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学生对 IBM 技能网络 提供的 使用 Python 进行机器学习 的评价和反馈

12,859 个评分


This course dives into the basics of machine learning using an approachable, and well-known programming language, Python. In this course, we will be reviewing two main components: First, you will be learning about the purpose of Machine Learning and where it applies to the real world. Second, you will get a general overview of Machine Learning topics such as supervised vs unsupervised learning, model evaluation, and Machine Learning algorithms. In this course, you practice with real-life examples of Machine learning and see how it affects society in ways you may not have guessed! By just putting in a few hours a week for the next few weeks, this is what you’ll get. 1) New skills to add to your resume, such as regression, classification, clustering, sci-kit learn and SciPy 2) New projects that you can add to your portfolio, including cancer detection, predicting economic trends, predicting customer churn, recommendation engines, and many more. 3) And a certificate in machine learning to prove your competency, and share it anywhere you like online or offline, such as LinkedIn profiles and social media. If you choose to take this course and earn the Coursera course certificate, you will also earn an IBM digital badge upon successful completion of the course....



Feb 6, 2019

The course was highly informative and very well presented. It was very easier to follow. Many complicated concepts were clearly explained. It improved my confidence with respect to programming skills.


Oct 8, 2020

I'm extremely excited with what I have learnt so far. As a newbie in Machine Learning, the exposure gained will serve as the much needed foundation to delve into its application to real life problems.


26 - 使用 Python 进行机器学习 的 50 个评论(共 2,238 个)

创建者 Derek A

Jun 2, 2019

Was a 3 stars until final week. Stuff is explained and is written poorly. I honestly felt like I got shammed by last week. I had to look online at other YouTube videos and forums and I am just not happy with what I got out of this course. I will be doing Andrew NG's course on YouTube now..

创建者 Andrew K J

Jul 9, 2019

This was a very informative course. The videos provided a good background on the concepts and I found the labs especially helpful for learning to implement Python code for each technique covered.

创建者 Arijit G

Jun 24, 2019

one of the best shot term course in Mechine Learning

创建者 Dhruv K

Apr 11, 2020

Could have explained a little coding in videos instead of putting it in labs...


Oct 23, 2018

I am thoroughly enjoying the course. The codes written are the shortest possible codes but the narrations are just fabulous to comprehend and remember. I need more practice to write the codes correctly by my own but my fundas are all cleared and I know exactly why am I doing the next step.

创建者 Fatai O

Oct 9, 2020

I'm extremely excited with what I have learnt so far. As a newbie in Machine Learning, the exposure gained will serve as the much needed foundation to delve into its application to real life problems.

创建者 Jonathan L

Dec 6, 2018

I am happy to have this online education, I drop out my nuclear engineering degree, I am happy to learn practical things with future... I work for IBM also...but I want to become a data scientis

创建者 Imran R

Feb 3, 2019

Thank You Mr. Saeed Aghabozorgi for designing and delivering such a immersive course, I found lot of pointers and specific details associated with many interesting topics in Machine Learning.

创建者 Suresh S

Apr 17, 2020

I liked it very much and was able to clearly understand the usage in programming language with ML related libraries. Thanks to IBM friends and Coursera for providing the expertise and the platform.

创建者 Juan V P

May 8, 2019

Very interesting subject, and very well explained. Even if I miss more concrete code examples, I can always look for it, the theory and the logic behind it was explained flawlessly.

创建者 Sumedh K

Oct 18, 2019

The course is amazing. It provides with Mathematical equations for all the algorithms taught and coding is done with real world cases as well.

创建者 Bjørn I A

Jun 25, 2019

I liked this course. Nice to see how math learnt in theory years ago can be used in practice in some of the models.

创建者 asher b

Dec 6, 2018

puts a lot of the previous courses all together. challenging, but doable.

创建者 Vivek R

Mar 20, 2020


创建者 Chetan M

Mar 21, 2020

The course was well described. Thanks Man !!

