Python in Capital Markets

Learning Outcomes

Unlocking the secrets of coding and data science.


Whilst there are a myriad of Python courses available, what many of them fail to do is spend time on the fundamental building blocks and use cases within finance. This course targets exactly what you need to know to be able to add value in situations faced by those working in Capital Markets. Our hard-hitting approach enables you to move from zero to hero, ensuring that you can produce robust code that works. We cover the fundamentals of programming in Python by building a simple bond pricer and moving towards a machine learning model that can predict bond prices based upon changing market conditions. We can also tailor the course to meet any specific models or use cases required. Our sessions are lively and engaging, ensuring that the content is not only extremely well delivered, but received and understood well by participants.

Program Overview

Python Fundamentals – Getting started and learning to code
  • Introduction to Python
  • Python environment – IDE, Package manager
  • Jupyter notebooks
  • Fundamentals of programming with Python
Python Practical programming – Building a simple bond pricer
  • Why Python is suited for data analysis?
  • Introduction to module – Numpy, Matplotlib
  • Building a bond pricer and scenario manager in Python
Python Data Analysis – Getting to the heart and soul of Python
  • Importing data from Excel and CSV files
  • Data analysis with Pandas
  • Pandas Essentials – Pandas Data Structures, Hierarchical Indexing, Handling Missing Data, Useful Methods and Operations
  • Data visualization using Pandas
Python Data Science & Machine Learning – Building an application to ‘predict’ the market
  • Descriptive Analysis with data
  • Data analysis using scikit-learn
  • Plotting data using various plotting methods
  • Using various statistical tools for analysis

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