Decision Tree is a popular tree based algorithm that has pre-defined target variables. It is compatible with continuous and categorical input and output variables. The basic concept is to split the data into simple and homogeneous sets, into a form of tree branching. The Decision Tree modeling using R is much simpler.
The Decision Tree modeling using R comes as a certification course that enables you to upgrade yourself to be a better Data analyst and could even be a Data Scientist in the future. This may consider as the stepping stone. At the end of the course, you will be better skilled to be a Predictive analytics expert.
What is Decision Tree Modeling using R certification?
The Decision Tree modeling using R certification is the way to know what is Decision Tree model, how to use it, where to use it and how to get the maximum and accurate prediction out of the data. It updates you with many of the advanced concepts and data designing through the curriculum.
Simply knowing something is not the end of it. You need to know how to, when and where to use it properly. This is what you will have with this certification training course.
The pre-requisite for this course is that you need to have some knowledge about R programming.
The course objectives
Decision Tree can be implemented in various business fields. It is quick to understand, develop and easier to implement.
- Understand clearly about the Decision Tree model
- Learn how to use R for the decision tree
- The benefits of learning the technique
- Learn about techniques like CHAID, GINI, CART, ID3 etc on the go
- Applying the decision tree techniques
- Perform the validation
- How to interpret and implement the Decision tree model
- How to derive business insights with this technique
- Understanding of predictive analytics and Objective segmentation
Why take the Decision Tree modeling using R certification course?
This training course will make you have a clearer picture of Decision Tree model and the hands on experience with the R program. It provides you some practical experience with the various cases where the technique is used. It makes you comfortable with the technique and makes you feel familiar with it.
Moreover, the course puts some light on the core analytics work, the benefits of modeling, and how to validate over the time with these techniques. Decision Tree Model developing using R technique is a popular platform and you will have the real-time experience with it to implement in your work field.
Who needs to do Decision Tree modeling using R certification training?
Decision Tree model can be used in various fields. People working in these areas can benefit with this training course.
- Developers who want to be a Data Scientist
- Analytics Consultants
- Data Analysts
- Professionals working with R, SAS, SPSS etc
- Data Engineers
- Information architects
All of these people can learn Decision Tree model and apply this technique using R in their respective fields.
The best Decision Tree modeling using R certification training courses
Edureka Decision Tree modeling using R
Edureka Decision Tree Modeling using R is an online self-paced course. It is a low-cost course offered for individuals mainly. It may be available for companies on request for their employees.
The course is done through videos, PPTs, assignments and project activities. You may complete it at your convenience and need not hurry. You may take your time to understand the concept and be thorough.
- There is no time limit for the course and is completed at your speed.
- There will be real life case studies that make you familiar with the real projects and how to apply the learned concepts.
- You can access the provided study materials for lifelong and can also access the discussion forum for the learning period or for reference, anytime in the future as well. You can share your experience, doubts, or queries with the fellow students and experts in the discussion forum.
- There will be assignments at the end of each module.
- As soon as you sign up, you will get the study materials and access to them.
- At the end of the course, you will be asked to a project based on the provided topics. Experts will review your project and if successful, you will be awarded the certificate.
- There is no job placements assistance but the Edureka certification is valid for many of the leading MNCs.
TO do the project, you will need the Edureka’s Virtual Machine in your system. This will give you local access. The installation guide is provided in the LMS and you can do the rest. The project will be given to you and you need to do it in the installed program.
There will be a total of 8 modules for the Decision Tree modeling using R certification.
- Introduction to Decision Tree
- Data Design for Modeling
- Data treatment before Modeling
- Classification of Tree Development and Algorithm details
- Industry practice of Classification tree-Development, Validation, and Usage
- Regression Tree and Auto Pruning
- CHAID Algorithm- You will be working with CHAID, CART, Chi square statistics, Implement Chi square in Decision Tree etc.
- Other Algorithm- You will learn about the ID3, Random Forest Method and use of R for this method
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Udemy- Decision Tree Theory, Application, and Modeling using R
Udemy Decision Tree- Theory, Application and Modeling using R is also a self-paced training course. The total duration of the videos provided for the course is 8 hours. These 8 hours are split for the different modules of the curriculum.
- Udemy offers a 30-day money back guarantee for those who are not happy or satisfied with the course. They may request the refund after the first class.
- The on-demand videos run for a total of 6 hours
- There is also the availability of 14 supplemental resources to help with the course
- You will have full-time access to all the study materials and can be referred to, anytime in the future.
- The videos have accessibility on mobiles and TV as well
- At the end of the course, you will be given a certificate of completion
There are 5 modules for the course at Udemy. The modules are split into several lectures as well.
- Introduction to Decision tree takes up to 10 lectures and 45 minutes
- Model Design- Ensure actionable data for modeling will be 38 minutes and 6 lectures. The first 2 modules bring about the basic understanding of this technique and there will be samples given.
- Demo of Decision Tree development using R will be 12 lectures and runs for 1 hour 10 minutes. The second section will need the installation of R studio program. Here you will know how to develop decision tree with this tool
- The Algorithm behind decision tree will be 2 hours 54 minutes long and takes up to 29 lectures. The algorithm section explains about GINI, variable split, CART, R-square etc.
- Other algorithm of decision tree development is 22 minutes long and 9 lectures. The section 4 deals with other algorithms like ID3, entropy, random forest method etc.
The course is simple and easy to understand. There is support to clear any doubts. There will be business scenarios from various fields to have a better understanding of how to use the Decision tree modeling using R. Moreover, the reviews reveal that the instructor is well versed and through in the field and is considered the best in the business.