Data Mining with RapidMiner

This is the bite size course to learn Data Mining using RapidmIner. This course uses CRISP DM data mining process.

You will learn RapidMiner to do data understanding, data preparation, modeling, Evaluation. You will be able to train your own prediction models with naive bayes, decision tree, knn, neural network, linear regression, and evaluate your models very soon after learning the course.

You can take the course as follow and you can take an exam at EMHAcademy to get SVBook Advance Certificate in Data Science using DSTK, Excel, RapidMiner:

• Introduction to Data and Text Mining using DSTK 3
• Data Mining with RapidMiner
• Learn Microsoft Excel Basics Fast
• Learn Data Aalysis using Microsoft Excel Basics Fast

Content:

• Getting Started
• Getting Started 2
• Data Mining Process
• Download Data Set
• Read CSV
• Data Understanding - Statistics
• Data Understanding - Scatterplot
• Data Understanding - Line
• Data Understanding - Bar
• Data Understanding - Histogram
• Data Understanding - BoxPLot
• Data Understanding - Pie
• Data Understanding - Scatterplot Matrix
• Data Preparation - Normalization
• Data Preparation - Replace Missing Values
• Data Preparation - Remove Duplicates
• Data Preparation - Detect Outlier
• Modeling - Simple Linear Regression
• MOdeling - SImple Linear Regression using RapidMiner
• MOdeling - KMeans CLustering
• Modeling - KMeans Clustering using RapidmIner
• Modeling - Agglomeration CLustering
• Modeling - Agglomeration Clustering using RapidmIner
• Modeling - Decison Tree ID3 Algorithm
• Modeling - Decision Tree ID3 Algorithm using RapdimIner
• Modeling - Decison Tree ID3 Algorithm using RapidMiner
• Evaluation - Decsion Tree ID3 Algorithm using RapidmIner
• MOdeling - KNN Classification
• Modeling - KNN CLassification using RapidmIner
• Evaluation - KNN Classification using RapidmIner
• Modeling Naive BAyes CLassification
• MOdeling - Naive Bayes Classification using RapidmIner
• Evaluation - Naive Bayes Classification using RapidMIner
• MOdeling - Neural Network Classification
• Modeling - Neural Network Classification using RapidmIner
• Evauation - Neural Network Classification using RapidmIner
• What Algorithm to USe?
• MOdel Evaluation
• Kfold cross validation using RapdimIner

Basic knowledge:

• Basic COmputer Knowledge

Beginner Data Scientist or Analyst interested in RapidMiner.

Course Completion Certificate

What will you learn:

• Data Mining using RapidMIner

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