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Course Outline

Orientation

Configuring Your Development Workspace

  • Local vs. cloud-based environments: Utilizing Anaconda and Jupyter

Core Python Syntax and Logic

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

Extending Functionality

  • Managing modules and third-party packages

Developing Your First Application

  • Calculating start and end periods for time-based analysis

Retrieving External Data

  • Data interchange, including CSV import/export workflows
  • Querying and extracting data from SQL databases

Managing Data with Arrays and Vectors

  • Implementing NumPy and vectorized operations for efficiency

Data Visualization

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

Advanced Data Analysis

  • Statistical analysis leveraging scipy.stats and pandas
  • Integrating and exporting data from Excel and web sources

Simulating Market Movements

  • Applying Monte Carlo methods for trajectory simulation

Portfolio Strategy and Optimization

  • Executing capital and asset allocation strategies alongside risk evaluation

Risk Assessment and Performance Metrics

  • Formulating and resolving complex portfolio optimization challenges

Fixed Income and Derivatives

  • Conducting bond analysis and option pricing calculations

Time Series Analysis

  • Interpreting temporal data trends within financial markets

Production Deployment

  • Integrating Python solutions with Excel and external web platforms

Performance Engineering

  • Refining application speed and efficiency
  • Leveraging parallel computing and multi-processing techniques

Debugging and Resolution

Conclusion

Requirements

  • Familiarity with financial instruments, including securities and derivatives
  • Foundational knowledge of probability and statistical concepts
  • Basic understanding of calculus, including differentiation and integration
 35 Hours

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