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Kursteilnehmer-Bewertung und -Feedback für Introduction to Data Science in Python von University of Michigan

4.5
12,025 Bewertungen
2,792 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

AU

Dec 10, 2017

Wow, this was amazing. Learned a lot (mostly thanks to stack overflow) but the course also opened my eyes to all the possibilities available out there and I feel like i'm only scratching the surface!

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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2651 - 2675 von 2,729 Bewertungen für Introduction to Data Science in Python

von zhangzhongquan

Nov 13, 2017

it's not very good

von Jeroen D

Apr 23, 2018

More or less my copy from an earlier review,

I was really excited about the this course, and was really let down. This course is really, really poorly done. I would not waste time and money on this course when there are much better options out there. I feel like I've gotten little in return for my time and money.

First, as several other students have noted, the timeframe for assignments is really unrealistic, taking much longer than projected (at least for me, and several other students). This is not acceptable when Coursera bills by the month. Coursera needs to provide a better assessment of the time commitments for the class. I took another datasciense course prior to this one (my employer wants a certificate) but still the assignments were tough, and I found it really dissappointing that I spend a lot of time solving inconsistencies in the assignments. I believe American students are in advantage here because of the Geo-American orientated datasets.

Second, the teaching is horrific. The professor is not engaging at all, but simply mechanically reads lines which often sound straight out of a user manual. The point of online videos is not to turn books into audio files- it’s to have a human talk/reason through problems with you. The teacher of the course should discuss the material, not recite a manual. In addition, the little amount of material is presented far too quickly, Also great emphasis is put on the discussion groups (which turns out to be just responded by the moderators, volunteers). In absence of a proper syllabus students are directed to Stack Overflow, a sign of the courses' weakness.

Third, the title of this course is a misnomer: an introduction to data science would provide an overview of the tools, techniques and scope of the field. An extremely detailed introduction to Pandas, which is essentially what most of this course is, is useful if well executed (which it is not here), but it is not an introduction to data science.

A more minor complaint is the absolutely horrendous choice of the background. Showing different permutations of lifeless office drones is not exactly inspiring material for aspiring data scientists, even if this the reality of office life- it’s distracting at best, and at worst, deeply disparaging. Why not have just a plain colored background? Or anything else?

The only positive thing besides some of the misleading assignemnts are the rest of the assignments. In general I had fun solving them, and althoug I've had my share of Jupyter Notebook and Grader's issues I was able to complete the course. I will not reconsider any online course from Michigan University again.

von Chenfeng L

Nov 14, 2016

Good course materials and the assignment itself is pretty good, but the grader is buggy, not informative and wasted a lot of my time.

von Isaac D

Jun 07, 2018

When ones motivation for taking a course switches from learning as much as possible to wanting to finish the course in order to leave a review warning others not to take the course until the numerous structural issues with the course are resolved then something has gone very wrong. The course materials are okay for an intermediate course. Just 'okay'. Not good. Not great. Certainly a substantial step down from the wonderful 'Python for Everybody' courses which, by the way, are inadequate preparation for this course despite the Dr. Brooks' claim. That said, the main issue with this course lies in its incredibly vague and poorly thought out assignments. If you are actually decent with Python you will, in all likelihood, spend more time fighting with the Jupyter notebooks and auto-grader than you will actually completing the assignments. If you're newer to programming expect to spend at least five times as much time on each assignment as the estimated completion time suggests. Also, good luck if you actually need help, as this course has the most aggressive enforcement of Coursera's honor code that I have seen on this site which means that you are SOL if you need help on a problem. In short, I would recommend that no one take this course until the numerous issues with it are provably fixed.

von Manuel M

Feb 26, 2018

For some reason the format in which the lectures are organized lack a lot of tact and seem to be made with no pedagogic consideration whatsoever.

von Shahar S S

Nov 19, 2017

The lectures are much too concise, practice is scarce which renders an overall frustrating experience.

von Pranam

Jun 13, 2018

Too fast and need to break the content even smaller with frequent practise assignment and graded quiz, just make it like python for everybody specialization

von Carl G

Apr 10, 2018

Not my style of course. Lectures is a mostly just a list of code snippets without any slides. Instead there is a background of 2 people just staring at their screens the whole time. Does not inspire one to enjoy Data Science as a field. Prefer a narrative explaining why and how with practical tips thrown in. Learning to code is more than just syntax. Good examples are the first chapter in Think Stats by Allen Downey and Andrew Ng's Machine Learning course. In this course the assignments took quite a bit of time to complete since lecture code snippets not very useful. Had to self-learn from web to complete assignments. Also took extra time by some trial and error to get right format of results. A more productive approach was assignments in A

von cheting c

Mar 02, 2018

Very unresponsible professor. No passion at all!!!!! Did not explain the fundamental concept well. As a result, I do not think I have a deep understangin at all. I spend most my time google in order to finish my assignments.

