● High-Level overview of Data Science / Machine Learning project management methodology
● Random Variable and its definition
● Probability and Probability Distribution
● Balanced vs Imbalanced datasets
● Sampling Funnel, its application and its components
● Measure of central tendency
● Measure of Dispersion
● Expected value of probability distribution
● Measure of Skewness
● Measure of Kurtosis
● Various graphical techniques to understand data
● Installation of Python IDE
● Anaconda and Spyder
● Working with Python with some basic commands
● Normal Distribution
● Standard Normal Distribution / Z distribution
● Z scores and Z table
● QQ Plot / Quantile-Quantile plot
● Sampling Variation
● Central Limit Theorem
● Sample size calculator
● T-distribution / Student’s-t distribution
● Confidence interval