Python in Finance

Learn one of the most popular programming languages in the financial industry, highly sought-after by banks, hedge funds, asset management firms, pension funds, consulting companies, and financial software and data providers



Python in Finance is a unique, easy-to-follow course which requires no prior programming knowledge or experience. Designed to meet the enormous rise in demand for individuals with knowledge of Python in the financial industry, students are taught the practical coding skills now required in many roles.

The material contains multiple examples of practical applications in finance with a focus on quantitative risk/pricing analytics (taught in the Market Risk (Finance) course), giving you an opportunity for valuable practical experience. The course contents provide you with the must-have coding skills needed to excel in the modern finance sector. The course material has been developed in partnership with industry veteran and renowned practitioner, Dr Simon Clift.

After this course, candidates will possess the knowledge to write their own code from scratch in the Python programming language to, for example price options with the Black Scholes model, derive greeks, perform Monte Carlo simulation, generate an implied vol surface and many more (see course curriculum for additional details).

The Python programs developed by the student during the training program, and for the project completed at the end of the cohort (in the full program only) become an important part of the student’s portfolio. The portfolio is a valuable addition to a student’s CV/resume, and is a real asset that is evidence of the student’s practical experience and knowledge. This is particularly useful during a job search to set the student apart from other applicants.

The Python in Finance course is not offered on a standalone basis. It is included in our Certificate in Finance Business Analysis (FinBA), and Coding (Python, SQL) in Finance Certificate training programs.


You will learn how to use the following and more, to write Python code for financial applications.

  • Jupyter Notebook
  • Pandas (for data analysis)
  • NumPy, and SciPy (for quantitative computing)
  • Matplotlib (for data visualisation)

We will cover:

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

All students are to work on the following Python projects:

  • 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)

Final Python Project:

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

Note – The Python version used in the course is 3.6.3. (Note – you are required to install any 3.x version of Python (not necessarily 3.6) for the course)

Software Requirements

The following software must be installed on your computer for this course:

  • Python 3.x

  • Jupyter Notebook

  • Notepad++ or a similar text editor for .py files

(Get both Jupyter Notebook and Python together (free of charge) at:

Note: This course is taught in a Windows environment. The course is designed for specialised professionals in finance. It is not intended for IT specialists, computer scientists, or professional developers in finance. Software installation/application support not provided by the program. Students are advised to contact the vendors or search online for information.

Our Alumni Get Great Jobs

Graduates of our training programs secure employment with some of the most prestigious financial employers in locations across the globe. Many financial institutions sponsor their employees. More...

Become a highly skilled, highly paid professional in investment banking

Whether you’re new to finance/coding, adding more skills, or advancing your career, our training programs will prepare you for your ideal job.

Focused curricula

Each of our courses focuses on delivering only the specific knowledge you need to pass the toughest interviews, land your coveted role, and succeed in your career.

Learn from experts

Our courses are developed/taught directly by industry-leading implementation experts and thought leaders.

No finance or coding experience required

Beginner, novice or intermediate, whatever your level, you don’t need to have prior knowledge of finance or programming as all our courses are taught from foundations.

Practical learning

You won't just study the theory. Our training programs are heavily practical by design. You will learn by doing - by undertaking the type of work you will likely be doing on the job.

Coding projects

You will learn the highly sought-after programming languages of Python & SQL and then actually write the code needed to build 10+ prototypes of the kind of systems every investment bank uses.

Live teaching sessions

You will join a live web session every week where you can talk directly to the expert instructor, and other students for one-to-one and group support.


You will overcome the catch-22 hurdle of eligibility by earning a globally recognised official certificate from Financial Risk Hub that demonstrates your competence to potential employers.

CPD credits - CFA, FRM, & PRM

You can consolidate your professional quantitative finance & risk analytics credentials by earning credits from leading industry organisations such as the CFA Institute, GARP and PRMIA.

Professional recruiters

You will gain exclusive access to specialist investment banking recruiters to help you advance your career and land a high-paying role.

Go from Job Search to Job Success

We provide access to a wide variety of career services and support to help you secure your next role after successfully completing the program.

CV/resume help (FinBA program only)

You will be assigned a dedicated professional investment banking recruiter, specialising in Risk & Quant Finance, who will work 1-1 with you to tailor your existing CV/resume.

Leverage our network (FinBA program only)

We foster personal introductions to our network of potential hiring managers and recruiters, to help our students based in London, Toronto, NY/Boston/Chicago/Dallas, and Sydney/Melbourne get connected to the right people.

Job search support

You will receive invaluable guidance on how to navigate the complex recruitment landscape and conduct a smart search for your first or next role in investment banking.

Interview prep

You will be provided a comprehensive set of common interview questions and framework for how to answer them. In addition, we will train you on the mindset and approach needed to ace interviews at any investment bank.

Our Taught Courses

Gain in-demand, specialised knowledge on financial products and risk analytics on a 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.
Get a solid introduction to counterparty credit risk, one of the key financial risks an investment bank faces, in a session led by Professor Johannes Ruf (London School of Economics).