Mahout Online Training | Machine learning Certification Course | Edureka

Machine Learning with Mahout Certification Training

An online course designed to provide a blend of Machine learning & Big Data and where Mahout fits in the Hadoop Ecosystem.


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Why this course ?

Online self - paced learning

Online Self Learning Courses are designed for self-directed training, allowing participants to begin at their convenience with structured training and review exercises to reinforce learning. You'll learn through videos, PPTs and complete assignments, projects and other activities designed to enhance learning outcomes, all at times that are most convenient to you.
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Course Duration

You will undergo self-paced learning where you will get an in-depth knowledge of various concepts that will be covered in the course.

Real-life Case Studies

Towards the end of the course, you will be working on a project where you are expected to implement the techniques learnt during the course.


Each module will contain practical assignments, which can be completed before going to next module.

Lifetime Access

You will get lifetime access to all the videos,discussion forum and other learning contents inside the Learning Management System.


edureka certifies you as a expert in Machine Learning with Mahout based on the project reviewed by our expert panel.


We have a community forum for all our customers that further facilitates learning through peer interaction and knowledge sharing.

This course covers the fundamentals of machine learning techniques ranging from various algorithms of Support Vector Machines, k-means clustering, Random Forests, Collaborative filtering to recommendation system, Mahout on Hadoop and Amazon EMR, etc.

After the completion of Apache Mahout Course at Edureka, you should be able to: 

1. Gain an insight into the Machine Learning techniques. 

2. Understand the algorithms of SVM, Naive Bayes, Random Forests,etc.

3. Implement these using 'Apache Mahout'

4. Understand the recommendation system

5. Learn Collaborative filtering, Clustering and Categorization

6. Analyse Big Data using Hadoop and Mahout

7. Implementing a recommender using MapReduce

8. Introduction to tools like Weka, Octave, Matlab, SAS

This course is designed for all those who are interested in learning machine learning techniques in big data domain and write intelligent applications using Apache Mahout. The following professionals can go for this course : 

1. Analytics Professionals

2. Data Scientists looking to hone their machine learning skills

3. Software Developers and Architects

4. Business Analysts wanting to learn Mahout for ML implementation

5. Professionals working with R, Matlab, Python, etc. 

6. Statisticians looking to learn machine learning techniques

7. Graduates aspiring to take a leap in analytics domain

The basic Java and Hadoop knowledge is recommended and not mandatory as these concepts will also be covered during the course.

In the modern information age of exponential data growth, the success of companies and enterprises depends on how quickly and efficiently they turn vast amounts of data into actionable information. Whether it's for processing hundreds or thousands of personal e-mail messages a day or driving user intent from petabytes of weblogs, the need for tools that can organize and enhance data has never been greater. Therein lies the premise and the promise of the field of machine learning and Apache Mahout.

For your practical work, we will help you setup Edureka's Virtual Machine in your System. This will be a local access for you. The required installation guide is present in LMS.

Learning Objectives - This module will give you an insight about what 'Machine Learning' is and How Apache Mahout algorithms are used in building intelligent applications.

Topics - Machine Learning Fundamentals, Apache Mahout Basics, History of Mahout, Supervised and Unsupervised Learning techniques, Mahout and Hadoop, Introduction to Clustering, Classification.

Learning Objectives - In this module you will learn how to set up Mahout on Apache Hadoop. You will also get an understanding of Myrrix Machine Learning Platform.

Topics - Mahout on Apache Hadoop setup, Mahout and Myrrix.

Learning Objectives - In this module you will get an understanding of the recommendation system in Mahout and different filtering methods.

Topics - Recommendations using Mahout, Introduction to Recommendation systems, Content Based (Collaborative filtering, User based, Nearest N Users, Threshold, Item based), Mahout Optimizations.

Learning Objectives - In this module you will learn about the Recommendation platforms and implement a Recommender using MapReduce.

Topics - User based recommendation, User Neighbourhood, Item based Recommendation, Implementing a Recommender using MapReduce, Platforms: Similarity Measures, Manhattan Distance, Euclidean Distance, Cosine Similarity, Pearson's Correlation Similarity, Loglikihood Similarity, Tanimoto, Evaluating Recommendation Engines (Online and Offline), Recommendors in Production.

Learning Objectives - This module will help you in understanding 'Clustering' in Mahout and also give an overview of common Clustering Algorithms.

Topics - Clustering, Common Clustering Algorithms, K-means, Canopy Clustering, Fuzzy K-means and Mean Shift etc., Representing Data, Feature Selection, Vectorization, Representing Vectors, Clustering documents through example, TF-IDF, Implementing clustering in Hadoop, Classification.

Learning Objectives - In this module you will get a clear understanding of Classifier and the common Classifier Algorithms.

Topics - Examples, Basics, Predictor variables and Target variables, Common Algorithms, SGD, SVM, Navie Bayes, Random Forests, Training and evaluating a Classifier, Developing a Classifier.

Learning Objectives - At the end of this module, you will get an understanding of how Mahout can be used on Amazon EMR Hadoop distribution.

Topics - Mahout on Amazon EMR, Mahout Vs R, Introduction to tools like Weka, Octave, Matlab, SAS.

Learning Objectives - In this module you will develop an intelligent application using Mahout on Hadoop.

Topics - A complete recommendation engine built on application logs and transactions.

. Call a Course Adviser for discussing Curriculum Details . 1844 230 6361
As soon as you enrol into the course, your LMS (The Learning Management System) access will be functional. You will immediately get access to our course content in the form of a complete set of Videos, PPTs, PDFs and Assignments. You can start learning right away.
We do provide placement assistance by routing relevant job opportunities to you as and when they come up. To get notified on relevant opportunities, it is important that you fill out your profile details.

It is important to attend classes and complete assignments. Course completion is an important criterion based on which we screen profiles of learners interested in a particular job. Also, before your profile is shared with prospective employers, you will have to go through an internal assessment by edureka. So it is important to be well versed with the course concepts to become eligible for placement opportunities.
You can pay by Credit Card, Debit Card or NetBanking from all the leading banks. We use a CCAvenue Payment Gateway. For USD payment, you can pay by Paypal. We also have EMI options available.
You can Call us at +91 90660 20867 /1844 230 6362 ( US Tollfree ) OR Email us at . We shall be glad to assist you. 

  • Once you are successfully through the project (Reviewed by a edureka expert), you will be awarded with edureka’s Machine Learning with Mahout Expert Certificate.
  • edureka certification has industry recognition and we are the preferred training partner for many MNCs e.g.Cisco, Ford, Mphasis, Nokia, Wipro, Accenture, IBM, Philips, Citi, Ford, Mindtree, BNYMellon etc. Please be assured.


Machine Learning with Mahout Certification Training