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Learner Reviews & Feedback for Machine Learning with Python by IBM

4.7
stars
16,914 ratings

About the Course

Python is one of the most widely used programming languages in machine learning (ML), and many ML job listings require it as a core skill. This course equips aspiring machine learning practitioners with essential Python skills that help them stand out to employers. Throughout the course, you’ll dive into core ML concepts and learn about the iterative nature of model development. With Python libraries like Scikit-learn, you’ll gain hands-on experience with tools used for real-world applications. Plus, you’ll build a foundation in statistical methods like linear and logistic regression. You’ll explore supervised learning techniques with libraries such as Matplotlib and Pandas, as well as classification methods like decision trees, KNN, and SVM, covering key concepts like the bias-variance tradeoff. The course also covers unsupervised learning, including clustering and dimensionality reduction. With guidance on model evaluation, tuning techniques, and practical projects in Jupyter Notebooks, you’ll gain the Python skills that power your ML journey. ENROLL TODAY to enhance your resume with in-demand expertise!...

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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2276 - 2300 of 2,952 Reviews for Machine Learning with Python

By Luke P

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Jan 25, 2021

Good course if you have some basic knowledge of Python and data analysis. However, much of the course material had typos and small errors.

By Laura S M D

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Dec 14, 2019

Un curso muy completo, aunque mejoraría un poco los ejercicios, que al estudiante se le diera más importancia en la resolución del programa

By Jacqueline ( G

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Aug 4, 2019

It's so bad when someone reviews your assignment and gives you an unfair score. But this happened a lot because of this peer review system.

By Muhammad R F D

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Mar 4, 2020

Well Explained. Video lecs are very easy to understand and upto the mark...Assignments little bit need more clarification and explanation.

By Ramzi M A A

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Aug 26, 2024

I prefer if there is a human instructor rather than the machine one... Any way, great course.. it gave me the basics needed in the field.

By Manoj S H

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May 4, 2023

I needed the syntax to be explained in the video tutorial also because it would be even easier to make the notes on a specific algorithm.

By Luis R

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Dec 19, 2021

Great course ! I really liked the fact that you don't need to install anything to try out the code and the system works without problems.

By Gaurav S

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Jul 18, 2019

The Course Could have been a little better if there were more theory and more illustrations at time a disconnect was felt in the Course

By Alonso h g

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Oct 25, 2021

I think the methodology is outdated. But the bases are the same. It is remarkable that they teach how the algorithm and formulas work.

By Shivam S

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Nov 6, 2020

Very fascinating course but exercises like final project will be more for exposure to real coding than it will be really more helpful.

By Roman S

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Jun 9, 2020

Course content and presentation is really good! The only thing i would add is the tuning of hyperparamaters which makes ML what it is.

By Sushant P

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May 3, 2020

Great course but there should be videos where there is need of explanation on code as well, codes given are very good and covers basic

By Mallangi P R

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Jan 27, 2020

I really liked the course content, way of teaching and assignments.

This will definitely help a beginner in data analysis to start with

By Beatriz E P

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Jan 28, 2021

Very nice course!! You learn a lot more of the theory than the practice part, but the concepts are well explained and I learned a lot

By manasa k

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Feb 22, 2021

A good course to quickly learn important aspects of ML with Python. The assignments and final exam is also very useful for learning.

By fang f

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Jul 11, 2020

quite good at the explanation and un-graded exercises.

But the knowledge could be deeper and more about parameters in Sklearn APIs.

By Ankit M

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Jul 25, 2019

Goodone for anyone who's a beginner in this field. But I personally suggest you to take the Data Analysis with Python course first.

By Raffaele N

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Sep 13, 2019

Although not extremely detailed in the model optimisation part of the work, it is a very useful way to get started on applied ML.

By Sadanand U

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May 1, 2019

Gives a good overview of regression and classification algorithms . It could have been expanded to other ML algorithms as well.

By Mohitkumar R

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Jan 12, 2019

Great course, SO much information and great excercise, In Captone project project guidance need improve,otherwise great course

By Katja M

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Apr 22, 2021

It was a hard class - the concepts made sense but it is hard to figure out how to use them without more programming examples.

By Vedang D

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Jun 10, 2024

Great Course to get an understanding of Machine Learning in Python with no background knowledge needed. Cheers to Learning!

By Baptiste M

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Nov 17, 2019

Very complete course yet full of typos even in the datasets. Lots of information were redundant but an overall great value.

By Eric H

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Dec 20, 2018

After taking Andrew Ng's ML course, I still learned some new things here, but this course is rather shallow in comparison.

By Mitchell K

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May 25, 2021

This course was a great refresher from my data mining course in college, but I think some topics need to be expanded upon