Machine Learning

Machine learning helps improve our lives in a huge number of ways.
For example, when you’re booking a taxi, you’re shown how much the trip would cost. Or when you’re on the trip, you’re shown the path the taxi would take to reach your destination. All of that, is machine learning.

Introduction to Data Science and Statistical Analytics

❖ Introduction to Data Science

❖ Use cases

❖ The need for Business Analytics

❖ Data Science Life Cycle ❖


Different tools available for Data Science Introduction to R

❖ Installing R and R-Studio

❖ R packages and R Operators

❖ if statements and loops (for, while, repeat, break, next), switch case


Data Exploration, Data Wrangling, and R Data Structure

❖ Importing and Exporting data from an external source

❖ Data exploratory analysis

❖ R Data Structure (Vector, Scalar, Matrices, Array, Data frame, List)

❖ Functions, Apply Functions Data Visualization

❖ Bar Graph (Simple, Grouped, Stacked)

❖ Histogram

❖ Pie Chart, Line Chart, Box (Whisker) Plot, Scatter Plot

❖ Correlogram


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