11-860: Quantum Computing, Cryptography, & Machine Learning Lab — Syllabus

Course Syllabus

Course Information

• Course: 11-860: Quantum Computing, Cryptography, & Machine Learning Lab
• Term: Spring 2026
• Meeting time: Monday and Wednesday, 5:00pm–6:20pm ET
• Location: GHC 4215
• Modality: In person (Zoom available for remote sessions as needed)
• Zoom: https://cmu.zoom.us/j/99820694854?pwd=WkpFTHFzRlBUUkNqWGpFSlhHaDdqUT09

Instructors

• Daniel Justice — djustice@andrew.cmu.edu
• Bhiksha Raj — bhiksha@cmu.edu
• Rita Singh — rsingh@cs.cmu.edu
• TA: Ryan Wang — ryanw3@andrew.cmu.edu

Course Overview

This course introduces core quantum computing concepts with an emphasis on algorithms, circuits, and hands-on implementation. The course blends lecture and lab sessions covering quantum information fundamentals, gate-based computing, and modern applications in cryptography and machine learning.

Learning Outcomes

By the end of the course, students will be able to:

• Explain key concepts in quantum information and computation.
• Analyze and implement basic quantum algorithms.
• Design and reason about quantum circuits.
• Apply quantum computing ideas to cryptography and machine learning contexts.

Prerequisites

Python, Jupyter Notebooks, Linear Algebra. Students do not need prior quantum mechanics.

Required and Recommended Reading

Main Book (recommended)

• Programming Quantum Computers (Wong)
  O’Reilly Online: https://learning.oreilly.com/library/view/programming-quantum-computers/9781492039679/

Additional Reading

• Quantum Computing for Computer Scientists (Yanofsky and Mannucci)
  https://www.amazon.com/Quantum-Computing-Computer-Scientists-Yanofsky/dp/0521879965
• Quantum Computation and Quantum Information (Nielsen and Chuang)
  https://mmrc.amss.cas.cn/tlb/201702/W020170224608150244118.pdf

Course Materials and Communication

• Canvas: Homework, assignments, and course materials will be posted on Canvas.
  https://canvas.cmu.edu/courses/51095
• Piazza: Questions, comments, and informal communication will take place on Piazza.
  https://piazza.com/class/mk4a0cn1bgr6qt
• Email: Important communications, including absences, should be emailed directly to the instructors.
• Recordings: Class recordings may be released upon request to Dr. Raj.

Grading

• Homework: 30%
• Group Project: 30%
• Participation: 10%
• Weekly Quizzes: 30%

Assignments and Quizzes

TBD. Details on homework, quizzes, and the group project will be posted on Canvas.

Attendance

TBD. Students are expected to attend regularly and participate in both lecture and lab sessions.

Schedule (Tentative)

See the course homepage for the current schedule and updates.

Policies

Academic Integrity
TBD. Follow CMU policies on academic integrity. Collaboration guidelines will be posted on Canvas.

Accessibility
TBD. Students needing accommodations should contact the instructors and the Office of Disability Resources.

Late Work
TBD. Late work policies will be posted on Canvas.