Minor in Quantum Computing, Florida Memorial University

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Recommended Program Overview

An 18-credit minor program preparing students for the quantum computing revolution. Designed to complement major programs in Computer Science, Physics, Mathematics, or Engineering.

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Prerequisites

• Calculus I & II

• Linear Algebra

• Introduction to Programming

• Modern Physics (recommended)

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Required Core Courses (12 credits)

QC 201: Introduction to Quantum Computing (3 credits)

• Quantum mechanics fundamentals

• Quantum bits and quantum gates

• Superposition and entanglement

• Basic quantum algorithms

• Hands-on programming with Qiskit

QC 301: Quantum Algorithms and Complexity (3 credits)

• Quantum circuit model

• Famous quantum algorithms

  • Deutsch-Jozsa

  • Grover's search

  • Shor's factoring

• Quantum complexity theory

• Quantum advantage cases

QC 302: Quantum Programming and Frameworks (3 credits)

• Qiskit programming

• Q# and Cirq

• Quantum simulation

• Error correction basics

• Cloud quantum computers

• Programming exercises on real quantum hardware

QC 401: Applied Quantum Computing (3 credits)

• Industry applications

• Quantum machine learning

• Quantum optimization

• Quantum cryptography

• Current quantum hardware

• Industry case studies

Elective Courses (Choose 2 - 6 credits total)

QC 303: Quantum Error Correction (3 credits)

• Error types and sources

• Error correction codes

• Fault tolerance

• Surface codes

• Practical implementations

QC 304: Quantum Machine Learning (3 credits)

• Quantum neural networks

• Quantum variational algorithms

• Quantum feature spaces

• Quantum kernels

• Hybrid quantum-classical algorithms

QC 402: Quantum Cryptography (3 credits)

• Quantum key distribution

• Post-quantum cryptography

• Quantum random number generation

• Security proofs

• Implementation challenges

QC 403: Quantum Hardware Systems (3 credits)

• Superconducting qubits

• Ion traps

• Photonic quantum computing

• Control systems

• Measurement techniques

Required Technologies & Tools

• Programming Languages:

  • Python (primary)

  • Q#

  • Qiskit

  • Cirq

  • PyQuil

• Quantum Cloud Platforms:

  • IBM Quantum Experience

  • Amazon Braket

  • Azure Quantum

  • Google Quantum AI

Learning Outcomes

1. Understand quantum computing principles and mathematics

2. Program basic quantum algorithms

3. Analyze quantum algorithm complexity

4. Apply quantum computing to real-world problems

5. Evaluate current quantum technologies

6. Develop quantum-classical hybrid solutions

Career Enhancement

• Quantum Software Developer

• Quantum Algorithm Researcher

• Quantum Applications Scientist

• Quantum Systems Engineer

• Quantum Security Analyst

Industry Certifications Available

• IBM Quantum Certification

• Azure Quantum Development

• Amazon Braket Certification

Special Requirements

• Capstone project in final course

• Access to cloud quantum computers

• Participation in quantum computing seminars

• Industry guest speaker series

Recommended Sequence

1. QC 201 (Fall)

2. QC 301 (Spring)

3. QC 302 (Fall)

4. QC 401 (Spring)

5. Electives (Any semester after QC 201)