I give him the second star only because I the way he designed those challenging assignments. He should include some skill needed to finish the assignments.

von Sayali B

Jun 20, 2018

The questions are very hard and not covered in training

von Nishant B

Jun 13, 2018

Very fast paced and concepts explanation was not upto the mark

von Varun D P

Apr 18, 2018

Course content is very scarce as compared to what is asked in assignments. No explanation is give to what function does and what should be its inputs and outputs. Unlike Professor chuck's course this course is very tough and not at all an introductory course. Assignments take 4x more time than mentioned in course content. Overall a very heavy work for student to go through other online materials to understand what each function does. It feels like I have learnt alot from other websites than in this course. What is the point in taking a course if I have to go through other materials from some other website? Please change course content, make videos more elaborative, reduce the difficulty of assignments.

von Hussain M

May 13, 2019

The course is neither for beginner nor for intermediate level students. Course is sort of tutorial where how is well explained, what is some time explained but why is always missing.

von Stefano M

May 27, 2019

The lessons were too fast and dense

von Zayd A

May 28, 2019

I had done "Python for Everybody" from Charles Severance which I had found excellent, with the instructor being passionate and the pace being just about right. I had assumed it would be similar for "Introduction to Data Science in Python", but that wasn't case. The delivery of the course is at a very very fast pace, you don't even have time to stop and absorb the functions and methods that you are supposed to learn. The instructor and the research assistant will list the functions and methods one after the other without pausing. The assignment is then extremely hard with no resemblance to the material in the course (I couldn't do it even after having reviewed the videos). After holding on for the first 2 weeks (it's a very useful topic after all), I gave up and decided to learn from the "learning the Pandas library book", which is a very good summary of the main Pandas functions and methods (and which was recommended by Dr Christopher Brooks), and I was able to follow it very easily.

von Dirk

May 28, 2019

Do you want all the fun sucked out of Data Science! This course's autograder will do it for you!

von Paul J

May 28, 2019

I realize Python is prerequisite, but there is very little Python instruction. At a minimum, it would have been very helpful if the professors explained the syntax of the python examples that are shown during lectures.

von See H L

May 29, 2019

One thing I dislike a lot about this Specialization is that it forces you to work through their structured weekly materials rigidly. It does not allow you from working on Week 2 and Week 3 courseworks when you have finished Week 1 materials which I think it is just a way for the course owner to make more money from you. Their excuse is that they allow 'other students' to mark your work to promote interactions between students but I think this makes no sense as not people who takes these courses have a uniformed fixed number of hours each week. The whole point of studying an online course is to be flexible with the hours you put in, which this isnt.

von Shikhar S

Jun 02, 2019

The content of teaching in videos is a way too less than the level of asssignments .I had to make a lot of efforts on my own to understand the things.

von Abhishek c

Jun 07, 2019

The learning is very fast paced.It seems like the trainer is in hurry.He just touched some keyword without going into details.

von Dario M

Jun 19, 2019

I didn’t like how the subjects are explained, and i feel the grading system is not good at all. It would be better if assignments were graded by peers.

von Muhammad B S

Jun 19, 2019

I decided to take this course after having a great experience with "Python 3 Programming Specialization". I was expecting the same kind of experience from this course but the lectures are pretty fast. The instructor seems to rush through the lectures and keeps on recommending using StackOverflow for any questions so I finally decided to unenroll myself from this course. I recommend you to install Jupyter notebook, buy "Python for data analysis" by Wes McKinney and follow along with all the book exercises. You will have a way better experience learning data analysis than this course.

von KIRILL B

Jun 20, 2019

The aim of the course and general guidelines are fine.

BUT!!!

It s aweful how the explanation s given.

Main idea of all videos is: here s a function, here s another one, also you can use this function.

Now you 'go girl' try to glue all the puzzles together by yourself.

It feels like professor was just rushing to record videos and get back to his work which gives money.

Never-the-less i did learn A LOT from this course which i couldnt do by myself since as i said GENERALLY GUIDELINES are OK.

PS. The WEEK4 last assignment was the main problem since i had to watch about 6-8 hours of statistics to truly feel and understand VAR, STD, TTEST.

von pouya g

Jul 01, 2019

the corrector system was very bad and i m not undrestod my mistake

von Marcin W

Jul 02, 2019

It would be a very nice course... if this guy was actually teaching and not explaining the basics and expecting people just to search online of the remaining 90%