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Data Science with R Training In Jalandhar

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Data Science with R Training In Jalandhar

Learn Data Science with R Training in Jalandhar with R, Python, Excel, SAS, and Tableau tool from Data Science Certified Experts. Call 9914077736 for more details about Data Science Course fees, Certification, Placements, Real-time Projects in Jalandhar City. We Rated as Best Data Science with R Training Provider in Jalandhar with 100% Job Assistance for our Students. In this course, we Cover Statistics, hypothesis testing, Machine Learning, AI Concepts, Deep Learning, Data Science algorithm, and Analytics Concepts.


Data Science with R Training Syllabus in Jalandhar

Module 1: Introduction to Data Science 

  • What is Data Science?
  • What is Machine Learning?
  • What is Deep Learning?
  • What is AI?
  • Data Analytics & it’s types

Module 2: Introduction to R 

  • What is R?
  • Why R?
  • Installing R
  • R environment
  • How to get help in R
  • R Studio Overview

Module 3: R Basics 

  • Environment setup
  • Data Types
  • Variables Vectors
  • Lists
  • Matrix
  • Array
  • Factors
  • Data Frames
  • Loops
  • Packages
  • Functions
  • In-Built Data sets

Module 4: R Packages 

  • DMwR
  • Dplyr/plyr
  • Caret
  • Lubridate
  • E1071
  • Cluster/fpc
  • table
  • Stats/utils
  • Ggplot/ggplot2
  • Glmnet

Module 5: Importing Data 

  • Reading CSV files
  • Saving in Python data
  • Loading Python data objects
  • Writing data to csv file

Module 6: Manipulating Data 

  • Selecting rows/observations
  • Rounding Number
  • Selecting columns/fields
  • Merging data
  • Data aggregation
  • Data munging techniques

Module 7: Statistics Basics 

  • Central Tendency
  • Mean
  • Median
  • Mode
  • Skewness
  • Normal Distribution
  •  Probability Basics
  • What does mean by probability?
  • Types of Probability
  • ODDS Ratio?
  • Standard Deviation
  • Data deviation & distribution
  • Variance
  • Bias variance Trade off
  • Underfitting
  • Overfitting
  • Distance metrics
  • Euclidean Distance
  • Manhattan Distance
  • Outlier analysis
  • What is an Outlier?
  • Inter Quartile Range
  • Box & whisker plot
  • Upper Whisker
  • Lower Whisker
  • Scatter plot
  • Cook’s Distance
  • Missing Value treatments
  • What is a NA?
  • Central Imputation
  • KNN imputation
  • Dummification
  • Correlation
  • Pearson correlation
  • Positive & Negative correlation

Module 8: Error Metrics 

  • Classification
  • Confusion Matrix
  • Precision
  • Recall
  • Specificity
  • F1 Score
  • Regression
  • MSE
  • RMSE
  • MAPE

Module 9: Machine Learning

Module 10: Supervised Learning 

  • Linear Regression
  • Linear Equation
  • Slope
  • Intercept
  • R square value
  •  Logistic regression
  • ODDS ratio
  • Probability of success
  • Probability of failure
  • ROC curve
  • Bias Variance Tradeoff

Module 11: Unsupervised Learning 

  • K-Means
  • K-Means ++
  • Hierarchical Clustering

Module 12: Machine Learning using R 

  • Linear Regression
  • Logistic Regression
  • K-Means
  • K-Means++
  • Hierarchical Clustering – Agglomerative
  • CART
  • 5.0
  • Random forest
  • Naïve Bayes




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