Whilst this learning method definitely had its merits, it could be quite time-consuming for someone seeking to gain introductory-level skills quickly. You could find yourself in situations where you spend hours searching for something quite elementary and could easily have been taught to you, which could be frustrating. I personally think this course could be improved by adding a bit more small quizzes for beginners to play around with the basics, before requiring them to self-learn through searches.

von Susan C

9. Feb. 2021

The lectures were essentially the instructor reading from the provided Jupyter notebooks at _very_ high speed. You can slow down the video, but then you get a weirdly artificial drone that is hard to listen to. And the lectures jump briskly from topic to topic without providing any context, or advice about writing good programs. The assignments took WAY more time than estimated because (a) there was a lot of self-learning via StackOverflow (b) the auto-grader is very very finicky. (It would have been useful to have a quick demo video showing how to approach the assignments and deal with the auto-grader).

That said, the people (TAs?) helping on the forums were very helpful. And I learned quite a bit, but mostly on my own.

von Markus Z

7. Aug. 2020

Compared to the previous course I have taken at University of Michigan the content was ok but how it was taught I didn't like. Just reading rapidly the text of the Jupyter Notebook is not enough from my point of view. Ok you can find out the stuff yourself but why take then this course and don't go directly to stack overflow.

You just get weird replies from the auto grader and search through the forum to get any idea why you didn't pass. And if you pass, you will never know if your solution was the proper way to solve this task....

von Ruibo S

4. Okt. 2020

The assignments are much more difficult than what is covered in the class. The teaching speed is too fast without enough PPT slides. The class coding demonstration is also too fast. The lecturer should either teach more in class or make the assignments easier. Assignment 3 and assignment 4 need a lot of independent studies of the functions in pandas library. If the assignments need a lot of independent studies, what is the meaning of the teaching in class?

von Daniel D

29. Jan. 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.

von Carl M

14. Nov. 2019

Poorly worded questions (that are mentioned throughout the discussion board), older version of pandas and the course resources don't help you with course. Get ready to 'learn' by looking in StackOverflow or reading the volumes upon volumes of python/pandas documentation. In other words, expect to spend 15 hours a week per week (obviously it will vary)

von Brent D

12. Aug. 2020

Lectures do not reflect what is required to complete the assignments. Much of the learning is left to independent study by the student. Assignment questions are too vague and frequently require parsing through class discussions to determine the answer the auto-grader is looking for.

von Olena K

28. März 2019

The lectures are not good. They go too quickly. They're about 5 minutes long, but you have to stop every minute or 30 seconds and rewind to understand what the instructor is saying. He just goes way too fast, and it's very frustrating. Really ruins the experience.

von Glenn

17. Feb. 2021

The teaching was sparse and assignments got very difficult very quickly. An inordinate amount of time was spent Googling to get past each step due to poor foundations. I learned more in a much shorter time from more gradual and concise YouTube tutorials.

von Yizi Z

9. Nov. 2018

There is only few minutes taught video courses each week, although the reading materials and topics are quite interesting. The learning of python coding rely heavily on your own trial and error, which you could do even without this course.

von Saurabh C

2. Sep. 2020

The level of course content and assignments is not at all similar. The course contents need to be revised, seems like the professor assumes we know everything about the topic. Also the teaching speed is extremely fast. Very Disappointed!