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Machine Learning A-Z™

Hands-On Python & R In Data Science

Interested in the field of Machine Learning? Then this course is for you.

This course has been designed by two professional Data Scientists so that we can share our knowledge and help you learn complex theory, algorithms and coding libraries in a simple way.

We will walk you step-by-step into the World of Machine Learning. With every tutorial you will develop new skills and improve your understanding of this challenging yet lucrative sub-field of Data Science.

This course is fun and exciting, but at the same time we dive deep into Machine Learning. It is structured the following way:

  • Part 1 - Data Preprocessing
  • Part 2 - Regression: Simple Linear Regression, Multiple Linear Regression, Polynomial Regression, SVR, Decision Tree Regression, Random Forest Regression
  • Part 3 - Classification: Logistic Regression, K- So not only will you learn the theory, but you will also get some hands-on practice building your own models.

And as a bonus, this course includes both Python and R code templates which you can download and use on your own projects.

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Rating 4.3 based on 10,773 ratings
Length 41 hours
Starts On Demand (Start anytime)
Cost $11
From Udemy
Instructors Kirill Eremenko, Hadelin de Ponteves, SuperDataScience Team, SuperDataScience Support
Download Videos Only via the Udemy mobile app
Language English
Subjects Business Data Science
Tags Business Data & Analytics

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What people are saying

We analyzed reviews for this course to surface learners' thoughts about it

step by step in 155 reviews

The step by step implementation of the algorithms in both Python and R enhance the learning experience while providing the students with valuable material to use later.

Even though CRISP DM provides that insight but seeing it getting applied step by step in this course enlighten me.

Very nice and step by step explanation of whatever we are doing.

The course also give step by step coding.

Step by step and understandable.

but the reason for less rating is to get the attention to convey the message that Why there is not step by step approach in tutorial from Krill.

During the neural networks and XGBoost chapters, installing required packages got very complex and instruction for it were very difficult to follow especially since he was on mac and was not fully step by step.

I learned coding Python and R step by step.

hadelin de ponteves in 25 reviews

Interessante en goede cursus, verzorgd door ervaren trainers Kirill Eremenko en Hadelin de Ponteves.

Kirill Eremenko and Hadelin de Ponteves are a really good team.

Kirill Eremenko and Hadelin de Ponteves do a great job with the way the course is structured and communicated.

Thank you Kirill Eremenko and Hadelin de Ponteves.

Very nice Thanks for Kirill Eremenko Hadelin de Ponteves.

对于机器学习的知识体系有相当全面的覆盖,讲解通俗易懂,是非常好的课程,最重要的是每个知识点都是理论与操作并重,非常棒! This is an amazing course put together by Kirill Eremenko and Hadelin de Ponteves.

Thanks to Kirill Eremenko and Hadelin de Ponteves for wonderful course design.

I will suggest,anyone who are searching for any course related to data-science, machine learning, deep learning etc, if you see the instructor on any course is Kirill Eremenko or Hadelin De Ponteves then blindly choose that course.

andrew ng in 21 reviews

I just had completed the ML course by Andrew NG on coursera, so I had a base good enough to get along with the implementation of the algorithms in Python (I am avoiding R for now).

Great course on Applied Machine Learning, I think this course should be taken after Andrew Ng Machine Learning course so you know the theories of ML algorithms and then how to apply them.

The instructor is awesome who explains each algorithm in simplest possible way without mathematical complications (even though I was looking for it for which I referred Andrew NG course).

This is a wonderful course, came to this course after completing Andrew Ng's course on Coursera.

After absorbing the theoretical-cum-intuitive style of teaching of Andrew Ng, I needed some hands-on.

I found the course from Andrew NG very deep in theory while this course is moderately deep in theory and also has many example exercises used to explain various algorithms.

For me, too much of theory makes it hard to stay attentive, which is why I liked this course better than the one from Andrew NG, though the course from Andrew NG is a must take and has a lot of theoretical depth necessary for ML.

However, if you are like me who prefers watching things in action more than theory, this is the course you must take first, followed by the one from Andrew NG.

superdatascience team in 21 reviews

Kudos to SuperDataScience Team!

First of all hats off to Kirill, Hadelin and entire SuperDataScience team on building a very comprehensive and easy to learn online course.

SuperDataScience Team is very quick to answer the questions in detail.

Thanks Kirill and all SuperDataScience Team and Udemy to publish this course everything was great all the codes worked and the course was updated.

It has kick started my journey into machine learning and I can now dig deeper into machine learning .Thanks Kirill, Hadelin and SuperDataScience Team.

And now very excited to pick my new course "Data Science A-Z & Deep Learning" Thanks alot kirill eremenko, Hadelin de Ponteves and SuperDataScience team for such a wonderful course.

Thanks to Kirill, Hadelin &Superdatascience team for putting this together!

Congrats SuperDataScience team A very good intro to machine learning.

muito bom in 17 reviews

Muito bom curso.

Muito bom, as explicações são bem feitas e possui bons exemplos que são explicados passo a passo.

Muito bom o curso.

Conteúdo completo, professor bastante didático, material muito bom clear explanation, can't wait to learn more on this course Very well done, would give 5 starts if each video had a author made subtitles This course provides knowledge regarding different machine learning models and their accuracy .And applicable in all datasets.In this course,doudts are cleared and with correct explanation.

Muito bom.

nice introduction and installation steps Am learning and intrigid Ok Muito bom, gostei muito das explicações do instrutor e a forma de discorrer sobre cada assunto.

Because concepts are building step-wise Su ana kadar bir sıkıntı yasamadım Material muito bom porem poderia corrigir a legenda, palavras erradas a todo momento.

Realmente muito bom.

neural networks in 15 reviews

Convolutional neural networks is such a wide field ---certainly couls have explained it a little better This course encouraged me a lot.

The main instructor rambled way too much, especially in the artificial and convoluted neural networks part.

There was also a nice little introduction to Deep Learning and Neural Networks.

XGBoosting is covered in the class which is cutting edge and not found elsewhere on Udemy; however, I wish they added a video on the intuition to explain why it can beat neural networks.

*5/5* I particularly enjoyed the practical emphasis, as I learned to import and manipulate data, apply regression and clustering techniques, and create Neural Networks in a logical step-by-step approach.

It was a great learning experience about Machine Learning for beginners especially the topics like Regression and Neural networks.

I only hope they create more advanced and specialized courses targeting Recurrent Neural Networks and Boltzman Machines.

When I first started on machine learning, I was pushed right into convolutional neural networks, which was not where I needed to be!


An overview of related careers and their average salaries in the US. Bars indicate income percentile.

Research Scientist-Machine Learning $55k

Cloud Architect - Azure / Machine Learning $75k

Watson Machine Learning Engineer $81k

Machine Learning Software Developer $103k

Software Engineer (Machine Learning) $116k

Applied Scientist, Machine Learning $130k

Autonomy and Machine Learning Solutions Architect $131k

Applied Scientist - Machine Learning -... $136k


Machine Learning Engineer 2 $161k

Machine Learning Scientist Manager $170k

Machine Learning Scientist, Personalization $213k

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Rating 4.3 based on 10,773 ratings
Length 41 hours
Starts On Demand (Start anytime)
Cost $11
From Udemy
Instructors Kirill Eremenko, Hadelin de Ponteves, SuperDataScience Team, SuperDataScience Support
Download Videos Only via the Udemy mobile app
Language English
Subjects Business Data Science
Tags Business Data & Analytics

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