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Large Language Models (LLMs) in Data Management

  • Number of credits 7.5 credits
  • Level Bachelor's level
  • Study form Web-based (online)
  • Starting Summer Term 2024

About the course

In 2022 ChatGPT riveted the world's attention. Finally a system that we can actually speak with! This breakthrough kicked off numerous projects applying GPT and other large language models (LLMs) to a vast number of use cases. And this includes cases where relevant data is not part of the LLM's original training corpus. An immediate example of this would be questions about recent news, but what we focus on here is when the data is a dynamic set of facts, for example weather data, or the value of a stock portfolio, or the intricate details of a unfolding business deal or work process. In short, we are exploring the topic of LLMs meet databases. And this raises many questions: Will LLMs let us chat directly with our databases? Will such systems actually work? Will such systems exploit the common sense knowledge latent in the LLM? How do we mitigate the problem of hallucination? Can LLMs define and populate databases on the fly and would that be useful? Can LLMs help existing databases better integrate? Should systems operate with autonomy or serve as assistants? The questions go on and on, but the overarching question is, how are we really going to get value out of LLMs in the data management context? While we do not yet have comprehensive answers, ultimately we will and this will likely have a profound impact on our economy and society. 

The course gives technical students and IT practitioners the opportunity to take a deep dive into the transformer networks that back LLMs and explore their application to long standing problems in data management. It will be a fun course given in an open, playful and inquisitive spirit. We will all learn a lot.

Application and eligibility

Large Language Models (LLMs) in Data Management, 7.5 credits

Det finns inga tidigare terminer för kursen Summer Term 2024 Det finns inga senare terminer för kursen

Starts

3 June 2024

Ends

25 August 2024

Study location

Varied

Language

English

Type of studies

Daytime, 50%, Distance

Number of mandatory meetings

No mandatory meetings.

Number of other meetings

None

Outline for distance course

This course is a distance course which requires no local physical presence. Lectures are held over Zoom and course material is delivered via Canvas. Lectures are recorded, so attendance is flexible. Students answer problems and demonstrate their programming solutions in recitation sessions held over Zoom. While attendance in recitations is mandatory, there are multiple opportunities to accommodate student schedules. The course ends with a take home exam that students upload to Canvas. All work is conducted by the student individually. Students must show their work at four separate Zoom-based recitations. There is also a take home final exam which students upload to Canvas for grading.

Required Knowledge

At least 30 ECTS in Computing Science or Mathematics including completed courses in programming (ideally Python), data structures and algorithms, databases, calculus, and linear algebra.

Entry requirements

Selection

Academic credits

Application code

UMU-95733

Application

Application deadline was 15 March 2024. The application period is closed.

Application and tuition fees

As a citizen of a country outside the European Union (EU), the European Economic Area (EEA) or Switzerland, you are required to pay application and tuition fees for studies at Umeå University.

Application fee

SEK 900

Tuition fee, first instalment

SEK 17,850

Total fee

SEK 17,850

Contact us

Please be aware that the University is a public authority and that what you write here can be included in an official document. Therefore, be careful if you are writing about sensitive or personal matters in this contact form. If you have such an enquiry, please call us instead. All data will be treated in accordance with the General Data Protection Regulation.

Course is given by
Department of Computing Science