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Bewertung und Feedback des Lernenden für Maschinelles Lernen mit Python von IBM Skills Network

12,843 Bewertungen

Über den Kurs

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....



8. Okt. 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.


6. Feb. 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.

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1626 - 1650 von 2,234 Bewertungen für Maschinelles Lernen mit Python

von Carol L

10. Mai 2020

Creo que este curso es muy avanzado para mi. Me gustó porque el instructor explicó muy bien de donde viene y como funciona las distintas metodologias, pero a nivel de practica algunas cosas no fueron explicadas y en el projecto final fue un poco confuso iniciar aunque realmente era aplicar las practicas.

von Deleted A

1. Feb. 2022

I loved this course "Machine Learning with Python" because it's a good courses, easy to understand , good explanation, and this course have an application with python programming language directly. So, you can understand not just the theory but how to code the theory that have been taught using python.


16. Juli 2020

Material was great. Tutorial videos were great. The only improvement I would expect is on the Labs. Not only the lab environment was slow but there were certain errors in the questionnaire for final assignment for quite some time which no one seems to correct. If this is rectified, its a great course.

von Utku Ü

10. Okt. 2020

It's a good course to have some idea about ML case. A good part of the course is that, it has some brief expenations people to let them work further. Maybe not a learning course but a very good start. I do appreciate the instructors capacity to give lecture and summirize. Thank's for all the afford!

von Frank O

2. Sep. 2020

Loved the content, there needs to be more explanation about what Python code is necessary to complete the final project. In many cases I had to convert strings to integers and use plotting codes outside of examples. Please provide references to use that are necessary to complete the final project.

von Shiyang Z

3. Juni 2021

Great course for machine learning beginers. Helped me gain some general ideas about machine learning, and I'm able to conduct simple machine learning algorithm on my own after the class. Would be better if the python code has more detailed explaination, or has videos walking us through the code.

von Subikesh P S

4. Feb. 2020

The course thoroughly teaches about all the mathematical formulas and theoretical explanation in creating and predicting of data in data models. But I think if he also teaches about various python modules used for data science too, then it would have been much easier to do the assignments.

von Daniel G

26. Feb. 2020

The content is good and broad, although a little too superficial sometimes. It also provides a fair Python practice. My biggest complaint are the quizzes, that are full of bugs. Those bugs are the number one complaint in the forum, but there is very little responde from the management.

von Rafael S

20. Juli 2020

This is a really good course, where the instructor is clear, detailed when needed and practical in his examples. The only downsight is that this, as every other course of IBM Data Science program, is not designed to be a part of a full course: Often it repeats some previous concepts.


8. Apr. 2021

The course is very useful for the beginner as me. It contains a good math explanation of ML methods. The technical Python part in labs is good enough too for the beginner in Python/ Sometimes it don't correspond fully to the math part but it isn't critical. Thanks for the course!

von Edwin S

25. Mai 2020

Good course syllabus. Some improvements needed: Jupyter notebooks contain many English typo errors. The final assignment rubric uses the wrong normalization technique for the test data where test data were normalized by itself instead of training a scaler with the training data.

von Fabrizio D

20. Juni 2020

I noticed some (not critical) mistakes here and there during the video lectures and the quizzes.

Over all, a good course, but I think in order to gain a full understanding of the material one needs to look deeper into the literature. The course provides a good starting point.

von joe b

13. Okt. 2020

Working with the IBM notebook for the final assessment was a bit of a pain

And the peer assessment has no recourse, someone marked me down for something i had, i guess they didnt notice? but i dont have an easy way of getting that changed

Content is good stuff though

von Pratyush R

28. Feb. 2022

Very Good Crash Course. Concepts are explained efficiently without wasting much time on the Mathematical/Statistical stuff. Awesome Notebooks are given to code along with the concepts which is really helpful. Must learn deeper and further to become a Professional.

von Martin E

2. Apr. 2020

Content was good, but mainly classification. I was missing other aspects (like regression, deep-learning, ...). What really annoyed me a lot was the constant advertisement of the IBM infrastructure; for this course the IBM Watson thingy is largely overblown imho.

von ankit s

22. Juli 2022

Reason for giving 4 rating

1) Proper explaination of all models & its concept

2) Exercise is good ,but you need to understand the python properly

Reason for deducting 1 rating-

1) No explaination about preprocessing of dataset

2) No pdf is given for future reference

von andrew r

16. Nov. 2020

Covers the basics and explains clearly the difference between regression and categorization. Lab work was instructive. Some of the material is now out of date, contains grammatical and spelling errors, and has inconsistencies with instructions and testing.

von Tauseef A

2. Juni 2021

The hands on lab are not worth it, there is very less explanation about why we are doing particular step, take for eg final peer graded we just put Boolean value based on just the attribute value of master or above. Very poor last project to be honest.

von John V H

14. Nov. 2019

I liked the course overall. Some of the lectures did not break down real world data sets or examples as much as I would have liked. Additionally, it would be nice to have more real world data set examples or tutorials to study or analyze with Python.

von Michael L

23. Okt. 2019

The labs are great and the videos are spot on. However, there are numerous typos here and there and also the final project grading rubric had some issues and did not provide some people with guidance and submissions that were correct were marked wrong,

von Rick K

22. Feb. 2022

The course information was good. I wish the videos would have touched on the pythonic code for these examples, even just a little bit. The bad was that the labs were down through the majority of my class which made it difficult to see the python part.


7. Aug. 2020

All classes was very well designed and structured. In my opinion was the best course I done by coursera. The inconvenience was due to IBM Watson. The Lite service plan offers 50 free hours of free use and I received 10 as the time limit.

Thank you.

von Miele W

21. Dez. 2019

A very good course to grasp the foundamentals of Machine Learning using python. Besides the math explanations, i reccomend to have at least a basic knowledge of python, in order to explore the jupyter labs which, in my opinion, are solid examples.

von Sean L

31. Aug. 2020

Really interesting course. I would have enjoyed if it went into more depth in some of the topics, for example being more specific with certain algorithms. Would also have liked a peer graded assessment on multiple topics (not just classifiers).

von Tom C

12. Aug. 2021

Excellent overview of machine learning in Python. Only reason I didn't give it a 5 is because I would have liked a little more content introducing more of the sklearn library in order to be better prepared for working on the project correctly.