Time Dependent Data: from Financial Analytics to Large Language Models

Overview

Academic Lead: Dr Sebastian Del Bano Rollin

Syllabus: SUM502M Time Dependent Data from Financial Analytics to Large Language Models [PDF]

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. A part 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 the some basic Exploratory Data Analysis in the context of time dependent data.
The couse 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.

Course content is subject to change.

Course aims

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 analyze 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.

Teaching and learning

You will be taught through a combination of lectures, laboratory work, and workshops.

Learning outcomes

You will:

• Understand Fundamental Concepts of Time Series Analysis
• Apply Predictive Modeling Techniques
• Explore Large Language Models and Their Applications

You will develop/be able to:

• analyse and interpret time dependent data Analysis
• consider and evaluate models used in the analysis of time dependent data
• utilise existing and new analytical and computational techniques in the resolution of real life problems related to the field

Fees

Additional costs

All reading material will be provided online, so it is not necessary to purchase any books.

For course and housing fees visit our finance webpage

Entry requirements

Course prerequisites:

Basic statistics, elementary usage of a computer, basic computer literacy either Windows or Apple, or Linux.

We welcome Summer School students from around the world. We accept a range of qualifications

How to apply

Have a question? Get in touch - one of the team will be happy to help!

Applications close 26 May 2025