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學生對 IBM 技能网络 提供的 使用 Python 进行数据分析 的評價和反饋

4.7
16,210 個評分

課程概述

Analyzing data with Python is an essential skill for Data Scientists and Data Analysts. This course will take you from the basics of data analysis with Python to building and evaluating data models. Topics covered include: - collecting and importing data - cleaning, preparing & formatting data - data frame manipulation - summarizing data - building machine learning regression models - model refinement - creating data pipelines You will learn how to import data from multiple sources, clean and wrangle data, perform exploratory data analysis (EDA), and create meaningful data visualizations. You will then predict future trends from data by developing linear, multiple, polynomial regression models & pipelines and learn how to evaluate them. In addition to video lectures you will learn and practice using hands-on labs and projects. You will work with several open source Python libraries, including Pandas and Numpy to load, manipulate, analyze, and visualize cool datasets. You will also work with scipy and scikit-learn, to build machine learning models and make predictions. If you choose to take this course and earn the Coursera course certificate, you will also earn an IBM digital badge....

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RP

2019年4月19日

perfect for beginner level. all the concepts with code and parameter wise have been explained excellently. overall best course in making anyone eager to learn from basics to handle advances with ease.

SC

2020年5月5日

I started this course without any knowledge on Data Analysis with Python, and by the end of the course I was able to understand the basics of Data Analysis, usage of different libraries and functions.

篩選依據:

26 - 使用 Python 进行数据分析 的 50 個評論(共 2,449 個)

創建者 Sobhan A

2020年5月6日

Low quality.

Do not recommend this course at all.

Boring teaching method.

Full of errors.

No IT support for problems.

創建者 Titans P

2020年8月17日

worst ever

the greatest thing i have learned here is patience and searching online

創建者 HIMANSHU S

2020年7月30日

perfect for beginner level. all the concepts with code and parameter wise have been explained excellently.overall best course in making anyone eager to learn from basics to handle advances with ease.

創建者 Usman A

2020年7月29日

AN excellent course. Hands-on training on the cloud makes an individual really involved. So far the best online course I have ever taken, and I have learned Python programming a lot from this course.

創建者 Oana M

2019年5月22日

Thank you so much! - Oana

創建者 Aditya J

2019年5月18日

None

創建者 William B L

2019年3月20日

The techniques, methodologies, and tools presented here are essential parts of the data analysts tool box. The coverage was, in general, well done. I am glad I took this class, and look forward to the next.

That said, there were problems:

1) The meta parameter, Alfa (or is is Alpha) is never explained, except that it helps. To be useful, the student needs to know a bit more. Also, the spelling should be consistent between the training texts and the lab.

2) The lab needs maintenance to keep up with changes in the Python packages. I received warnings about using deprecated functions and values.

3) The text needs grammar/spelling checking, for example, the end of the course exam is labeled "Quizz"

創建者 Karen B

2019年5月25日

Does an excellent job in providing the Python commands needed to do data analysis, along with some descriptions of what the steps actually involve. Has quite a few typos and minor issues -- looks a little sloppy.

創建者 Hakki K

2020年7月9日

Hi,

I completed entire program and received the Professional Certificate. On the Coursera link of my certificate "3 weeks of study, 2-3 hours/week average per course" is written. This information is not correct at all, it takes approximately 3 times of that time on average! I informed Coursera about it but no correction was made. It should be corrected with "it takes approximately 19 hours study per course" or "Approx. 10 months to complete Suggested 4 hours/week for the Professional Certificate".

Here is the approximate duration for each course can be found one by one clicking the webpages of the courses in the professional certificate webpage: (*)

Course 1: approximately 9 hours to complete

Course 2: approximately 16 hours to complete

Course 3: approximately 9 hours to complete

Course 4: approximately 22 hours to complete

Course 5: approximately 14 hours to complete

Course 6: approximately 16 hours to complete

Course 7: approximately 16 hours to complete

Course 8: approximately 20 hours to complete

Course 9: approximately 47 hours to complete

This makes in total approximately 169 hours to complete the Professional Certificate. As there are 9 courses, each course takes approximately 19 hours (=169/9) to complete.

