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Decision Tree Modeling Using R Certification Training ( S028 )

4.5 + (25,859) Students Ratings

IQ’s Decision Tree Modeling course using R platform is designed to make you an expert by mastering concepts like Data design, Regression Tree, Pruning and various algorithms like CHAID, CART, ID3, GINI, and Random forest.

Course Price :

₹5,174
₹5,749
10%
off

Live Instructor

Available

Self Paced

Think Bigger Advantage

Live Online Classes

All our Classes are Live Instrucotor led online sessions. You can attend at the comfort of your place and Login to our Classes.

LMS (Learning Management System)

LMS will help you to organize your all training material, session videos and review at later date. You can access LMS anytime and review your completed classes. If you miss any class, then you can review the missed class in LMS.

Flexible Schedule

For some reasons, you can not attend the Classes, we can enroll you in the next possible classes. we assure flexibility in class schdules.

Lifetime Access to Learning Platform

You will get Lifetime free access to LMS(Learning Mangement System) You can access all Videos, class room assignments, quizzes, Projects for Life time. You will also get free video sessions for Life time.

Highest Completion Rate

We have the highest course completion rate in the Industry. If you miss a class, you can opt for the missed class in different batch. We assure you the best training possible for you to succeed.

Certificate of Completion

We provide you the Industry recognized Certification of Course completion This certificate will sometimes helps you to get reimbursement of training expenses by your company.

Training Schedule
Batch Start Date Days of Training Weekday/ Weekend Timings
 
 
 
 
 

Course Curriculum

Learning Objectives: This module helps you to learn what is a Decision Tree and what are its benefits. Also, know what are the core objectives of Decision Tree modeling, how to understand the gains from the Decision Tree, and how does one apply the same in business scenarios.

Topics:

  • What is the Objective of Decision Tree modeling
  • Explain Anatomy of a Decision Tree
  • Explain Gains from a decision tree (KS calculations)
  • Understand the definitions related to objective segmentations

Learning Objectives: This module will help you to understand how to design the data for modeling.

Topics:

  • Describe Historical window
  • Describe Performance window
  • Understand how to decide performance window horizon using Vintage analysis
  • Explain the general precautions related to data design

LearningObjectives: This module will help you to understand how to ensure a Data Sanity check and you will also learn to perform the necessary checks before modeling.

Topics:

  • Contents of Data sanity check
  • Define View
  • Describe Frequency Distribution
  • Evaluate Means / Uni-variate
  • Explain Categorical variable treatment
  • Explain Missing value treatment guideline
  • Explain capping guideline

Learning Objectives: This module helps you to know how to use R and the Algorithm to develop the Decision Tree. 

Topics:

  • Preamble to data
  • Learn to install R package and R studio
  • Know how to develop first Decision Tree in R studio
  • Find the strength of the model
  • Describe Algorithm behind Decision Tree
  • Explain how a Decision Tree is developed
  • Understand First on Categorical dependent variable
  • Describe the GINI Method
  • Explain the steps taken by software programs to learn the classification (develop the tree)
  • Assignment on decision tree

Learning Objectives: This module helps you to understand how Classification trees are developed, validated, and used in the industry 

Topics:

  • Discussion on assignment
  • Find the strength of the model
  • Explain the steps taken by a software program to implement the learning on unseen data
  • Learn more from a practical point of view
  • Explain Model Validation and Deployment

Learning Objectives: This module helps you to learn the advance stopping criteria of a decision tree. Also, know how to develop Decision Trees for numerous outcomes.

Topics:

  • Pruning - Introduction
  • What are the steps of Pruning
  • Explain the Logic of pruning
  • Explain K fold validation for the model
  • How to implement Auto Pruning using R
  • How to develop Regression Tree
  • Learn to Interpret the output
  • Understand how it is different from Linear Regression
  • Explain the advantages and disadvantages of Linear Regression
  • Explain Another Regression Tree using R

Learning Objectives: This module helps you to understand what is Chi-square and CHAID and their working and also the difference between CHAID and CART, etc.. 

Topics:

  • What are the key features of CART
  • Explain Chi-square statistics
  • Learn to implement Chi-square for decision tree development
  • Describe Syntax for CHAID using R
  • Evaluate CHAID vs CART

Learning Objectives: This module helps you to understand about ID3, Entropy, Random Forest and Random Forest using R 

Topics:

  • Explain Entropy in the context of the decision tree
  • Describe ID3
  • Explain the Random Forest Method and Using R for Random forest method
  • Project work 
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Course Details

Upon completion of this Decision Tree Modeling course, you should be able to:

  1. Know about the Anatomy of a Decision Tree
  2. Know how to use the R platform to develop Decision Trees
  3. Understand how to apply various Decision Tree techniques (CHAID / CART etc.)
  4. Know how to perform Decision Tree Model Validation
  5. Understand where to use CHAID / CART / ID3,etc.
  6. Learn how to design data for Decision Tree modeling
  7. Learn to interpret and implement the Decision Tree model
  8. Learn to implement Decision Trees to derive business insights.

This course is best suitable for the professionals who want to learn Decision Tree modeling and apply the modeling techniques using R. They are:

  1. Developers who want to step-up as Data Scientists
  2. Analytics Consultants
  3. R / SAS / SPSS Professionals
  4. Data Analysts
  5. Information Architects and Data Engineers
  6. Statisticians

The prerequisite for this course is the basic knowledge of R programming language. This course only explains those R programming syntaxes which are required for the Decision Tree model development.

Decision Tree Modeling Using R Certification Training Ceritficate

Decision Tree Modeling Using R Certification Training Reviews

25,859

Total number of reviews

4.5

Aggregate review score

80%

Course completion rate

Decision Tree Modeling Using R Certification Training Features

Live Online Classes

All our Classes are Live Instructor led online sessions. You can attend at the comfort of your place and Login to our Classes.

LMS (Learning Management System)

LMS will help you to organize your all training material, session videos and review at later date. You can access LMS anytime and review your completed classes. If you miss any class, then you can review the missed class in LMS.

Flexible Schedule

For some reasons, you can not attend the Classes, we can enroll you in the next possible classes. we assure flexibility in class schedules.

Lifetime Access to Learning Platform

You will get Lifetime free access to LMS(Learning Mangement System) You can access all Videos, class room assignments, quizzes, Projects for Life time. You will also get free video sessions for Life time.

Highest Course Completion Rate

We have the highest course completion rate in the Industry. If you miss a class, you can opt for the missed class in different batch. We assure you the best training possible for you to succeed.

Certificate of completion

We provide you the Industry recognized Certification of Course completion This certificate will sometimes helps you to get reimbursement of training expenses by your company.

Like the course? Enroll Now

Structure your learning and get a certificate to prove it.

Decision Tree Modeling Using R Certification Training FAQs

You will never miss a class at IQ Online Training! You can choose either of the two options:

  1. View the recorded session of the class available in your LMS or
  2. You can attend the missed session in any other live batch.

After the enrolment, the LMS access will be instantly provided to you able to access for lifetime which includes complete set of previous class recordings/PPTs/PDFs/assignments. You can start learning right away.

Your access to the Support Team is for lifetime. Our team will help you in resolving queries, during and after the course.

Yes, once enrollment has done for course. Access to the course material will be available for lifetime.

You can Call our support numbers listed in site OR Email us at info@iqtrainings.com.

You can view in-depth class sample recordings before the enrollment. Experience the complete learning instead of a demo session with our expertise.

All the instructors are Industry experts with minimum 10-12 yrs of relevant IT experience. They are subject matter experts and are well trained for providing an awesome learning experience to the participants.

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