Work Experience :- Overview of Analytics and Data Science-Basic Statics (Descriptive statistics, Inferential statistics, Probability theory and distribution, Tests of hypothesis, Distance measures and central limit theorem, t –test on a sample data, ANOVA and Chi square tests)-Numpy(arrays)-Pandas( for data manipulation and analysis)-Basics of Machine Learning-Scikit Learn-Matplotlib

work experience included, - Introduction to python basics for ML - Python libraries pandas,numpy,matplotlib - ML models linear regression, Naive bayes classifier, Decision, Random forest classifier, SVN classifier - Calculating errors using r and r square error - Accuracy score determination using sklearn As for a project,each one of us were given an individual data set . My project was to Analyze if a person earns 50,000 in a census of income data. I successfully completed my work for the same.