QC101 Quantum Computing & Intro to Quantum Machine Learning

Math-Based Introduction to Quantum Computing, Cryptography & Quantum Machine Learning. Code with Python, Q#, & Qiskit

Created by: Kumaresan Ramanathan
Principal Architect at Coroman Systems

What Will I Learn?

• Use quantum cryptography to communicate securely
• Develop, simulate, and debug quantum programs on IBM Qiskit and Microsoft Q#
• Run quantum programs on a real quantum computer through IBM Quantum Experience
• Use Dirac's notation and quantum physics models to analyze quantum circuits
• Train a Quantum Support Vector Machine (Quantum Machine Learning) on real-world data and use it to make predictions
• Learn Data science and how quantum computing can help in artificial intelligence / machine learning
• Learn why machine learning will be the killer-app for quantum computing

Requirements

• 12th grade level high-school Math and Physics
• You must have studied Math and Physics upt o 12th grade level and *enjoyed* it. Quantum Computing is primarily about Math & Physics. There is very little coding involved.
• 12th grade level, high school Math: Complex numbers, linear algebra, probability, statistics, & boolean logic

Target audience

• Software professionals and technical managers who want to learn quantum computing and enjoy Math & Physics
• Machine Learning and AI professionals who want to learn how quantum computing can be used in data science