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    Data Science with R Course Syllabus

    Data Science with R Training in Chennai

    We Equip the global learners with our well-structured Data Science with R Course Syllabus to convert raw data into meaningful insight that helps the decision-makers and industry leaders. Our Data Science with R Course Curriculum covers the introduction of data science, the introduction of R, basic concepts of R programming, packages and data importing methods, data manipulation, basics of statistics, error metrics, machine learning concepts, and useful ML algorithms.

    Introduction to Data Science

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

    Introduction to R

    • What is R?
    • Why R?
    • Installing R
    • R environment
    • How to get help in R
    • R Studio Overview
    R Basics
    • Environment setup
    • Data Types
    • Variables Vectors
    • Lists
    • Matrix
    • Array
    • Factors
    • Data Frames
    • Loops
    • Packages
    • Functions
    • In-Built Data sets
    R Basics
    R Packages
    • DMwR
    • Dplyr/plyr
    • Caret
    • Lubridate
    • E1071
    • Cluster/FPC
    • Data.table
    • Stats/utils
    • ggplot/ggplot2
    • Glmnet
    R Basics
    Importing Data
    • Reading CSV files
    • Saving in Python data
    • Loading Python data objects
    • Writing data to CSV file
    R Basics
    Manipulating Data
    • Selecting rows/observations
    • Rounding Number
    • Selecting columns/fields
    • Merging data
    • Data aggregation
    • Data munging techniques
    R Basics
    Statistics Basics
    • Central Tendency
    • Mean
    • Median
    • Mode
    • Skewness
    • Normal Distribution
    R Basics
    Statistics Basics
    • What does it mean by probability?
    • Types of Probability
    • ODDS Ratio?
    • Standard Deviation
      • Data deviation & distribution
      • Variance
    • Bias variance Tradeoff
      • 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 an NA?
      • Central Imputation
      • KNN imputation
      • Dummification
    • Correlation
      • Pearson correlation
      • Positive & Negative correlation
    R Basics
    Error Metrics
    • Classification
      • Confusion Matrix
      • Precision
      • Recall
      • Specificity
      • F1 Score
    • Regression
      • MSE
      • RMSE
      • MAPE
    Machine Learning
    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
    Unsupervised Learning
    • K-Means
    • K-Means ++
    • Hierarchical Clustering
    Machine Learning using R
    • Linear Regression
    • Logistic Regression
    • K-Means
    • K-Means++
    • Hierarchical Clustering – Agglomerative
    • CART
    • 5.0
    • Random forest
    • Naïve Bayes
    Conclusion

    SLA Institute is the leading Data Science with R Training Institute in Chennai to enjoy experiential learning on industry-relevant Data Science with R Course Syllabus. Book a free demo class today.

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