CODING FOR FINANCE (2 SCU)
Learning Outcomes:
On successful completion of this course, students will be able to: apply Python for interactive financial analytics and application development; recognize Python data types and structures, NumPy, pandas and its DataFrame class, and object-oriented programming; apply Python techniques and packages for financial time series data, I/O operations, stochastics, and machine learning.
Topics:
- Why Python for Finance;
- Python Infrastructure;
- Data Types and Structures;
- Numerical Computing with NumPy;
- Data Analysis with pandas;
- Object-Oriented Programming;
- Data Visualization;
- Financial Time Series;
- Input/Output Operations;
- Performance Python;
- Mathematical Tools;
- Stochastics;
- Statistics.
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