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Avis et commentaires pour d'étudiants pour Introduction to Applied Machine Learning par Alberta Machine Intelligence Institute

690 évaluations
154 avis

À propos du cours

This course is for professionals who have heard the buzz around machine learning and want to apply machine learning to data analysis and automation. Whether finance, medicine, engineering, business or other domains, this course will introduce you to problem definition and data preparation in a machine learning project. By the end of the course, you will be able to clearly define a machine learning problem using two approaches. You will learn to survey available data resources and identify potential ML applications. You will learn to take a business need and turn it into a machine learning application. You will prepare data for effective machine learning applications. This is the first course of the Applied Machine Learning Specialization brought to you by Coursera and the Alberta Machine Intelligence Institute....

Meilleurs avis


8 oct. 2020

I have been teaching Machine Learning for some time now. This course is really good and comprehensively presents the working of machine learning process in a nutshell. Very good introductory course.


28 oct. 2019

I have really got benefit from this course as a beginner to ML, it gives me the best understanding of ML. I m looking forward to getting into it more efficiently with more practices.

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126 - 150 sur 158 Avis pour Introduction to Applied Machine Learning

par Swapnali L

25 avr. 2021

Very good

par Sujatha M

22 juin 2020


par Silvia E

16 sept. 2019

Loved it


20 mai 2020


par Aparajita M

19 janv. 2022



19 avr. 2020


par Phanikumar P

3 juin 2020

Positive point about this course was explanation of real life examples and basic definitions of machine learning was really excellent. but I have one suggestion for this course was please explain QuAM clearly and specifically with examples.

par Shingo F

22 mars 2020

The lectures are good but no textbook is available. This makes me hard to review what I learned. In addition, I wanted to know the answers after the exams are over but I couldn't. Please give us the explanations of the exams.

par Abdullah A

12 sept. 2019

very comprehensive course on applied machine learning. the most interesting information in this course is business needs for ML and what it's requirement to have a good QuAM.

par Vern E

22 sept. 2019

I have taken a great deal of knowledge in this course and have applied it to what I have seen in the ML and AI world. This was a great introduction!

par Ali H

30 mars 2020

It is a good start. For sure, this course is recommended for everyone who is not in the computer science world.

par Srihari A

15 avr. 2020

It was basic and super easy to understand. Kudos to the instructor for doing a great job.

par Saleha Z

27 mars 2020

t refreshed my previous concepts of machine learning with better understanding


21 juil. 2020

This course gave me a very good general understanding of Machine Learning.

par K P K

24 janv. 2021

week 3 needs some technical information which it lacks

par Abdulaziz S

19 nov. 2020

it is very good as a beginner, Thank you

par BADANA M 1

10 sept. 2021

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par Hameed H

12 juin 2022

Very enlightning


19 avr. 2020


par Ashwith

3 juin 2020


par rohan g

12 oct. 2020

A bird's Eye View with all algorithms available with some practice example would have been beneficial instead of procrastinating it to later courses. This would help to generate more interest in the topic

par Kleuber R A

15 juil. 2021

Good! The course has a very simple content, easy to understand and well structured, it can be completed very quickly and not in the 4 weeks proposed.

par Kumar

22 août 2020

I love the way you presented. It is better if we get hands on project to apply. Thank you so much for your time and efforts.

par rezvan a

28 mai 2020

It was way more easier that I thought, As a finance expert with background in engineering I already knew all the stuff.

par Hen H

10 févr. 2021

tests are a joke ! and material can be finished in ~2hrs, not 4 weeks.. and yes, I read all the extra material