Chevron Left
返回到 Python for Data Science and AI

学生对 IBM 提供的 Python for Data Science and AI 的评价和反馈

4.6
19,017 个评分
2,964 条评论

课程概述

Kickstart your learning of Python for data science, as well as programming in general, with this beginner-friendly introduction to Python. Python is one of the world’s most popular programming languages, and there has never been greater demand for professionals with the ability to apply Python fundamentals to drive business solutions across industries. This course will take you from zero to programming in Python in a matter of hours—no prior programming experience necessary! You will learn Python fundamentals, including data structures and data analysis, complete hands-on exercises throughout the course modules, and create a final project to demonstrate your new skills. By the end of this course, you’ll feel comfortable creating basic programs, working with data, and solving real-world problems in Python. You’ll gain a strong foundation for more advanced learning in the field, and develop skills to help advance your career. This course can be applied to multiple Specialization or Professional Certificate programs. Completing this course will count towards your learning in any of the following programs: IBM Applied AI Professional Certificate Applied Data Science Specialization IBM Data Science Professional Certificate Upon completion of any of the above programs, in addition to earning a Specialization completion certificate from Coursera, you’ll also receive a digital badge from IBM recognizing your expertise in the field....

热门审阅

HM

Nov 18, 2019

it becomes easier wand clearer when one gets to complete the assignments as to how to utilize what has been learned. Practical work is a great way to learn, which was a fundamental part of the course.

MA

May 17, 2020

The syllabus of the course takes you in a roller-coaster ride.\n\nFrom basic level to advance level and you won't feel any trouble nor hesitate a bit.\n\nIt's easy, it's vast, and it's really usefull.

筛选依据:

2851 - Python for Data Science and AI 的 2875 个评论(共 2,932 个)

创建者 Ritayan G

Jun 09, 2020

Good for basics. I was expecting something else.

创建者 KARTHIK S

Sep 13, 2019

There is no deep contents for AI in this course.

创建者 Rudy S

Jun 25, 2018

Lots of typos in labs, which are not graded.

创建者 Larry P

Mar 02, 2020

so fast for a beginner to understand

创建者 Michel R

Apr 30, 2020

Exercise a little bit disappointing

创建者 Liuyang F

May 31, 2019

the lab is not clear and missing

创建者 Davide B

May 17, 2019

to many time spent on IBM Watson

创建者 MICHAEL K M

Apr 22, 2020

Very confusing final assignment

创建者 Saumya G

May 26, 2019

Not very user friendly

创建者 Mariano J G C

Jul 20, 2020

poor instructing

创建者 prattya d

Aug 03, 2018

robotic teaching

创建者 Yuhuan Z

Jan 30, 2020

Too simple

创建者 Kevin F

Jan 24, 2020

Very basic

创建者 Yuanjia Y

Dec 30, 2019

too easy

创建者 Hakki K

Jul 09, 2020

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

创建者 Aleksey A

Dec 09, 2019

Lots of mistakes and imprecisions. In case of technical issues, staff will leave you alone with your problem after one formal and meaningless reply. The staff does not comment more than once on a topic, even if the issue is not resolved. Get ready to work through your problems with the help of a chatbot, that is in a beta development stage.

You have to deal with Watson studio in this course. Oh, this is such a pain... I couldn't even create a new project there dew to technical issues. After getting in a dead end with Coursera stuff I tried to use IBM support and that was so fun, just check it out:

reply1:

"Hello Alexey

blah blah blah

Regards Raino Soikkeli IBM Watson Services Support"

solution provided not working

reply2:

"Hello Alexey , My name is Nigel Terry and I on following up on this ticket as my colleague Raino is off-shift at the moment.

exactly the same blah blah blah

Please confirm and I will follow up accordingly. Kind regards, Nigel "

not working again. no wonder, he gave me the same instructions the first guy did.

reply3:

"Hi Alexey, Nigel and Raino are not available at this time. I also work with the IBM Watson Studio Cloud (WSC) team. I do not have access to your services (LOL, same as previous two guys), but I can list them.

exactly the same blah blah blah"

and not working again, to no wonder.

