Python in Finance Curriculum

An easy-to-follow introduction to Python coding in finance that will quickly equip you with the coding skills you need to start writing useful code in Python at work.



1 – Basics

  • Jupyter Notebook Introduction

  • Variables

  • Python Functions

  • Data Types

  • Operators (arithmetic, comparison, Boolean)

2 – Data Structures

  • Tuples

  • Lists

  • Sets

  • Indexing and Slicing

3 – Language Structures

  • Range Function

  • For Loop

  • While Loop
  • If Statement

  • User-defined Functions

4 – Advanced Python Features

  • List Comprehension

  • Lambdas

5 – Pandas for Data Analysis

  • Dataframe Basics

  • Data Import/Export

  • Indexing, and Slicing Data

  • Access Methods

  • Date Columns, and Arithmetic

  • Data Manipulation

  • Handling Missing Values

  • Delimited Data

  • Merging Dataframes

  • Dataframe Arithmetic Operations

  • Data Aggregation

6 – Visualisation Using Matplotlib

  • Line Chart

  • Bar Chart

  • Histogram

  • 3D Plotting

7 – Basic Financial Calculations with Pandas

  • Moneyness Computation

  • Forward Filling, Backward Filling

  • Linear Interpolation Using Specific Index

8 – Financial Computing with NumPy, and SciPy

  • Arrays

  • Arrays Mathematics

  • Array Operations
  • Indexing, and Slicing

  • Black Scholes Option Pricer

  • Monte Carlo Pricing (Pure Python)

  • Monte Carlo Pricing (NumPy)

  • Sensitivities (Greeks) Computation

  • Vectorised Black Scholes Option Pricer

  • Implied Volatility Surface Generation

  • Value at Risk (VaR) estimation

  • Newton Iteration

  • Altman Iteration

9 – Python Projects (Financial Applications)

  • Residual Risk Add On capital

  • PnL Attribution Test (PLAT) – Spearman correlation, and Kolmogorov-Smirnov test

  • Scenario Generation
  • Sensitivities Based Method sensitivities

  • Risk Factor Eligibility Test

  • Value at Risk
  • Expected Shortfall
  • Timeseries imputation

  • Vanilla option pricing

  • Exotic option pricing
  • Stress testing

  • Back testing
  • Volatility surface construction
  • Monte Carlo stock price simulation (geometric brownian motion)

10 – Project (for FinBA students only)

At the end of the cohort, students will build Python programs with financial applications, using the skills acquired during the course.


Our Global Employers

Our training programs are respected by banks and financial institutions all over the world. Our graduates go on to secure employment with some of the most prestigious financial employers in locations across the globe. Many financial institutions sponsor and/or reimburse employees attending our programs. More...

All Our Training Programs Include

Taught by industry experts, our training programs focus on the real-world. Whether you are new to finance or you have experience in the financial industry, you will be taught practical, applied skills that you need for a specialised career in finance.

Gain in-demand, specialised financial knowledge on an accredited, hands-on course with an opportunity to qualify for GARP/PRMIA/CFA Institute CPD credits.
Learn one of the most popular programming languages in the financial industry - highly sought-after by employers.
Learn one of the most important programming languages in finance - Structured Query Language (SQL) for data storage, analysis and manipulation.
Receive support with CV/resume refining, interview prep, job search strategy, and get expert guidance directly from professional investment banking recruiters.