Summary

 

 

Course Code: DS-ML

Duration :45 Hours

Technology: Data Science

Delivery Method: Instructor-led (Classroom)

Training Credits: N/A

Audience: Data: Fresh graduates

Machine Learning Training Course


Join Best Machine Learning Training in Mississauga

Our Machine Learning Training has been designed by associate chief data scientists at IPGenius. In addition to machine learning algorithms, you can also learn to use machine learning’s real-time use cases and their implementation using Python, in our training

Introduction

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. Rprogramming 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 programmer.

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 Mississauga 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.
  • IPGenius is the best Machine Learning training center in Mississauga 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.

Target Audience

Anyone interested in artificial intelligence and how it can be used to solve many problems

Prerequisites

Before attending this course, delegates must have:

  • 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.

Course Objectives

The objectives of the course “Machine Learning” is to introduce students to state-of-the-art methods and modern programming tools for data analysis.

Learning outcomes

After completing the study of the discipline “Machine Learning ”, the students are expected to:

  • understand complexity of Machine Learning algorithms and their limitations;
  • understand modern notions in data analysis oriented computing;
  • be capable of confidently applying common Machine Learning algorithms in practice and implementing their own;
  • be capable of performing distributed computations;
  • be capable of performing experiments in Machine Learning using real-world data

Course Content


Lesson 1: Core Java Fundamentals

 

Lesson 2: Declarations and Access Control

Lesson 3: Object Orientation, Overloading and Overriding, Constructors

Lesson 4: Flow Control, Exceptions, and Assertions

Lesson 5: TestNG

Lesson 6: Machine Learning

Lesson 7: Machine Learning -IDE

Lesson 8: XPATH

Lesson 9: Machine Learning

Lesson 10: Automation Test Design Considerations

Lesson 11: Handling Test Data

Upon successful completion of this course, delegates will receive an IPGenius IT course attendance certificate.