Time Dependent Data from Financial Analytics to Large Language Models

Course description:

This course is a basic introduction to the dynamics of time dependent data. We will start by discussing the type of data to be analysed. Apart from typical single number time series such as temperatures or stock prices, we will also consider the evolution of geospatial variables, 3D and text data.

This will be followed by some basic Exploratory Data Analysis in the context of time dependent data. The course will then provide insights on how time dependent data can be analysed based on real world examples and applications. Areas of applications that might be considered are speech, stock market evolution, music, geospatial data such as MRI scans, and medical time series data used in diagnostics.

This module aims to:

1. Introduce students to the fundamental concepts of time-dependent data analysis in financial markets, medicine, social studies and other domains.

2. Develop a basic understanding of the methodologies and tools used to analyse time series data.

3. Provide hands-on experience with real-world datasets to apply theoretical concepts.

4. Explore the application of time-dependent data analysis in the context of large language models and cognitive sciences.

5. Equip students with the skills to critically evaluate and interpret dynamic data trends in various fields.

Learning outcomes:

You will learn/develop:

• To understand fundamental concepts of time series analysis

• Apply predictive modelling techniques

• Explore large language models and their applications

• To analyse and interpret time dependent data Analysis

• To consider and evaluate models used in the analysis of time dependent data

• To utilise existing and new analytical and computational techniques in the resolution of real-life problems related to the field

• Critical Thinking and Problem-Solving 

• Technical Proficiency

• Interdisciplinary Insight