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Learner Reviews & Feedback for Machine Learning with Python by IBM

4.7
stars
15,242 ratings

About the Course

Get ready to dive into the world of Machine Learning (ML) by using Python! This course is for you whether you want to advance your Data Science career or get started in Machine Learning and Deep Learning. This course will begin with a gentle introduction to Machine Learning and what it is, with topics like supervised vs unsupervised learning, linear & non-linear regression, simple regression and more. You will then dive into classification techniques using different classification algorithms, namely K-Nearest Neighbors (KNN), decision trees, and Logistic Regression. You’ll also learn about the importance and different types of clustering such as k-means, hierarchical clustering, and DBSCAN. With all the many concepts you will learn, a big emphasis will be placed on hands-on learning. You will work with Python libraries like SciPy and scikit-learn and apply your knowledge through labs. In the final project you will demonstrate your skills by building, evaluating and comparing several Machine Learning models using different algorithms. By the end of this course, you will have job ready skills to add to your resume and a certificate in machine learning to prove your competency....

Top reviews

FO

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.

RC

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.

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151 - 175 of 2,667 Reviews for Machine Learning with Python

By Xi W

•

Jan 16, 2022

Thanks for providing this excellent course. It explains things clearly and step by step. I learned a lot from this course. There are some minor errors in the exercises. It would be good if the team updates the exercises codes more frequently. And it would be nice if we will have a standard answer for the capstone project.

By Shivansh G

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Feb 28, 2022

Brilliant content for starters like me who are looking to make their way into the Data Science world. The course offers a conceptualised learning experience with practical examples to enhance one's skills. I loved the content and the instructors are very fluent. A great course for anyone looking to enjoy introductory ML.

By Siva s

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Jun 3, 2021

I have found this course very helpful - in terms of the concepts explained in the video for the different machine learning algorithms.

IBM Watson studio is very useful tool introduced through this course.

The assignment notebooks had guided instructions - on how to apply the learnt coding techniques and various ML models.

By MICHAEL K

•

Sep 16, 2020

The Machine Learning course was made practical with hidden mathematics and applied to solve real world research problems. The instructor merged the theories with labs to simplify difficult part of Machine Learning. I recommend this course for any one interested in using predictive modelling to solve research questions.

By kalidindi s v

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Apr 4, 2020

Before joining this course I thought ML is so tough. But after this course I got a overview of some of the concepts of ML and not only overview, they also provided the lab sessions for every concept they teach. I suggest the beginners to join this because they get the complete overview of Machine learning. Thankyou..

By Rafael A C

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Jun 24, 2020

Presentations are very well designed. I have teaching experience and I can tell you that my style is great for illustrative purposes.

I learned to conceptually understand the mechanism and purpose of the models presented in Machine Learning. I feel like I can do things that were unthinkable for me before. Thanks IBM!

By Abhijit S

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Mar 9, 2020

This introductory course is really very good to understand the basics as well as methods to perform activity. Would recommend highly to anyone wish to learn ML in Python. The explanation, bit of maths and code were flawless and explained well in video as well as in code (most of code is explained in sample notepad).

By Daniel K

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Nov 1, 2019

The information in this course is laid out in a easily digestible format that makes it possible to fully own the knowledge that you gain and put it to the test. I appreciate that the videos are straight to the point and that the jupyter notebooks illustrate varying techniques for cleaning data. Tremendous value.

By Amy P

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Jul 25, 2019

Having worked my way through the IBM Data Science courses, this one was the "pay off" - it was so cool to finally apply more sophisticated techniques to real world data sets. The labs were fantastic. Highly recommend this course to anyone interested in learning about the most popular machine learning algorithms.

By V M R

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May 18, 2019

Complex concepts of machine learning algorithms are explained clearly with an illustration. Learner definitely have confidence in Machine learning after this course completion. A practical assignment work is really helped the learner to do the implementation of classifier model of their own and gain confidence.

By Shakshi N

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Jan 15, 2020

This course has been awesome. I have been doing ML Work for my college for quite some time, but never understood what goes in it, and kind of surfed through the net and just did the work. But this course has given me in depth knowledge of the logic that goes behind these algorithms and for that I am very glad.

By Prasanna K

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Mar 10, 2023

Amazing course... !! Thoroughly explained every concept with a number of examples.Also helped me to remember the concept by quality test at the end of every topic.It also helped me to learn more about the concept by applying those concepts in the real time projects.

thanks a lot for this amazing course...

By Mayank P

•

May 21, 2019

This course offers a simple and effective experience. I learnt how to find the most accurate algorithms in the scenarios. Most importantly, the Jupyter notebooks provided are although optional, but you should study them thoroughly. They might seem difficult on an overview, but are very easy to understand.

By Surendrabikram T

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Jul 12, 2019

Great course.

It could be even better if programming assignment were provided in each week but still, final assignment was of great quality and I found it really engaging. The program introduces you to scikit learn which is again a wonderful advantage of taking this program. I am giving this course 5/5.

By Li G

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Aug 25, 2020

A very good course for beginners. It's quite practical and helpful. If it can go to more details of the machine learning modeling algorithms, it would be better. I get an overall picture of simple machine learning tasks but cannot handle real work task yet. The real world is much more complicated.

By XiangDong F

•

May 20, 2023

This is an excellent course. The teacher explains very clearly and in the shortest possible time, I have gained a solid understanding of the core concepts and practical applications of various algorithms. I highly recommend it for business students who want to get started with machine learning.

By Christopher B

•

Aug 19, 2020

The course was quite challenging. I especially appreciate how the labs required significant modification and deep understanding of the underlying motivation for the code in order to complete the final project for the course. Thanks to the lab authors and instructors for some high-quality demos!

By Luis M

•

Jan 8, 2020

The course was thorough and a great introduction to machine learning. The capstone project was challenging and required me to have a good working knowledge of the various models. This has been the most intensive course, so far (course 8 of 9), in the IBM Data Science Professional Certificate.

By Priyansh S

•

Jul 20, 2019

The course is really good for machine learning beginners. I would recommend everyone to take this course as it gives you all the basic knowledge and working of ML. It is fun to do with the Jupyter notebook tool which gives a great actual experience. Thanks a lot. This course helped me a lot.

By G_R_S

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May 7, 2020

It is indeed a very thorough course, yet easy to understand. The animations and visual graphics made it an engaging and pleasurable experience. Learning classification, clustering and regression was made easy in such a way, that I could do it all over again without hesitation. Keep it up!

By Thierry P

•

Mar 11, 2021

BEWARE : student access to ibm cloud for last project lab is limited : I have reached the max usage working 10 days for 2 hours. I would prefer have been warned at the begining of the course about this limitation instead of discover it at the end when I needed to finish my last project

By Luís M B d M

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Mar 3, 2021

I really loved doing this course and I definitely recommend it to anyone with a minimum level of machine learning algorithms who is looking to gain a better and more comprehensive understanding of this subjects. The instructors are awesome, as well as the course materials and videos.

By Jeff P

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Jun 17, 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.

By farid a

•

Mar 7, 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.

By XFAN

•

Apr 17, 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.