CS428 Principles of Quantum Computing
CS428 Principles of Quantum Computing
Syllabus | International University of Sarajevo - Last Update on Mar 03, 2026
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Computer Sciences and Engineering
Ali Almisreb
Course Lecturer
Course Objectives
The objectives of the course are: 1. To provide students with the necessary knowledge about quantum computing and the world's most recent quantum programming tools. 2. To help students embrace this futuristic technology and participate in applying quantum technologies to solve problems. 3. To Introduce the Quantum Gates and their usage in Quantum circuits. 4. To Introduce the Quantum circuits and their implementation in solving real-world problems.
Learning Outcomes
After successful completion of the course, the student will be able to:
Course Materials
Required Textbook
1. Learn Quantum Computation Using Qiskit, [Online], IBM, 2023. 2. Michael Nielsen and Isaac Chuang, Quantum Computation and Quantum Information: 10th Anniversary Edition, 2010. 3. N. David Mermin, Quantum Computer Science An Introduction, Cambridge University Press, 2007. 4. David McMahon, Quantum computing explained, Wiley, 2007.
Additional Literature
1. Chubb, Jennifer, Ali Eskandarian, and Valentina Harizanov, eds. Logic and Algebraic Structures in Quantum Computing. Vol. 45. Cambridge University Press, 2016. 2. Bera, Rajendra K. The Amazing World of Quantum Computing. Springer, 2020. 3. Hassi Norlén. Quantum Computing in Practice with Qiskit® and IBM Quantum Experience®: Practical recipes for quantum computer coding at the gate and algorithm level with Python, Packt, November 23, 2020. 4. Hidary, Jack D, Quantum Computing: An Applied Approach, Springer, 2019. 5. https://ocw.mit.edu/courses/media-arts-and-sciences/mas-865j-quantum-information-science-spring-2006/lecture-notes/Teaching Methods
Classes will be carried out through weekly lessons
Including lab programming examples and practical exercises.
Weekly Topics
| Week | Topic | Readings / References |
|---|---|---|
| 1 | Introduction to Linear Algebra for Quantum Computing | Qiskit Textbook Chapter 0 and Hands-on |
| 2 | Quantum Computation: History & Overview | Mike & Ike Chapter 1 |
| 3 | Quantum states and Qubits | Qiskit Textbook-Chapter 1 |
| 4 | Single Qubits and Multi-Qubits gates | Qiskit Textbook-Chapter 2 |
| 5 | Quantum Problems | Qiskit Textbook and Hands-on |
| 6 | Quantum Algorithms: Teleportation, Superdense Coding, Deutsch-Josza Algorithm | Qiskit Textbook-Chapter 3 |
| 7 | Mid-Term Exam | |
| 8 | Quantum Algorithms: Bernstein-Vazirani, Simon's Algorithm, Quantum Fourier Transform | Qiskit Textbook-Chapter 3 |
| 9 | Quantum Algorithms for Applications | Qiskit Textbook-Chapter 4 |
| 10 | Investigating Quantum Hardware Using Qiskit: Calibrating qubits, Introduction to Quantum Error Correction | Qiskit Textbook-Chapter 5 |
| 11 | Investigating Quantum Hardware Using Qiskit: Randomized Benchmarking, Measuring Quantum Volume | Qiskit Textbook-Chapter 5 |
| 12 | Implementations of Recent Quantum Algorithms: The Variational Quantum Linear Solver | Qiskit Textbook-Chapter 6 |
| 13 | Quantum Cryptography | Quantum computing explained-Chapter 11 |
| 14 | Grovers search algorithm | Qiskit Textbook-3.8 |
| 15 | Introduction to Quantum Machine Learning | Qiskit Textbook |
Course Schedule (All Sections)
Office Hours & Room
| Day | Time | Office | Notes |
|---|---|---|---|
| Thursday | 09:00 - 11:55 | A F2.6 | |
| Friday | 09:00 - 11:55 | A F2.6 |
Assessment Methods and Criteria
Assessment Components
Final Exam
AI: Not AllowedAlignment with Learning Outcomes :
Lab Work
AI: Not AllowedAlignment with Learning Outcomes :
Exercises
AI: Not AllowedAlignment with Learning Outcomes :
Quizzes
AI: Not AllowedAlignment with Learning Outcomes :
Midterm
AI: Not AllowedAlignment with Learning Outcomes :
IUS Grading System
| Grading Scale | IUS Grading System | IUS Coeff. | Letter (B&H) | Numerical (B&H) |
|---|---|---|---|---|
| 0 - 44 | F | 0 | F | 5 |
| 45 - 54 | E | 1 | ||
| 55 - 64 | C | 2 | E | 6 |
| 65 - 69 | C+ | 2.3 | D | 7 |
| 70 -74 | B- | 2.7 | ||
| 75 - 79 | B | 3 | C | 8 |
| 80 - 84 | B+ | 3.3 | ||
| 85 - 94 | A- | 3.7 | B | 9 |
| 95 - 100 | A | 4 | A | 10 |
Late Work Policy
Information about late submission policies will be shared during class and posted in this section. Please check back for official guidelines.
