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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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Learning Objectives - In this module, you will understand What is a Decision Tree and what are the benefits. What are the core objectives of Decision Tree modelling, How to understand the gains from the Decision Tree and How does one apply the same in business scenarios
Topics - Decision Tree modeling Objective, Anatomy of a Decision Tree, Gains from a decision tree (KS calculations), and Definitions related to objective segmentations
Learning Objectives - In this module, you will learn how to design the data for modelling
Topics - Historical window, Performance window, Decide performance window horizon using Vintage analysis, General precautions related to data design
Learning Objectives - In this module, you will learn how to ensure Data Sanity check and you will also learn to perform the necessary checks before modelling
Topics - Data sanity check-Contents, View, Frequency Distribution, Means / Uni-variate, Categorical variable treatment, Missing value treatment guideline, capping guideline
Learning Objectives - In this module, you will learn to use R and the Algorithm to develop the Decision Tree.
Topics - Preamble to data, Installing R package and R studio, Developing first Decision Tree in R studio, Find strength of the model, Algorithm behind Decision Tree, How is a Decision Tree developed?, First on Categorical dependent variable, GINI Method, Steps taken by software programs to learn the classification (develop the tree), Assignment on decision tree
Learning Objectives - In this module you will understand how Classification trees are Developed, Validated and Used in the industry
Topics - Discussion on assignment, Find Strength of the model, Steps taken by software program to implement the learning on unseen data, learning more from practical point of view, Model Validation and Deployment.
Learning Objectives - In this module you will understand the Advance stopping criteria of a decision tree. You will also learn to develop Decision Trees for numerous outcomes.
Topics - Introduction to Pruning, Steps of Pruning, Logic of pruning, Understand K fold validation for model, Implement Auto Pruning using R, Develop Regression Tree, Interpret the output, How it is different from Linear Regression, Advantages and Disadvantages over Linear Regression, Another Regression Tree using R
Learning Objectives - In this module you will learn what is Chi square and CHAID and their working and also the difference between CHAID and CART etc..
Topics - Key features of CART, Chi square statistics, Implement Chi square for decision tree development, Syntax for CHAID using R, and CHAID vs CART.
Learning Objectives - In this module you will learn about ID3, Entropy, Random Forest and Random Forest using R
Topics - Entropy in the context of decision tree, ID3, Random Forest Method and Using R for Random forest method, Project work
Edureka has been an unique and fulfilling experience. The course contents are up-to-date and the instructors are industry trained and extremely hard working. The support is always willing to help you out in various ways as promptly as possible. Edureka redefines the way online training is conducted by making it as futuristic as possible, with utmost care and minute detailing, packaged into the a unique virtual classrooms. Thank you Edureka!
Very good courses covering lots of topics. Excellent class delivery and lecture notes. I really learnt a lot and will surely miss not having the classes any more. I will definitely keep in touch with edureka! and my instructor through LinkedIn and emails. I would also like to convey my special thanks to the edureka! support team for their prompt technical support that is available 24/7 and for their awesome Learning Management System (LMS) on the website with all the class recordings and the material.
Clean, simple and a fantastic learning resource. The courses are a great resource for personal development and continual learning. They are well structured and provided both ease of access and depth while allowing you to go at your own pace.Support team people is also really very cooperative and helps out at there best.
Let me start of by congratulating the entire Edureka team for putting together such an amazing content for their courses. I am enrolled in their self paced and live batches courses and my learning experience has been phenomenal. I tried learning Linux Administration on my own but in every attempt i hit a dead end. However, I learned Linux Administration from the very best. The quality and experience of the instructor are excellent and this reflects in his high quality post lecture hands on projects and assignments. I must also take this opportunity to thank the support staff for prompt doubt solving via their student forums. I am a permanent member of theirs and will continue to learn from Edureka.
I am a Customer at Edureka. I attended the AWS Architect Certification Training, I found the training to be very informative. The course content was excellent, just what I was after. The trainer was very knowledgeable. I found him to be very patient, he listened and answered everyone's questions. I especially liked the way he repeated and summarised the previous day's leanings at the start of each new day. I also liked his interactive style of training. Edureka demonstrated the highest standard of professionalism in delivering the course content and their support to me in helping complete the project has been exceptional. Thanks Edureka!
I'm currently enrolled in a lot of courses offered at Edureka, so I'm attending live classes and using their study materials, course projects, have access to support staff and teachers. I can confidently say Edureka staff is very hard working and committed to help students which is reliable. Course instructors are experienced candidates from industry who know what they are teaching. Course materials are pretty comprehensive and students need to work very hard to finish course projects, pass the project interviews and gain certification. I say, it is worth it.