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Python

Welcome to the course! This course introduces Python as a powerful tool for financial analysis, quantitative modelling, and data-driven decision making. Through a combination of programming fundamentals and real-world applications, you will develop the skills needed to analyse financial data, build trading models, and apply modern machine learning techniques.

1. Python Basics

The course begins with the fundamentals of Python programming and is organised into four sessions:

  • Session 1: Programming Foundations
  • Session 2: Python Data Structures
  • Session 3: Statistical Analysis
  • Session 4: Data Visualisation

2. Applied Finance and Trading Strategies

Building on the programming fundamentals, you will learn how Python is used in finance to analyse markets and develop quantitative trading strategies. Topics include:

  • Financial data collection and preprocessing
  • Time series analysis
  • Return and risk analysis
  • Portfolio construction and optimisation
  • Technical indicators
  • Strategy development and backtesting
  • Performance evaluation and risk metrics
  • Data visualisation for financial analysis

3. Machine Learning and Artificial Intelligence

The final section introduces modern machine learning techniques that are increasingly used in finance and algorithmic trading. Topics include:

  • Data preparation and feature engineering
  • Supervised learning
  • Unsupervised learning
  • Model evaluation and validation
  • Predictive modelling for financial markets
  • Introduction to deep learning
  • Large Language Models (LLMs) and Generative AI
  • AI-assisted financial analysis and decision support