Hands-on Master Class on LLMs and ChatGPT
Unlock the potential of Large Language Models (LLMs) and ChatGPT in an intensive short course offered by the Department of Electrical and Computer Engineering at the University of Washington. Over two weekends, we’ll explore the capabilities of LLMs and generative AI through comprehensive lectures, interactive coding sessions, and individual projects.
Date: Saturday 11/11, Sunday 11/12, Saturday 11/18, and Sunday 11/19, 2023
Time: 9 a.m. – noon
Location: Room ECE 045, University of Washington Seattle Campus, Paul Allen Center, 185 E Stevens Way NE, Seattle, WA 98195
- Intro to LLMs
- Transformers: BERT, sBERT, BART, T4
- LLM Libraries: Hugging Face, LangChain
- NLP Applications: Question-Answering, Emotion Detection
- Training models: Pre-training, fine-tuning, zero-shot, few-shot
- Data Augmentation: How to leverage ChatGPT for data augmentation through prompt engineering
Short Course Schedule
Each module will take place from 9 a.m. – noon
|Introduction to LLMs
|Prompt Engineering with LLMs
|Data Augment ChatGPT
|Mini Project utilizing ChatGPT
|Showcase on Kaggle
Engineers, developers, and data scientists with a background in computer science, engineering, or a related field. Participants should have familiarity with machine learning and natural language processing concepts, as well as proficiency in Python.
Participants in the course are required to have the following:
Registration and Cost
- General: $1100
- UWECE alumni: $800
Registration is now closed but keep an eye out for future offerings in 2024!
Are you a current ECE PMP student? Email firstname.lastname@example.org for information on taking this course for 1 credit.
Can I participate remotely in this short course?
Unfortunately not. We will record the sessions for participants to review later, but the short course is designed for live participation on the UW Seattle campus.
Are continuing education units/ professional development hours available for this short course?
Yes! UW ECE is an approved IEEE Credential Provider and IEEE will be providing PDH (or CEU) credits for this short course.
Are compute resources provided as part of the registration cost?
No, participants are responsible for obtaining their own compute resources as outlined in the “Course Requirements” section above.
Karthik Mohan is an affiliate professor in the Department of Electrical & Computer Engineering at the University of Washington. He has extensive experience in machine learning from his Ph.D. studies to later on as Senior Applied Scientist at Amazon and Facebook. He has worked on a range of problems including recommender systems, anomaly detection, learning graphical models, optimization methods for machine learning and natural language generation for intelligent devices, which have led to multiple publications at top conferences.
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