- Random Variables
- Statistical Distributions
- Probability theory ( Calculating MGF, CGF, Mean, Median, Mode, Variance Maximum likelihood Expectation, Central limit theorems, ANOVA )
- Fitting of a distribution
- Sampling
- Testing of a hypothesis
- Bayesian Modeling
- Regression and Time Series
- Intermediate Python for Data Science
- Importing Data in Python
- Pandas Foundation
- Databases in Python
- Manipulating DataFrames with pandas
- Data Visualization with Python
- NumPy, Scikit learn and Model Evaluation
- Data Visualization with Bokeh
- Merging DataFrames with pandas
- Naïve Bayes
- Classifier Algorithm
- K Means Clustering Algorithm
- Support Vector Machine Algorithm
- Apriori Algorithm
- Linear Regression
- Logistic Regression
- Artificial Neural Networks
- Random Forests
- Decision Trees
- Nearest Neighbour
- SVM