“Qiskit Mastery : Advanced Concepts in Quantum Computing”

Prerequisites: 

Linear Algebra and Basic Python Programming, Basics of Quantum Mechanics

Course description:

This advanced course provides learners with a formal introduction to the basics of quantum computing, including topics such as the density matrix formalism. It serves as a foundation for diving deeper into advanced quantum concepts.

Participants will also gain practical skills in constructing quantum circuits and implementing quantum algorithms using the Qiskit framework. Key algorithms covered in the course include Variational Quantum Eigensolver (VQE), Quantum Approximate Optimization Algorithm (QAOA), and Quantum Machine Learning (QML).

The course places significant emphasis on exploring the various applications of quantum computing in real-world scenarios. Learners will delve into areas such as data classification, portfolio optimization, cryptography, and quantum chemistry. By studying these applications, participants will gain insights into how quantum computing can be applied to solve complex problems across different domains.

Upon completion of the course, learners will be equipped with the ability to read and understand technical and research papers in the field of quantum computing. They will also have the skills necessary to tackle industrial or research problems, leveraging the knowledge gained throughout the course to propose innovative quantum computing solutions.

Instructor:

Mr. Chetan Waghela, Advisory Research Scientist at Qkrishi and Research Scholar at IIT Ropar