Chevron Left
Voltar para Aprendizagem automática com Python

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

12,619 classificações
2,190 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.

Filtrar por:

101 — 125 de 2,187 Avaliações para o Aprendizagem automática com Python

por Dr. M C

30 de mai de 2021

The course was enlightening. The course is very well designed in terms of ease to follow from one to the next step. Concepts are well described along the way. There is plenty of room to try out different models and learn the next piece of the puzzle. Everything falls in place when you finally reach the capstone exercise. I recommend this course especially to those, like me, who love numbers! I enjoyed the course very much.

por Haroldo D Z

30 de set de 2019

Hay un nivel de Detalle en los Algoritmos de Machine learning, que ayuda a entender como pueden aportar realmente en diferentes problemas de regresión, clasificación, clusterring y recomendación. y la plataforma es muy practica para lograr entender como un lenguaje como python puede aportar a hacer mas sencillo la aplicación y uso de estos sin necesidad de instalar herramientas ni conocer los detalles del lenguaje.

por Niladri B P

22 de jun de 2019

A lot of ground is covered here. So it won't make you an expert, but will provide a great base from which one can build further expertise. The videos explain the concepts very nicely, so it is important to sit, listen and take notes. The labs are also very detailed and occasionally a bit advanced with the code. Overall, however, the course makes you work but you can choose how much work to put into it. Recommended.

por Aaron S I

2 de jan de 2022

G​ood course. Has bits and pieces of heavy theory and practical application.

F​inal project is much more open ended compared to others in the IBM Data Science Specialization track so far. Multiple ways to go about solving the project, and yet most of them will work. Still a bit of hand holding to guide someone along as to 'what to do'.

A​ decent course to make sure you are well on your way to doing data science

por Hussain A

17 de mai de 2020

The best direct-to-the point instructor so far! After going through the major classes available on the net I found Dr. Saeed Aghabozorgi concise way of keeping videos short with no code and rely on labs with best example for each concept highly admirable in an intermediate course. It took me once 30 minutes for taking notes about a 5 minutes video, well worth it. I say keep it concise it becomes a reference!

por Andréas V J

16 de mai de 2020

Fantastic course for quickly understanding the basic categories of machine learning algorithms and how they work. I would recommend this course to those who have some experience in computer science or software engineering with little-to-no experience in machine learning. Covered in this course: machine learning basics, data regression, classification algorithms, clustering algorithms and recommender systems.

por Rhea A

29 de ago de 2021

The intuitions behind the algorithm were very well explained, however line by line explanation of the codes could have been provided. Thank you for the crystal clear explanation of the intuition, really helped me a lot in understanding the concepts. I will high recommend this course to the beginners due to the clarity behind working of algorithm it gives. Thanks a heap. Looking forward to more such courses.

por Math

11 de set de 2020

Its a nice course for beginners! Gives clear explanations on some of the basic concepts! Python Notebooks give clear picture on basic code implementation aspects.

Suggestion - Week 6 there are 2 videos that need an update on logging into Watson Studio. Need to update the instructions with latest version. Its a minor correction; good if updated as our screens and options differ from your instructions.

por Jaime O

19 de abr de 2020








por Riccardo C

3 de abr de 2021

Course was great, however I think that when you deal with certain topics peer to peer review is not the best method for evaluation, or at least it should be kinda different from previous courses. In my opinion many students misunderstood some parts of the final assignment, so how are they suppose to review other's work? I saw I wasn't the only one noticing and having trouble with that.

por Kolitha W

3 de jan de 2021

Absolutely knowledgeable and interesting course with a plethora of insights and plenty of hands-on lab sessions to digest what you learn. I take this moment to thank all the resource collaborators and appreciate the immense effort they all have put into this course to keep it updated and attractive. I wish they could keep this up to help thousands of individuals to groom individually.

por William B L

27 de mar de 2019

This course gives a good introduction (theory and applied) to a variety of machine learning methodologies. The presentations are well thought-out. The labs are great. I learned an enormous amount from doing the hands-on work in Watson Studio/Jupyter notebook.

