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Course Outline

Introduction

Configuring the Development Environment

  • Local vs. online programming: Anaconda and Jupyter

Core Python Concepts

  • Control flow, data types, functions, structures, and operators

Enhancing Python’s Functionality

  • Working with Modules and Packages

Your First Python Project

  • Calculating start and end dates and times

Accessing External Data in Python

  • Handling CSV data (importing, exporting, reading, and writing)
  • Connecting to and querying SQL databases

Managing Data with Arrays and Vectors

  • Using NumPy and vectorized operations

Data Visualization in Python

  • 2D and 3D plotting with Matplotlib, pyplot, and SciPy

Data Analysis with Python

  • Utilizing scipy.stats and pandas for analysis
  • Importing and exporting financial data (Excel, web sources, etc.)

Simulating Asset Price Movements

  • Monte Carlo simulation techniques

Asset Allocation and Portfolio Optimization

  • Executing capital allocation, asset distribution, and risk evaluation

Risk Assessment and Investment Performance

  • Formulating and resolving portfolio optimization challenges

Fixed-Income and Options Analysis

  • Conducting fixed-income analysis and option pricing

Financial Time Series Analysis

  • Analyzing time-series data in financial markets

Deploying Python Applications for Production

  • Integrating applications with Excel and other web-based tools

Application Performance

  • Optimizing application efficiency
  • Implementing parallel computing and multiprocessing

Debugging and Troubleshooting

Conclusion

Requirements

  • Familiarity with financial instruments (e.g., securities, derivatives)
  • Basic knowledge of probability and statistics
  • Foundational understanding of differential and integral calculus
 35 Hours

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