Data Science: Benefits and uses – facets of data – Data Science Process: Overview – Defining research goals – Retrieving data – Data preparation – Exploratory Data analysis – build the model–presenting findings and building applications–Data Mining–Data Warehousing–Basic Statistical descriptions of Data

Introduction - Data Types and Scales - Population and Sample -Measures of Central Tendency - Measures of Variation - Measures of Shape - Data Visualization

Probability Theory- Axioms of Probability - Bayes’ Theorem - Random Variables - Probability Density Function & Cumulative Distribution Function-Random Variable-Binomial Distribution -Normal Distribution-Chi-Square Distribution

Correlation–Scatter plots–correlation coefficient for quantitative data–computational formula for correlation coefficient–Regression–regression line–least squares regression line–Standard error of estimate

Importing Matplotlib–Line plots–Scatter plots–visualizing errors– density and contour plots – Histograms – legends – colors – subplots – text and annotation – customization – three dimensional plotting –Visualization with Seaborn