17-659 — Generative AI for Quantum Computing and Machine Learning Software Implementations — Summer Semester 2023
Generative AI for Quantum Computing and Machine Learning Software Implementations
Tuesdays and Thursdays (7:00pm to 8:20pm @ Zoom)
Daniel Justice
Location
Class room is fully remote. The class will be streamed via Zoom.
Course Goals
Students will gain familiarity with current universal gate quantum computing tools and technology. Students will also become comfortable with several QC algorithms and their implementation on state of the art quantum computer simulators and hardware.
Grading
90% Homeworks/Quizzes, 10% Participation.
Quizzes
Each week a quiz will be given. The worst one will not be counted.
Prerequisites
Python, Jupyter Notebooks, Linear Algebra
Students will not need an understanding of quantum mechanics.
Note: The syllabus is subject to occasional change. This is especially the case in the latter half of the semester once your professors have become comfortable with the group’s overall skill level. Adequate notice will be given.
Basic course structure
Due to this being a mini, we will do our best to skirt into a new topic each and every day.
Schedule
- Day 1 (05/16): Intro & Intro to Quantum Computing
- Day 2 (05/18): Fundamentals of Quantum Computing Continued
- Day 3 (05/23): Introduction to AI, ML and DL
- Day 4 (05/25): Fundamentals of Generative Models
- Day 5 (05/30): Fundamentals of LLMs
- Day 6 (06/01): Software Implementation of Generative AIs
- Day 7 (06/06): LLM Implementations
- Day 8 (06/08): Quantum Programming Languages
- Day 9 (06/13): Quantum Generative Models
- Day 10 (06/15): Langchain
- Day 11 (06/20): LLM Data Preparation and Finetuning
- Day 12 (06/22): LLMs in Machine Learning and Quantum Computing
- Day 13 (06/27): OPEN - Guest Lecture
Schedule with assignments, readings, etc. can be found here
Alternative Schedule
- Day 1 (05/16): Introduction to Artificial Intelligence
- Day 2 (05/18): Exploring Quantum Computing
- Day 3 (05/23): Fundamentals of Generative Models in Machine Learning
- Day 4 (05/25): Understanding Language Models
- Day 5 (05/30): Implementing Generative Artificial Intelligence Software
- Day 6 (06/01): Practical Applications of Language Models
- Day 7 (06/06): Quantum Programming Languages and Quantum Computing
- Day 8 (06/08): Quantum Generative Models and their Applications
- Day 9 (06/13): Exploring Langchain Technology
- Day 10 (06/15): Data Preparation and Finetuning for Language Models
- Day 11 (06/20): Language Models in Machine Learning and Quantum Computing
- Day 12 (06/22): OPEN - Guest Lecture
- Day 13 (06/27): Final Project Presentation and Wrap-up