This would be a bit much for a beginner in Python, but with a modest understanding of the language, this offers a lot!

por Christian C

4 de mai de 2020

Excelente curso. Los contenidos se presentan de forma facil y comprensible. Hay un gran dominio por parte del instructor y ademas, los contenidos son cubiertos con suficiente profundidad.

Excellent course. The contents are presented in an easy and understandable way. There is great mastery on the part of the instructor and also, the contents are covered in sufficient depth.

por Timur U

27 de mar de 2020

I really enjoyed this well-organized and professional course. I would like to show my appreciation to the manager of this course, especially for a video presentation for each module. The technique to have Query and then Solution is the outstanding feature and helped me to cover all course materials and implement the Assignment tasks on a high level. Thank you so much.

por Marius-Liviu B

28 de dez de 2021

This is my first Machine Learning course so definitely I've learned a lot of new things. You cannot associate 100% Machine Learning with Programming, Math or Stats. And even you use scikit-learn it's not enough only to read the help for this tool. You need to know what model fits your problem, how to interpret the result and how can you optimize the solution.

por Juan R

9 de set de 2019

This Course is awesome to learn the theory and practice of some Machine Learning Metods.

By the end I feel like I can tackle my own datasets and analyze them with various methods seeking the optimal one.

The only thing that could be better is if the course could go a bit deeper into the optimization algorithms (like gradient descent) even if it's a bit mathy.

por Wagner M

4 de nov de 2019

[PT-br] Um dos melhores cursos onde se alinha teoria com a prática na área. Conteúdo bem completo, passando pelas diversas técnicas de ML, com vídeos muito bem explicados e conteúdos práticos que demonstram como aplicar cada técnica. Além disso, as provas são bem desafiadoras e o projeto final é bem completo, o que aumenta o valor do certificado ao final.

por Arindam G

20 de dez de 2018

No Doubt COURSERA is always best AND MNC like IBM,Google courses associated with coursera are MIND-BLOWING.

The Instructors are so great at Explanation Part that hardly anyone won't Understand All the Topics

I would love to thank all the INSTRUCTORS who created such a Awesome Content for us.

My Personal Ratings For All the Instructors: 100 / 100


26 de mar de 2020

The course was amazing to get started with machine learning. You are going to learn about some amazing machine leaning algorithms and for the capstone project you have to use them to find best accuracy for a dataset. Peer reviewed assignments are really good as they help every student to know different techniques each person use and can learn from them.

por Lior B

28 de ago de 2019

Great introductory course. Clear explanations and good homework to get your hands dirty and see results of algorithms.

A rather minimal mathematical understanding is assumed by the course so begginers would not be overwhelmed.

Keep in mind this course will not make you an expert or teach you how to write some of the more advanced algorithms by yourself.

por Robinson P P

30 de abr de 2020

Excellent Course. Course cover.

1) Regression

2) Classification- Algorithm :KNN , Decision Tree , SVM , Logistic Regression etc.,

3) Clustering- K-Means , Hierarchical ,Agglomerative ,DBSCAN

4) Recommender System - Content-Based and Collaborative Filtering

5) sci-kit learn and SciPy details with Practical labs on Jupyter Notebook on IBM Watson Platform

por Akbar B

20 de abr de 2020

This is by far the best course on ML. I have explored many online courses. However, this one is the simplest and most effective. Instructor (Mr. Saeed) has explained the concepts with practical examples. His way of explaining things is very simple and to the point. I enjoyed each and every section of the course. Looking forward to his next course.

por Vijayanandhan

5 de jul de 2019

The Video content is very clear and simple to understand the concepts and lab is very good. The IBM Trainer


did a great job in this course. Got hand on experience on Machine learning. Final Project is helpful to apply all the concepts I learned throughout the course. Glad to get this certification from Coursera and IBM.

por Rakshith

27 de dez de 2019

under well designed syllabus , became easy to learn and solve real world examples,which keeps motivated through out the learning process . The fascinating about this platform is the ease for access to quality resources or otherwise it is difficult. The end of course meant to me s skill for solution to many issues irrespective of field.