ECTS Credit Calculation
📚 Student Workload
This 6 ECTS credit course corresponds to 150 hours of total student workload, distributed as follows:
home study
30 hours ⏳ (15 week × 2 h)
final exam
20 hours ⏳ (2 week × 10 h)
Lab Work
30 hours ⏳ (15 week × 2 h)
Exercises
20 hours ⏳ (10 week × 2 h)
Quizzes
10 hours ⏳ (2 week × 5 h)
mid-term exam
40 hours ⏳ (2 week × 20 h)
150 Total Workload Hours
6 ECTS Credits
Course Policies
Academic Integrity
All work submitted must be your own. Plagiarism, cheating, or any form of academic dishonesty will result in disciplinary action according to university policies. When in doubt about citation practices, consult the instructor.
Attendance Policy
Students are expected to adhere to the attendance requirements as outlined in the International University of Sarajevo Study Rules and Regulations. Excessive absences, whether excused or unexcused, may impact academic performance and eligibility for assessment. Mandatory sessions (e.g., labs, workshops) require attendance unless formally exempted. For detailed policies on absences, documentation, and penalties, please refer to the official university regulations.
Technology & AI Policy
Laptops/tablets may be used for note-taking only during lectures. Phones should be silenced and put away during all class sessions. Audio/video recording requires prior permission from the instructor.
Artificial Intelligence (AI) Usage: The use of AI tools (e.g., ChatGPT, Copilot, Gemini) varies by assessment component. Please refer to the AI usage indicator next to each assessment item in the Assessment Methods and Criteria section above. Submitting AI-generated content as your own work, where AI is not explicitly allowed, constitutes an academic integrity violation.
Communication Policy
All course-related communication should occur through official university channels (institutional email or SIS). Emails should include [CS428] in the subject line.
Academic Quality Assurance Policy
Course Academic Quality Assurance is achieved through Semester Student Survey. At the end of each academic year, the institution of higher education is obliged to evaluate work of the academic staff, or the success of realization of the curricula.
Learning Tips
Be prepared to contribute thoughtfully during class discussions, labs, or collaborative work. Active participation deepens understanding and encourages critical thinking.
Complete assigned readings or prep materials before class. Take notes, highlight key ideas, and jot down questions. Aim to grasp core concepts and their applications—not just facts.
Use course frameworks or methodologies to analyze problems, case studies, or projects. Begin early to allow time for reflection and refinement. Seek feedback to improve your work.
Don’t hesitate to reach out when something is unclear. Use office hours, discussion boards, or peer networks to clarify concepts and stay on track.
