Introduction to Data Science ᎓ Evolution of Data Science ᎓ Data Science Roles ᎓ Stages in a Data Science Project ᎓ Applications of Data Science in various fields ᎓ Data Security Issues.

Data Collection and Data Pre-Processing Data Collection Strategies ᎓ Data Pre-Processing Overview ᎓ Data Cleaning ᎓ Data Integration and Transformation ᎓ Data Reduction ᎓ Data Discretization.

Exploratory Data Analytics Descriptive Statistics ᎓ Mean, Standard Deviation, Skewness and Kurtosis ᎓ Box Plots ᎓ Pivot Table ᎓ Heat Map ᎓ Correlation Statistics ᎓ ANOVA.

Model Development Simple and Multiple Regression ᎓ Model Evaluation using Visualization ᎓ Residual Plot ᎓ Distribution Plot ᎓ Polynomial Regression and Pipelines ᎓ Measures for In-sample Evaluation ᎓ Prediction and Decision Making.

Model Evaluation Generalization Error ᎓ Out-of-Sample Evaluation Metrics ᎓ Cross Validation ᎓ Overfitting ᎓ Under Fitting and Model Selection ᎓ Prediction by using Ridge Regression ᎓ Testing Multiple Parameters by using Grid Search.