I am thrilled to find out how many people work at IBM

创建者 Nicholas B

Jul 29, 2020

I strongly suggest that you look into other providers for learning python for data science. As has been outlined by other reviewers, this is mostly a bad ad for IBM's Watson and there is little actual instruction for actually using Python. As a background I'm a EE with a lot of hardware coding experience (Verilog as well as Perl). I completed a specialization in Python from another provider and this gave me quite a bit of help as those classes were clear, with a good progression. In addition I've now written a bit of Python for work so I have a good base. This IBM course has, at best, cursory instruction on using Python, Numpy, and Pandas. The instructions are not clear, with poor sentence structure, and terrible grammar, making it difficult to follow along. Further, Watson is a confusing mess with instructions that use a prior UI, making it tough to figure out exactly what needs to be done to set up an environment. Avoid. Just avoid. Go to UMich or JHU. Anywhere but IBM. The only thing I *did* get from this class is that I don't want to go into Data Science: living in Jupyter notebooks is miserable. But then, I would also rather build things than write reports. Your mileage may vary.

创建者 Jonathan K

Aug 13, 2020

I was very unhappy with this course. While the videos are fairly informative and useful, the course assignments are laughably easy. They barely require any thought and absolutely don't practice or reinforce any of the skills you learn - I'm pretty sure you could complete them with no prior knowledge based on the instructions alone. I learn better from doing things, not just hearing about them.

Usually, this was earn a 3 star rating from me, but the final assignment is even worse. The 'dashboard' you create is a single graph, and the rest of the final assignment is hosting the jupyter notebook on the IBM Cloud... except whoever set up the course forgot to actually upload the tutorial to do so. You can figure it out yourself, of course, but I didn't need to pay for a course to read documentation and figure out how it works on my own.

创建者 Arunjith M

Jun 17, 2019

This is the first time I am disappointed with a module in IBM Certification course. The module Python for Data Science is very poorly organized. The trainers are rushing like anything just for the sake of completing it. There are lot of confusions after listening to each and every sentences. Another big problem which I noticed is the lack of quality quiz questions. The questions are way easy that a school student can answer without any difficulty. Now comes the biggest drawback; this particular module Python for Data Science offers nothing but a display of IBM products. It has less focus on Data Science, though the course name is Python for Data Science. Sorry to give such a low rating for this course.

创建者 Alex S

Apr 22, 2020

The content is great. Instructors are clearly subject matter experts with a passion for the material. But mostly everything else? Extremely disappointing. Confusing questions asked about information irrelevant to long-term success, labs required neither thought nor creativity, and their r typos all clover the pace.

I do not say the following lightly. I learned very little from this course, and what little information I did learn is almost certainly on a thousand random blog posts I could read for free. "IBM on Coursera" led me to expect an extremely high level of quality, one I long to see met at a later date. Right now, however, that date seems nowhere in sight. Please rise to the occasion.

创建者 Roberta B

May 02, 2020

I just want to say one thing: there is nothing, nothing of AI in this course.

Just some Python snippets for babies. Are you kidding me ?

Sorry, but I am very disappointend. This course is related to data science, you can't put

the very basics of Python here, it is like going back, and not ahead.

If Python is necessary, please specify it in the "Prerequisites", but stop making fun of the people who simply wants to learn and study sofisticated technologies.

** Artificial Intelligence.... You call "Artificial Intelligence" making a dataframe from a file csv ?

Are you serious ? **

The worst and fake course I've ever took here in Coursera.

F.A.K.E. Course.

创建者 Maryna M

Oct 08, 2020

I have no idea how 2+2 suddenly got to sin, cos and other complex functions. The week tests are laughabale comparing to what the final assessment is. The course is not poorly structured but weeks 3 and 4 lack consistent practical tasks. I did MySQL course previously and it actually provided you with a chance to practice step by step. Here you feel like being thrown into a swimming pool without knowing how to swim. To make it clear - do not waste your time, watch youtube or pick up a different course.

创建者 Ariel C

Jun 05, 2019

You learn some basic python coding skills. The pain point is the peer graded project where you have to sign up for an IBM cloud account and Watson Studio account. They are irrelevant to python skills. The instructions (how to set up the connections, buckets, servers, credentials, keys, etc.) are lacking clarity and have sizable gaps. I spent hours struggling with cloud which did not add value in gaining python skills. I would not recommend this course to people who want to learn python.

创建者 Samual F H J

Dec 31, 2019

lots of errors, can't believe they want to charge for this. Requires signing up with IBM Watson for several exercises which I refuse to do (more than a little advertising going on here). I'm pursuing my programming objectives by downloading Jupyter Notebook tutorials. These are more convenient and of higher quality. After completing the Stanford ML course, this particular tutorial came as a real disappointment. IBM can do better.

创建者 Maria N L

Jun 11, 2019

I speak for almost everyone who's taken this course in saying that the final assignment was the absolute worst. It's terrible not because the concept was difficult (it's not at all), but because the assignment instructions were so convoluted that it took me at least two hours to complete even just setup. The assignment itself should not take more than 30 minutes. Please update the instructions for the final assignment. Please.