Universität Wien

580015 VU VU Large Language Models (LLMs) - application and impact in Pharmaceutical Sciences (2024S)

Continuous assessment of course work

Registration/Deregistration

Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).

Details

Language: German

Lecturers

Classes

June 17, 2024, 9:00-12:30: Introduction to Large Language Models (LLMs)

Target Audience: This session is primarily for attendees new to LLMs. It will cover the basics of what LLMs are, their underlying technology, and their potential applications in pharmaceutical sciences. Attendees with prior knowledge of LLMs may skip this session.
Content: Overview of LLMs, understanding their mechanisms, potential benefits, and limitations in the context of pharmaceutical research and development.
June 18, 2024, 9:00-12:30: Legal Concerns and Introduction to New Tools/Platforms

Content: This session will delve into the new legal challenges posed by LLMs, including intellectual property issues and data privacy concerns. We will also explore various tools and platforms, both local and remote, that are being developed to leverage LLMs in pharmaceutical sciences. The discussion will include how these tools can be integrated into existing workflows.
June 19, 2024, 9:00-12:30: Hands-On Coding and Application in Pharmaceutical Sciences

Content: The final day will be a practical session focused on solving coding problems using LLMs. Participants will learn how LLMs can assist in programmatic solutions within pharmaceutical sciences, including data analysis, drug discovery, and more. This session emphasizes the importance of Python programming skills; those not proficient are encouraged to partner with others. The goal is to demonstrate the practical applications and limitations of LLMs in enhancing research and development tasks.


Information

Aims, contents and method of the course

This course aims to explore the impact of Large Language Models (LLMs) within the pharmaceutical sciences. Participants will gain foundational knowledge of LLMs, understand emerging legal concerns and the introduction of new computational tools, and acquire hands-on experience in applying LLMs to solve programming challenges relevant to the field. The course is designed for those with an interest in the intersection of artificial intelligence and pharmaceutical sciences, with a particular emphasis on how coding and LLMs can enhance research and development.

Assessment and permitted materials

Minimum requirements and assessment criteria

Who Should Attend:

Students and researchers in the pharmaceutical sciences interested in the application of AI and machine learning.
Individuals with a basic understanding of programming in Python or a willingness to learn, given the practical component of the course.
Note: Participants are encouraged to bring their laptops for the hands-on session. Collaboration is highly recommended for those less experienced in programming.

Examination topics

Reading list


Association in the course directory

Last modified: Mo 11.03.2024 11:27