Data Science with R Course Syllabus
Live Online & Classroom Training
EMI
0% Interest
Have Queries? Ask our Experts
+91 89256 88858
Quick Enquiry
One of the most popular open-source languages for data science and statistical computation is R. R Fundamentals, data manipulation with dplyr and tidyr, data visualization with ggplot2, statistical analysis, machine learning with packages, data wrangling and exploratory data analysis, working with R markdown, and data science projects are just a few of the many topics covered in this Data Science using R syllabus. Get practical experience with R’s robust libraries and build a solid basis for a prosperous data science career with our R syllabus for data science.
Course Syllabus
Download SyllabusIntroduction 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 Packages
- DMwR
- Dplyr/plyr
- Caret
- Lubridate
- E1071
- Cluster/FPC
- Data.table
- Stats/utils
- ggplot/ggplot2
- Glmnet
Importing Data
- Reading CSV files
- Saving in Python data
- Loading Python data objects
- Writing data to CSV file
Manipulating Data
- Selecting rows/observations
- Rounding Number
- Selecting columns/fields
- Merging data
- Data aggregation
- Data munging techniques
Statistics Basics
- Central Tendency
- Mean
- Median
- Mode
- Skewness
- Normal Distribution
Statistics Basics
- What does it mean by probability?
- Types of Probability
- ODDS Ratio?
- Data deviation & distribution
- Variance
- Underfitting
- Overfitting
- Euclidean Distance
- Manhattan Distance
- What is an Outlier?
- Inter Quartile Range
- Box & whisker plot
- Upper Whisker
- Lower Whisker
- Scatter plot
- Cook’s Distance
- What is an NA?
- Central Imputation
- KNN imputation
- Dummification
- Pearson correlation
- Positive & Negative correlation
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
Data science with R course uses the R programming language to give a thorough introduction to data science.