创建者 Nathan E

Apr 16, 2020

The course covered quite a wide range of topics in Machine Learning, which was great. However, the sample code was not commented as much as I would have liked, at least for visualizations of the results of the machine learning algorithms, so I don't feel very confident that I would be able to replicate many of those on my own. The in-lesson exercises mostly consisted of following examples arranged by the instructor, there weren't many opportunities to challenge yourself with exercises and get feedback.

创建者 Serdar M

Dec 10, 2018

labs are not easy to understand

创建者 James F

May 3, 2020

Using IBM Watson Studio 'Lite' plan is a huge pain in the ___. I had to use 4 different emails to start from scratch to submit the notebooks for peer review. The course's instructions don't mimic the actual site - sometimes I wonder if they're referencing the same site in the instructions. You can learn this information elsewhere without added the headache.

创建者 Aditya V R

Jun 30, 2020

Too much maths. Those who didnt have any background in math, it is very difficult for them to pass this course. They wont explain the code. They explain only the concept. The code is very difficult to understand. Very complex code. I many times thought of giving up. Finally completed with luck and hardwork.

创建者 Pierre-Antoine M

Mar 2, 2020

That course is a joke.

Videos are less informative than wikipédia, hands-on labs have praticaly no exercises and are really shallows.

Finally the Peer-Graded Assignment is made even more difficult, because not having correct lessons and hands-on is not bad enough, by being really bad worded

创建者 kyleg907

Apr 30, 2020

Its interesting given the title the lectures never mention Python or show code ; ) That's left to the ungraded exercises. I liked it this way. Getting the good background on the algorithms independent of language or library, and then applying that in the labs is effective. I will refer back to this class as I continue learning about ML.

I had trouble getting my final project graded - but realized I hadn't shared my project correctly (at first didn't share code cells), and had to save a `version` of the notebook so my edits would be available to the other students to be graded. Leave yourself extra time for your peers to review your project, and check that the shared link to your notebook shows what you expect. You don't need to post in the forum to get your project graded - lots of students were doing that..

创建者 Gilbert V

Feb 7, 2020

Course is largely a scam. At the end you have to have a peer reviewed project that will prevent you from finishing the course if other people do not grade your project. You can have a high enough overall grade that you could get a 0 on the final and still pass and still be out of luck if people decide to not help with grading, which is exactly what happened to me. Do not waste your time and money if you want to be at the mercy of other people.

创建者 Stephen P

Mar 10, 2019

Lots to learn in this class! Week 3 was definitely heavy and challenging in the middle of it, but the course really builds up well and makes sense by the end of it and I understand why those topics were combined as they were. I found the labs most helpful when they included # hashtag explanations/documentations when introducing new code to explain the different parameters and reasons for using them, or if establishing parameters in the code with explanatory definitions/names to guide the user through new operations. In the very last lab, I think they included a link to the pandas API reference page with that specific new operation. I found that really helpful because I had already been going to the pandas page to learn more about other new operations as they were introduced in previous labs.

创建者 Caterina F

Feb 27, 2020

Machine Learning with Python is highly informative and very well presented. It wasn't easy, it requires a good understanding of math. Complex concepts of machine learning algorithms are explained clearly.

After the course, you will have a solid awareness of how machine learning is applied to the real world and how to use the skills like, sci-kit learn and SciPy from the Python language.

Excellent support of the labs and the Notebooks provided. The final project will be a challenge for what we have learned.

I strongly recommend this course.

创建者 Jeremiah J

Feb 11, 2020

This was MILES ahead of the last IBM course I took (Building AI Application with Watson APIs). The part that I thought isn't great is the use of other students to "grade" the final project. I definitely understand that you wasn't have hundreds taking the courses at any one time, so that might be the best way to get through the projects. I hope that there is some sort of feedback loop so that if a project was failed by a classmate more than twice, the next submission goes to a REAL staff member for review. Thanks for the great course.