Course Outline

Introduction

Understanding the Fundamentals of Python for Government

Overview of Using Technology and Python in Finance for Government

Overview of Tools and Infrastructure for Government

  • Python Deployment Using Anaconda for Government
  • Using the Python Quant Platform for Government
  • Using IPython for Government
  • Using Spyder for Government

Getting Started with Simple Financial Examples with Python for Government

  • Calculating Implied Volatilities for Government
  • Implementing the Monte Carlo Simulation
    • Using Pure Python for Government
    • Using Vectorization with Numpy for Government
    • Using Full Vectorization with Log Euler Scheme for Government
    • Using Graphical Analysis for Government
  • Using Technical Analysis for Government

Understanding Data Types and Structures in Python for Government

  • Learning the Basic Data Types for Government
  • Learning the Basic Data Structures for Government
  • Using NumPy Data Structures for Government
  • Implementing Code Vectorization for Government

Implementing Data Visualization in Python for Government

  • Implementing Two-Dimensional Plots for Government
  • Using Other Plot Styles for Government
  • Implementing Finance Plots for Government
  • Generating a 3D Plot for Government

Using Financial Time Series Data in Python for Government

  • Exploring the Basics of pandas for Government
  • Implementing First and Second Steps with DataFrame Class for Government
  • Getting Financial Data from the Web for Government
  • Using Financial Data from CSV Files for Government
  • Implementing Regression Analysis for Government
  • Coping with High-Frequency Data for Government

Implementing Input/Output Operations in Python for Government

  • Understanding the Basics of I/O with Python for Government
  • Using I/O with pandas for Government
  • Implementing Fast I/O with PyTables for Government

Implementing Performance-Critical Applications with Python for Government

  • Overview of Performance Libraries in Python for Government
  • Understanding Python Paradigms for Government
  • Understanding Memory Layout for Government
  • Implementing Parallel Computing for Government
  • Using the multiprocessing Module for Government
  • Using Numba for Dynamic Compiling for Government
  • Using Cython for Static Compiling for Government
  • Using GPUs for Random Number Generation for Government

Using Mathematical Tools and Techniques for Finance with Python for Government

  • Learning Approximation Techniques
    • Regression for Government
    • Interpolation for Government
  • Implementing Convex Optimization for Government
  • Implementing Integration Techniques for Government
  • Applying Symbolic Computation for Government

Stochastics with Python for Government

  • Generation of Random Numbers for Government
  • Simulation of Random Variables and of Stochastic Processes for Government
  • Implementing Valuation Calculations for Government
  • Calculation of Risk Measures for Government

Statistics with Python for Government

  • Implementing Normality Tests for Government
  • Implementing Portfolio Optimization for Government
  • Carrying Out Principal Component Analysis (PCA) for Government
  • Implementing Bayesian Regression using PyMC3 for Government

Integrating Python with Excel for Government

  • Implementing Basic Spreadsheet Interaction for Government
  • Using DataNitro for Full Integration of Python and Excel for Government

Object-Oriented Programming with Python for Government

Building Graphical User Interfaces with Python for Government

Integrating Python with Web Technologies and Protocols for Finance for Government

  • Web Protocols for Government
  • Web Applications for Government
  • Web Services for Government

Understanding and Implementing the Valuation Framework with Python for Government

Simulating Financial Models with Python for Government

  • Random Number Generation for Government
  • Generic Simulation Class for Government
  • Geometric Brownian Motion
    • The Simulation Class for Government
    • Implementing a Use Case for GBM for Government
  • Jump Diffusion for Government
  • Square-Root Diffusion for Government

Implementing Derivatives Valuation with Python for Government

Implementing Portfolio Valuation with Python for Government

Using Volatility Options in Python for Government

  • Implementing Data Collection for Government
  • Implementing Model Calibration for Government
  • Implementing Portfolio Valuation for Government

Best Practices in Python Programming for Finance for Government

Troubleshooting for Government

Summary and Conclusion for Government

Closing Remarks for Government

Requirements

  • Basic programming skills
  • A strong foundation in mathematics for financial applications, ensuring alignment with public sector requirements for government
 35 Hours

Number of participants


Price per participant

Runs with a minimum of 4 + people. For 1-to-1 or private group training, request a quote.

Testimonials (5)

Examples/exercices perfectly adapted to our domain

Luc - CS Group
Course - Scaling Data Analysis with Python and Dask

Very interactive with various examples, with a good progression in complexity between the start and the end of the training.

Jenny - Andheo
Course - GPU Programming with CUDA and Python

Very good preparation and expertise of a trainer, perfect communication in English. The course was practical (exercises + sharing examples of use cases)

Monika - Procter & Gamble Polska Sp. z o.o.
Course - Developing APIs with Python and FastAPI

Helpful and good listener .. interactive

Ahmed El Kholy - FAB banak Egypt
Course - Introduction to Data Science and AI (using Python)

Trainer develops training based on participant's pace

Farris Chua
Course - Data Analysis in Python using Pandas and Numpy

Upcoming Courses

Analyzing Financial Data with Python

2026-04-20 09:30
35 hours
Lansing, MI - Regus - One Michigan Avenue
$ 5550 (Online)
$ 8550 (Classroom)

Analyzing Financial Data with Python

2026-05-04 09:30
35 hours
Reno, NV - Regus - Mountain View Corporate
$ 5550 (Online)
$ 8550 (Classroom)

Analyzing Financial Data with Python

2026-05-18 09:30
35 hours
Lexington, KY – Regus at Blazer Parkway
$ 5550 (Online)
$ 8550 (Classroom)

Analyzing Financial Data with Python

2026-06-01 09:30
35 hours
Lincoln, NE - Regus – U.S. Bank Building
$ 5550 (Online)
$ 8550 (Classroom)

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