FE524: Prompt Engineering Lab for Business Applications


Course Description

Catalog Description

This course explores advanced techniques in prompt engineering to optimize the performance of large language models (LLMs). Participants will delve into the key elements of designing effective prompts, apply various prompting techniques, and evaluate LLMs for safety and reliability. The course includes hands-on exercises, discussions, and real-world business applications.

Course Description

This 1-credit course will cover the applied use of Large Language Models (LLMs). There are no course prerequisites, but students will need (1) general comfort using a computer with a command-line application like Terminal or PowerShell and (2) knowledge of Python or a commitment to learning it.


Campus Fall Spring Summer
On Campus X X
Web Campus

Instructors

Professor Email Office
Ed Loeser eloeser@stevens.edu Babbio 109

Other Information

Course Outcomes

This 1-credit course aims for students to gain a general understanding of the applied use of Large Language Models (LLMs), particularly:
  • how to take advantage of in-context learning when using LLMs
  • how to use LLMs programmatically
  • common LLM system architectures
  • how to use open LLMs
  • other related topics (inference engines, frameworks, etc)

Course Resources

Textbook

There is no required textbook. All material will be introduced during class.