### Pandas

- Let’s Start with Pandas Library: Introduction and Installation
- Pandas DataFrame
- Pandas Series
- Pandas Basic Operations
- Data Manipulation using Pandas
- Iterating over rows and columns in Pandas DataFrame
- apply() in Pandas
- Pandas map() and reduce() Operations
- Handling Missing Values in Pandas
- Grouping Data in Pandas
- Merging and Joining in Pandas
- Concatenating data in Pandas
- Working with crosstab, pivot_tables, and melt functions in Pandas
- Working with Pandas Date and Time
- Working with Strings in Pandas

### Data Visualization

### Optimization Techniques (Operation Research)

- Solving Linear Programming using Python PuLP
- Solving Staff Scheduling Problem using Linear Programming
- Solving Cargo Loading Problem using Integer Programming in Python
- Solving Transportation Problem using Linear Programming in Python
- Solving Blending Problem in Python using Gurobi
- Solving Assignment Problem using Linear Programming in Python
- Transshipment Problem in Python Using PuLP
- Solving Balanced Diet Problem in Python using PuLP
- Solving Multi-Period Production Scheduling Problem in Python using PuLP
- Sensitivity Analysis in Python