3 Days Live Virtual Training on Data Science with R Certification
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Training TypeLive Training
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CategoryR Language
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Duration15 Hours
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Rating4.9/5
Data Science with R Certification Course Online Introduction
About Data Science with R Certification Course Online
The Data Science with R Certification course enables you to take your data science skills into a variety of companies, helping them analyze data and make more informed business decisions. The course covers data exploration, data visualization, predictive analytics, and descriptive analytics techniques with the R language. You will learn about various data structures in R, various statistical concepts, cluster analysis, Regression and classification. In this curriculum we will have in-depth mathematical understanding of the algorithms from the basics.
Data Science with R Certification Course Online Objective
- Install R, Rstudio, and learn about the various R packages
- Gain an in-depth understanding of data structure used in R and learn to import/export data in R
- Define, understand and use the various functions in R
- Learn to do data visualization using ggplot2 packages
- Gain a basic understanding of various statistical concepts
- Understand and use the hypothesis testing method to drive business decisions
- Understand and use linear and non-linear regression models, and classification techniques for data analysis
- Learn and use the various association rules with the Apriori algorithm
- Learn and use clustering methods including k-means, DBSCAN, and hierarchical clustering
Who is the R Certification Course Target Audience?
This course is meant for all those students and professionals who are interested in using the R’s powerful ecosystem
What Basic Knowledge Required to Learn Data Science with R Certification
There are no prerequisites
Available Batches
Pricing
Require a Different Batch?
Request a Batch For
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Missing Data
Categorical Data
Feature Scaling
Data Split (Test and Training Set)
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Simple Linear Regression
Multiple Linear Regression
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Logistic Regression
K Nearest Neighbours (K-NN)
Support Vector Machine (SVM)
Navie Bayes
Decision Tree Classification
Random Forest Classification
XGBoost
Regularization in Logistic Regression
Understanding different hyper parameters
Accuracy measures
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K Means
Hierarchical Clustering
DBScan
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Apriori
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K Fold Technique
Grid Search