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[Udemy Black Friday 97 off] Decision Tree – Theory, Application and Modeling using R Coupon

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Last updated on 17th January 2022 3:26 am

[Udemy Black Friday 97 off] Decision Tree – Theory, Application and Modeling using R Coupon

What you’ll learn

  • Get Crystal clear understanding of decision tree
  • Understand the business scenarios where decision tree is applicable
  • Become comfortable to develop decision tree using R statistical package
  • Understand the algorithm behind decision tree i.e. how does decision tree software work
  • Understand the practical way of validation, auto validation and implementation of decision tree

What is this course?

Decision Tree Model building is one of the most applied technique in analytics vertical. The decision tree model is quick to develop and easy to understand. The technique is simple to learn. A number of business scenarios in lending business / telecom / automobile etc. require decision tree model building.

This course ensures that student get understanding of

  • what is the decision tree
  • where do you apply decision tree
  • what benefit it brings
  • what are various algorithm behind decision tree
  • what are the steps to develop decision tree in R
  • how to interpret the decision tree output of R

Course Tags

  • Decision Tree
  • CART
  • Objective segmentation
  • Predictive analytics
  • ID3
  • GINI

Material in this course

  • the videos are in HD format
  • the presentation used to create video are available to download in PDF format
  • the excel files used is available to download
  • the R program used is also available to download

How long the course should take?

It should take approximately 8 hours to internalize the concepts and become comfortable with the decision tree modeling using R

The structure of the course

Section 1 – motivation and basic understanding

  • Understand the business scenario, where decision tree for categorical outcome is required
  • See a sample decision tree – output
  • Understand the gains obtained from the decision tree
  • Understand how it is different from logistic regression based scoring

Section 2 – practical (for categorical output)

  • Install R – process
  • Install R studio – process
  • Little understanding of R studio /Package / library
  • Develop a decision tree in R
  • Delve into the output

Section 3 – Algorithm behind decision tree

  • GINI Index of a node
  • GINI Index of a split
  • Variable and split point selection procedure
  • Implementing CART
  • Decision tree development and validation in data mining scenario
  • Auto pruning technique
  • Understand R procedure for auto pruning
  • Understand difference between CHAID and CART
  • Understand the CART for numeric outcome
  • Interpret the R-square meaning associated with CART

Section 4 – Other algorithm for decision tree

  • ID3
  • Entropy of a node
  • Entropy of a split
  • Random Forest Method

Why take this course?

Take this course to

  • Become crystal clear with decision tree modeling
  • Become comfortable with decision tree development using R
  • Hands on with R package output
  • Understand the practical usage of decision tree

Who this course is for:

  • Data Mining professionals
  • Analytics professionals
  • People seeking job in analytics industry

Course content

  • Introduction to decision tree
  • 1 A : Model Design – Ensure actionable data for modeling
  • Demo of Decision Tree development using R
  • Algorithm behind decision tree
  • Other algorithm of decision tree development

5 reviews for [Udemy Black Friday 97 off] Decision Tree – Theory, Application and Modeling using R Coupon

4.5 out of 5
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  1. Vinicius Motta

    Amazing course. Fantastic and useful examples of what can be done with each lessons topic. Angela took her time to set the bar high with regards to real world examples that can be achieved with python.

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  2. Ethan Zerad

    I’ve had a good experience with this course. I learned a lot, Angela went deep diving into some of the more complex concepts and broke them down into pieces, that evantually led to these so-called complex topics become simply easy. This easily deserves 5 stars, being able to understand how things work, using documentation and just the process of developing, is something rare, but this course provides you with it, and that deserves 5 starts.

    Now, that was the pro, let’s get to the con. I was tempted to give this course 4.5 stars, but evantually made it 5 because of the amazing explanations that led me to understand some topics I thought were so complex before. Why did I want to give it 4.5 stars? Well, because of the Data Science part, in days 71-80, you get pre-made documents with explanations and learn Data Science, and sure, maybe Angela wants to challenge you, but that’s the wrong topic to choose to challenge a programmer. This topic is complex, it’s frustrating, and hanging us out to dry with it is not helpful, whatsoever, I ended up feeling really insecure after this part. And maybe that’s just me, maybe other people understood it better, but I believe that this topic deserved some videos and explanation, so we could understand how things tick. However, this course is still 100% worth buying, it’s just that the last part of this course felt like it was already too far with the “deal with it” part of the course. I hope I’ll be able to understand Data Science and actually enjoy it at one point, but this, didn’t provide what I needed to understand the topic and enjoy it, it led to me being frustrated and doubtful about my ability, and some of you might say, “that’s just a part of being a programmer”, well, it is, but with this being a course, and with Data Science being a new topic, I believe that it deserves more explanation and videos that could help us see what is going on behind the scenes.

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  3. Anubhav Singh Rathore

    Course is really good. It is very engaging. Learning wise its amazing and flawless. But, I feel if, It could provide some kind of placement assistance as well because getting job in India is another struggle.

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  4. Bavan M Y

    pros :- 1. good way of teaching
    2. useful exercises in every modules
    3. different topics covered

    1. Python taught here is only of beginner level. basically you are taught all you need to start learning a framework or anything related to python , but it isn’t touching any intermediate or advance topics. there is a lot more in python than just what is taught here .

    2. you get to become jack of all trades ,but master of none. you learn many different topics , but nothing is in depth as it should have been , including python itself
    3. Teacher doesn’t reply no matter how many doubts you have, I guess this goes with evey course of angela.

    4. way too long than it has to be .
    I literally didn’t feel like continuing this course anymore ,lessons are long enough to make a beginner discontinue it. I completed the rest of my python journey from youtube and that’s where I found out that this course is missing way too many things.

    5. save time by watching every lesson in 1.5x speed. this isn’t an issue until you reach intermediate level in this course.

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  5. Brendon Meintjes

    Loved the course and it’s structure of doing something new everyday and tackling it one piece at a time. Also nice to be able to build so many apps so that you can actually see what you are learning, loads of practical to support the theory

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