Machine Learning Training in Chennai


Machine learning is a newly emerging AI (Artificial Intelligence) based technology where a software application runs the sequential tasks in an intelligent and independent manner. R programming can be used to create customized analytics and data manipulation modules within the Machine Learning environment.

Machine Learning is simply making a computer perform a task without explicitly programming it. In today’s world every system that does well has a machine learning algorithm at its heart. Take for example Google Search engine, Amazon Product recommendations, LinkedIn, Facebook etc. All these systems have machine learning algorithms embedded in their systems in one form of the other. They are efficiently utilizing data collected from various channels which helps them get a bigger picture of what they are doing and what they should do.

This course provides learners the best combination of theory and practical aspects of machine learning along with relevant case studies, making it a crisp and hands-on programme.

Machine Learning training is available in various formats, including onsite live training and live instructor-led training using an interactive, remote desktop setup. Local Machine Learning training can be carried out live on customer premises or in Softlogic training centers.

More about Machine Learning Training

  • High and effective throughputs can be easily achieved in AI based application via statistical and predictive machine learning algorithms and analysis to the existing data.
  • Five phases of Machine Learning are data collection, data preparation, data modeling, data model testing and performance monitoring.
  • Healthcare domain, face recognition, tagging features in social networks and spam detection of mailboxes are some of the real-time environments where the Machine learning has been applied.
  • Softlogic Systems is the best Machine Learning training center in Chennai where you will be exposed to differentiated learning environment as the course syllabus has been prepared by the highly experienced professionals. With this course, you can learn about statistics, workflow of R tool, data mining, reporting/visualization, fundamental of SQL, classified algorithms, supervised, unsupervised machine learning algorithms and lot more. Please check below for the detailed syllabus.

Prerequisites for Machine Learning Training

  • Basic knowledge of any programming language and statistics.
  • If you are already familiar with the above, this course will be quite easy for you to grasp the concepts. Otherwise, experts are here to help you with machine learning from the basics.

Machine Learning Course Fee and Duration

Training Mode

Regular Track

45 – 60 Days

2 hours a day

Live Classroom

Weekend Track

8 Weekends

3 hours a day

Live Classroom

Fast Track

5 Days

6+ hours a day

Live Classroom

This is an approximate course fee and duration for Machine Learning. Please contact our team for current Machine Learning course fee and duration.

Machine Learning Training Course Syllabus

Module 1 – Core Java Fundamentals

  • Java Programming Language Keywords
  • Literals and Ranges of All Primitive
  • Data Types
  • Array Declaration, Construction, and Initialization

Module 2 – Declarations and Access Control

  • Declarations and Modifiers
  • Declaration Rules
  • Interface Implementation

Module 3 – Object Orientation, Overloading and Overriding, Constructors

  • Benefits of Encapsulation
  • Overridden and Overloaded Methods
  • Constructors and Instantiation
  • Legal Return Types

Module 4 – Flow Control, Exceptions, and Assertions

  • Writing Code Using if and switch statements
  • Writing Code Using Loops
  • Handling Exceptions
  • Working with the Assertion Mechanism
  • Write Java Programs

Module 5 – TestNG

  • Setting up TestNG
  • Testing with TestNG
  • Composing test and test suites
  • Generating and analyzing HTML test reports
  • Troubleshooting

Module 6 – Machine Learning 

  • Introducing Machine Learning
  • To Automate or Not to Automate?
  • Test Automation for Web Applications
  • Machine Learning Components
  • Supported Browsers
  • Flexibility and Extensibility

Module 7 – Machine Learning -IDE

  • Introduction
  • Installing the IDE
  • Opening the IDE
  • IDE Features
  • Building Test Cases
  • Running Test Cases
  • Debugging
  • Writing a Test Suite
  • Executing Machine Learning -IDE Tests on Different Browsers

Module 8 – XPATH

  • Understanding of Source files and Target
  • XPATH and different techniques
  • Using attribute
  • Text ()
  • Following

Module 9 – Machine Learning 

  • Introduction
  • How Machine Learning Works
  • Installation
  • Configuring Machine Learning With Eclipse
  • Machine Learning RC Vs Machine Learning
  • Programming your tests in WebDriver
  • Debugging WebDriver test cases
  • Troubleshooting
  • Handling HTTPS and Security Pop-ups
  • Running tests in different browsers
  • Handle Alerts / Pop-ups and Multiple Windows using WebDriver

Module 10 – Automation Test Design Considerations

  • Introducing Test Design
  • What to Test
  • Verifying Results
  • Choosing a Location Strategy
  • UI Mapping
  • Handling Errors
  • Testing Ajax Applications
  • How to debug the test scripts

Module 11 – Handling Test Data

  • Reading test data from excel file
  • Writing data to excel file
  • Reading test configuration data from text file
  • Test logging
  • Machine Learning Grid Overview

Module 12 – Building Automation Frameworks Using Machine Learning 

  • What is a Framework
  • Types of Frameworks
  • Modular framework
  • Data Driven framework
  • Keyword driven framework
  • Hybrid framework
  • Use of Framework
  • Develop a framework using TestNG/WebDriver