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Course Outline

Introduction

Configuring the Development Environment

  • Local versus online programming setups: Anaconda and Jupyter

Core Python Concepts

  • Exploring control structures, data types, functions, data structures, and operators

Extending Python's Functionality

  • Understanding modules and third-party packages

Building Your First Python Application

  • Calculating and estimating start and end dates and times

Retrieving External Data with Python

  • Handling data import and export, including reading and writing CSV files
  • Interacting with data stored in SQL databases

Structuring Data with Arrays and Vectors

  • Utilizing NumPy and vectorized operations for efficiency

Data Visualization with Python

  • Creating 2D and 3D plots using Matplotlib, pyplot, and SciPy

Data Analysis with Python

  • Performing statistical analysis with scipy.stats and managing data with pandas
  • Importing and exporting financial data from sources like Excel and web platforms

Simulating Asset Price Behaviors

  • Implementing Monte Carlo simulations

Asset Allocation and Portfolio Strategy

  • Executing capital allocation, asset distribution, and risk evaluation

Risk Assessment and Performance Measurement

  • Formulating and resolving portfolio optimization challenges

Fixed-Income Analysis and Derivative Valuation

  • Conducting fixed-income calculations and option pricing

Financial Time Series Examination

  • Interpreting time-series data within financial market contexts

Deploying Python Applications to Production

  • Integrating applications with Excel and other web-based services

Enhancing Application Performance

  • Tuning and optimizing application speed
  • Leveraging parallel computing and multiprocessing

Debugging and Troubleshooting

Conclusion

Requirements

  • A solid grasp of financial instruments, including securities and derivatives
  • A foundational understanding of probability and statistical principles
  • Basic knowledge of differential and integral calculus
 35 Hours

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