Post Top Ad

Tuesday, 19 March 2019

Data Mining with RapidMiner.. udemy 100% free course

Free udemy course.............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.
Business
Data Mining with RapidMiner

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
  1. Getting Started
  2. Getting Started 2
  3. Data Mining Process
  4. Download Data Set
  5. Read CSV
  6. Data Understanding: Statistics
  7. Data Understanding: Scatterplot
  8. Data Understanding: Line
  9. Data Understanding: Bar
  10. Data Understanding: Histogram
  11. Data Understanding: BoxPLot
  12. Data Understanding: Pie
  13. Data Understanding: Scatterplot Matrix
  14. Data Preparation: Normalization
  15. Data Preparation: Replace Missing Values
  16. Data Preparation: Remove Duplicates
  17. Data Preparation: Detect Outlier
  18. Modeling: Simple Linear Regression
  19. MOdeling: SImple Linear Regression using RapidMiner
  20. MOdeling: KMeans CLustering
  21. Modeling: KMeans Clustering using RapidmIner
  22. Modeling: Agglomeration CLustering
  23. Modeling: Agglomeration Clustering using RapidmIner
  24. Modeling: Decison Tree ID3 Algorithm
  25. Modeling: Decision Tree ID3 Algorithm using RapdimIner
  26. Modeling: Decison Tree ID3 Algorithm using RapidMiner
  27. Evaluation: Decsion Tree ID3 Algorithm using RapidmIner
  28. MOdeling: KNN Classification
  29. Modeling: KNN CLassification using RapidmIner
  30. Evaluation: KNN Classification using RapidmIner
  31. Modeling Naive BAyes CLassification
  32. MOdeling: Naive Bayes Classification using RapidmIner
  33. Evaluation: Naive Bayes Classification using RapidMIner
  34. MOdeling: Neural Network Classification
  35. Modeling: Neural Network Classification using RapidmIner
  36. Evauation: Neural Network Classification using RapidmIner
  37. What Algorithm to USe?
  38. MOdel Evaluation
  39. k fold cross validation using RapdimIner
Who this course is for:
  • Beginner Data Scientist or Analyst interested in RapidMiner
  • Get the course

No comments:

Post a Comment