Data Science with R Syllabus
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
- Data Visualization
- Machine Learning
- Other Miscellaneous R Packages
- More R Packages!
Module 5: Importing Data
- Reading CSV files
- Writing data to csv file
- Reading data from RDBMS
- Writing data into RDBMS
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
- 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
Module 9: 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
Module 10 Machine Learning - Unsupervised Learning
- K-Means
- Hierarchical Clustering
Module 11: Machine Learning using R
- Random forest
- Naïve Bayes