Quantum Computing - course description

General information

Course name	Quantum Computing
Course ID	11.3-WK-DEED-QC-S22
Faculty	Faculty of Mathematics, Computer Science and Econometrics
Field of study	Data Engineering
Education profile	academic
Level of studies	Second-cycle studies leading to MS degree
Beginning semester	summer term 2023/2024

Course information

Semester	3
ECTS credits to win	5
Course type	optional
Teaching language	english
Author of syllabus	mgr inż. Andrzej Majczak

Classes forms

The class form	Hours per semester (full-time)	Hours per week (full-time)	Hours per semester (part-time)	Hours per week (part-time)	Form of assignment
Lecture	30	2	-	-	Credit with grade
Laboratory	30	2	-	-	Credit with grade

Aim of the course

Presentation of the concept of quantum computers.
Presenting examples of quantum computing and the application of quantum computers.
The student will acquire knowledge and skills in the basics of quantum computer programming.

Prerequisites

Linear algebra, basics of C/C++, Java or Python programming.

Scope

Lecture

Why we need quantum computers.
How quantum computers work.
What is quantum computing.
Quantum concepts including superposition, entanglement and uncertainty.
Learning to program in quantum computing.
Where quantum computers are used.
Case study of how quantum can improve industry applications.

Laboratory

IBM Quantum Network.
Introduction to the Qiskit platform, SDK (Software Development Kit)
Coding the first quantum circuit using the Qiskit platform.
Creating and running circuits using IBM Quantum Composer.
Prototype cloud applications.
Quantum programs in Python.
Advanced research in quantum computing.

Teaching methods

Lecture: Problem lecture, presentation of quantum concepts and case study.
Laboratory: Laboratory exercises in a computer lab, writing and running self-written programs on topics given by the instructor.

Learning outcomes and methods of theirs verification

Outcome description	Outcome symbols	Methods of verification	The class form

Assignment conditions

Checking the degree of students' preparation and their activity during laboratory exercises.

Obtaining positive grades from laboratory exercises planned for implementation as part of the laboratory program.

A written test to pass the lecture, consisting of questions and tasks verifying knowledge of the material covered.

The final grade for the course consists of the laboratory grade (50%) and the lecture grade (50%). The condition for passing the course is a positive grade in the laboratory lecture.

Notes

Modified by dr Maciej Niedziela (last modification: 30-04-2024 17:21)

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