(*): https://www.coursera.org/professional-certificates/ibm-data-science?utm_source=gg&utm_medium=sem&campaignid=1876641588&utm_content=10-IBM-Data-Science-US&adgroupid=70740725700&device=c&keyword=ibm%20data%20science%20professional%20certificate%20coursera&matchtype=b&network=g&devicemodel=&adpostion=&creativeid=347453133242&hide_mobile_promo&gclid=Cj0KCQjw0Mb3BRCaARIsAPSNGpWPrZDik6-Ne30To7vg20jGReHOKi4AbvstRfSbFxqA-6ZMrPn1gDAaAiMGEALw_wcB

創建者 Vera

2021年4月7日

The general course content was okay. Unfortunately I didn't learn too much about Python and Data Analysis for Data Scientists. This was due to the following reasons:

1) a lot of interaction with not working IBM infrastructure. It took me around 3x as much time to get required things working on IBM cloud and IBM Watson compared to the time spent for actual assessments. It is annoying if it's getting that obvious that IBM wants to use the course to promote own products. This is sad as we all already pay for the course...

2) There occurred quiet some arrows in the labs which even after months (according to the discussion) have to been corrected.

3) The amount of hands-on training in the notebooks/labs was really small. It was not a lot one had to program on their own and the parts which had to be programmed were only an exact copy of what was already done before. Even the final assessment did not really contain a real task.

4) Many concepts weren't explained in depth. The explanations just stayed very superficial. Some concepts like fit()/fit_transform() which appeared in the labs weren't explained at all in the videos or in the labs. This led to a lot of confusion as could be seen in the discussion threads.

As we all pay for this course please increase the amount of actually explaining concepts in depth and the amount of real in depth hands-on training and reduce the parts on IBM Watson and other such stuff. Thanks a lot!

創建者 Matthew A

2021年4月13日

During the 4th week of the course, lots of important information and explanations are over summarized and in some cases skipped over. Learning tools outside of what is provided in the course or a decent understanding statistics is required in order to be successful in this course.

創建者 Shashank S C

2020年5月6日

I started this course without any knowledge on Data Analysis with Python, and by the end of the course I was able to understand the basics of Data Analysis, usage of different libraries and functions.

創建者 Srikantha R

2021年3月23日

Definitely NOT for beginners. No proper explanation of basic concepts. The instructor assumes that all students knows everything and they just explaining python formulas without giving basic concepts on data analysis or statistics. If one has to complete this course only for the sake of certification, one must get the basics right with free online materials and then only can enroll for this so called 'BEGINNER' course to get certificate. I am cancelling my subscription and can learn on my own with free and better online materials

創建者 Jennifer R

2020年3月31日

The topic is very interesting, but the execution was poor. Code and numbers were just being read at me, instead of focusing the recorded lectures on teaching concepts and troubleshooting, and leave the code to be read by myself in the labs. Also, the quizzes along the way were nearly useless: only two questions, a "pass with at least 50%", and the questions asked were very superficial. This is the most poorly executed course I have taken on Coursera so far.

創建者 Vincent L

2018年9月17日

Ton of errors, both minor and major, in the videos and the quizzes. For example, saying the a difference between two variables is significant because p > 0.05. I report them all and I've stopped counting.

Not professional at all.

創建者 Anastasiya B

2019年9月22日

Low technical quality of the course with lots of typos, errors and comletely mess in final assignment.

Low quality of material, bad structure, and you can get your certificate just by clicking shift+ enter

創建者 John K

2019年7月7日

Poorly put together course - especially the labs. Frequent misspellings, incorrect links and confusing instructions. The technical problems are a greater challenge than the course material.

創建者 Abhijit R

2019年9月6日

Course content is very poor. Not clearly explaining each & every thing in each slide. Disgusting

創建者 Saba A

2020年7月28日

The instructor does not explain the codes at all. She just rushes to finish the videos!

創建者 Ritesh C

2020年8月4日

Nothing explained in course, nor even exercise for practice any good

創建者 Ahmed B

2020年7月14日

the explanation isn't good

創建者 Shuting Z

2020年11月22日

Not well designed at all.

創建者 Uygar H

2019年3月14日

I have really learned many things in this course which are meaningful and helpful in real life. It is not just lines and numbers , it is exciting how you can apply these methods to find solutions in your real life problems. Combined with strong Python skills , you will enjoy more..Thank you

創建者 Daniel T

2019年4月9日

This was a great review of stuff math I learned in high school and college. Of course it's all easy now because it's baked into Python. We used to do it by hand and with slide rules back in the early 1970s

創建者 Firat E

2019年6月4日

It is really a good course, simple to understand and very complete. Thank you !