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.
For Online & Offline Training
Have Queries? Ask our Experts
+91 88707 67784 Available 24x7 for your queries