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Voltar para Aprendizagem automática com Python

Comentários e feedback de alunos de Aprendizagem automática com Python da instituição IBM

12,667 classificações
2,199 avaliações

Sobre o curso

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....

Melhores avaliações


6 de fev de 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.


8 de out de 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.

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151 — 175 de 2,199 Avaliações para o Aprendizagem automática com Python

por Jeff P

17 de jun de 2019

I think it would be beneficial to talk about neural networks somewhere after the gradient of steepest descent section. I did appreciate the course talked about many other ML algorithms that are not typically covered by other programs - and the lab notebooks are extremely valuable.

por farid a

7 de mar de 2022

I suggest this course to others because of good teaching videos and the top of that,coding enviroment just like that google Colab and Kaggle with simple and substantial explanation in comments. It is really amazing .Thank you to IBM team and coursera website . best wish for you.

por XFAN

17 de abr de 2020

If more knowledge on 1) how to find the optimal depth value for decision trees and variables for other models; 2) explanations on parameters used, will be elaborated in hands-on lab notebooks, it would be better. Those are important to new beginners with zero idea on ml models.

por Yi Y

3 de out de 2018

It is one of the best introduction course to Machine Learning.

The material is well explained to someone with a beginner level of understanding to Statistics and Machine Learning.

All the material is presented in a way that is easy to understand, without leaving out the details.

por Salman T

26 de ago de 2021

One of the best course on Coursera so far. Instructors not only covered the theoretical side of the the course but also taught us how to implement various algorithms practically. I would definitely refer it to anyone who wants to start a career in the machine learning field.

por Shiva S

19 de mar de 2020

This course is a good chance to start python programming and reviewing ML concepts with deeper insights. I would suggest it for those who are familiar with ML and its algorithms. For those ones who want to start learning ML, it is better to take ML courses with Basic level.

por Reza J

15 de out de 2021

It was a great experience for me to start learning on Coursera with this course. I face with great tools, great learning methods, so I became interested in getting other courses of IBM in this field. thank you, Coursera, thank you, IBM and thank you dear Saeed Aghabozorgi.

por Omri

27 de nov de 2019

Great course, cover many important aspects of classical machine learning algorithms. The lectures are very focused and not tedious. Labs are excellent, and can serve as a starting point for every data science project in the future. I definitely recommend taking the course.

por Pankaj Z

3 de mai de 2020

This is one of the finest courses for anyone who wishes to transform his/her career into Machine Learning. It has optional external tool assignments after each chapter to help you understand and try out code and the concept. I would highly recommend this course to anyone.

por Mohadeseh E

13 de jan de 2022

Hello Dears,

This course was very great for me because it taught me a lot of practical projects.

I would like to express my special thanks to everyone who built the coursera site and teaches these courses and IBM company.

Thank you so much,

Kind regards,

Mohadeseh Emamipour

por Dominique D

16 de abr de 2020

If you put your heart to it, there is really a lot to learn in the course. The course touches quite some ML topics and gives a good introduction to it. I feel I got a whole new set of tools to use, and i am hungry to learn and experiment more.

Really enjoyed the course!

por Benedict A

1 de abr de 2020

The videos and labs were remarkable in that it was able to concisely communicated vast and complex information.

I did have to do additional research to fully understand and appreciate the material because I am not coming from a programming or statistical background.

por Toan L T

28 de out de 2018

Great course.

Knowledge wise, just like Prof. Ng's, minus the mathematics foundation.

Practical wise, carefully designed labs really help learners understand the data cleaning processes, understanding data through visualization, ML algorithms and evaluation metrics.

por Joshua F

14 de jan de 2021

The course was really great. You have the luxury to explore in-demand practical skills and apply them in fun ways. ML is applicable to the industries, and our lives. I've been blessed greatly by the expertise of the instructors to design a well-structured content.

por Roger T

28 de mar de 2020

It's a very precise and practical course. It focuses on the main ideas and application aspects of M.L., without drilling too deep into the math rationale behind.

To get the most from this course, it's good to equip yourself with basic knowledge in numpy and pandas.

por Ashish S

14 de set de 2019

Can include more details. Every time I was more interested in a certain topic it mentioned it was out of the scope of this which was disappointing. I absolutely loved the teaching and would like to hear more to his lectures and sessions!

Amazing course. Thank you!

por Patrick W B

4 de fev de 2020

The lessons are very simple to understand with both logic intuition and mathematical explanations.

It is really the best course and beginner friendly.

I strongly recommend this course for anyone willing to start a career in Artificial Intelligence technologies.

por Victor A M B

17 de set de 2019

Muy buen curso, se da información bastante relevante acerca de los algoritmos de Maching Learning. Debe tenerse en cuenta que después de este curso será necesario profundizar más en los diferentes algoritmos, pero en mi opinión esto se dará con mayor facilidad.

por Ravi P B

12 de mai de 2020

Excellent Course.Really enjoyed it.Covers details of lots of machine learning techniques and their implementation also.A nice way to start Machine learning.Instructors are fantastic.Even those who already know machine learning can learn a lot from this course.

por henry c

19 de set de 2019

The course is not easy, but it is a lot of work with dedication and commitment to the management of platforms, if the concepts are very understandable and the laboratories are very didactic, thank you very much for sharing the information and thanks again ...

por Moez B

24 de fev de 2019

Excellent course on machine learning principles and various algorithms. It's a great start if you want to jump into the practical side of implementing ML using Python libraries, without getting too deep into the theory behind the most popular algorithms.

por Yiannis B

26 de jun de 2021

The requested Final Assignment was TOO difficult in regard to what was taught during the course. No objection to provide more material into the course to support the final assignment. It was of course a wonderfull course although a pain in the ... back!

por Chayan M

6 de jan de 2021

Good learning opportunity on ML using various data science modules in Python. The Labs are well defined using the Jupyter notebook platform. All in all great learning experience and would recommend the course to anyone aspiring towards ML data sciences.

por Kiran S

14 de out de 2020

Only concern is notebook should be user friendly and setting up the notebook and sharing should be straight forward. I did spend quite few hours how to set up those things . Over hall Course is good and loved it but need more exercises to practice

por yatish s

17 de jul de 2019

It was a very good course having atmost knowledge about the machine learning with the help of python libraries. I recommend this course to the freshers in machine learning field having good knowledge of python libraries like numpy, pandas and matplot.