Syllabus Last Updated on Mar 03, 2026 | International University of Sarajevo
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Referencing Curricula Print this page
| Course Code | Course Title | Weekly Hours* | ECTS | Weekly Class Schedule | ||||||
| T | P | |||||||||
| CS428 | Principles of Quantum Computing | 3 | 2 | 6 | Friday, 09:00-11:50 | |||||
| Prerequisite | None | It is a prerequisite to | - | |||||||
| Lecturer | Ali Almisreb | Office Hours / Room / Phone | Thursday: 9:00-11:55 Friday: 9:00-11:55 |
|||||||
| aalmisreb@ius.edu.ba | ||||||||||
| Assistant | Assistant E-mail | |||||||||
| Course Objectives | The objectives of the course are: 1. To provide students with the necessary knowledge about quantum computing and the world's most recent quantum programming tools. 2. To help students embrace this futuristic technology and participate in applying quantum technologies to solve problems. 3. To Introduce the Quantum Gates and their usage in Quantum circuits. 4. To Introduce the Quantum circuits and their implementation in solving real-world problems. |
|||||||||
| Textbook | 1. Learn Quantum Computation Using Qiskit, [Online], IBM, 2023. 2. Michael Nielsen and Isaac Chuang, Quantum Computation and Quantum Information: 10th Anniversary Edition, 2010. 3. N. David Mermin, Quantum Computer Science An Introduction, Cambridge University Press, 2007. 4. David McMahon, Quantum computing explained, Wiley, 2007. | |||||||||
| Additional Literature |
|
|||||||||
| Learning Outcomes | After successful completion of the course, the student will be able to: | |||||||||
|
||||||||||
| Teaching Methods | Classes will be carried out through weekly lessons, including lab programming examples and practical exercises. | |||||||||
| Teaching Method Delivery | Face-to-face | Teaching Method Delivery Notes | ||||||||
| WEEK | TOPIC | REFERENCE | ||||||||
| Week 1 | Introduction to Linear Algebra for Quantum Computing | Qiskit Textbook Chapter 0 and Hands-on | ||||||||
| Week 2 | Quantum Computation: History & Overview | Mike & Ike Chapter 1 | ||||||||
| Week 3 | Quantum states and Qubits | Qiskit Textbook-Chapter 1 | ||||||||
| Week 4 | Single Qubits and Multi-Qubits gates | Qiskit Textbook-Chapter 2 | ||||||||
| Week 5 | Quantum Problems | Qiskit Textbook and Hands-on | ||||||||
| Week 6 | Quantum Algorithms: Teleportation, Superdense Coding, Deutsch-Josza Algorithm | Qiskit Textbook-Chapter 3 | ||||||||
| Week 7 | Mid-Term Exam | |||||||||
| Week 8 | Quantum Algorithms: Bernstein-Vazirani, Simon's Algorithm, Quantum Fourier Transform | Qiskit Textbook-Chapter 3 | ||||||||
| Week 9 | Quantum Algorithms for Applications | Qiskit Textbook-Chapter 4 | ||||||||
| Week 10 | Investigating Quantum Hardware Using Qiskit: Calibrating qubits, Introduction to Quantum Error Correction | Qiskit Textbook-Chapter 5 | ||||||||
| Week 11 | Investigating Quantum Hardware Using Qiskit: Randomized Benchmarking, Measuring Quantum Volume | Qiskit Textbook-Chapter 5 | ||||||||
| Week 12 | Implementations of Recent Quantum Algorithms: The Variational Quantum Linear Solver | Qiskit Textbook-Chapter 6 | ||||||||
| Week 13 | Quantum Cryptography | Quantum computing explained-Chapter 11 | ||||||||
| Week 14 | Grovers search algorithm | Qiskit Textbook-3.8 | ||||||||
| Week 15 | Introduction to Quantum Machine Learning | Qiskit Textbook | ||||||||
| Assessment Methods and Criteria | Evaluation Tool | Quantity | Weight | Alignment with LOs | AI Usage |
| Final Exam | 1 | 40 | Not Allowed | ||
| Semester Evaluation Components | |||||
| Lab Work | 5 | 15 | Not Allowed | ||
| Exercises | 5 | 10 | Not Allowed | ||
| Quizzes | 2 | 10 | Not Allowed | ||
| Midterm | 1 | 25 | Not Allowed | ||
| *** ECTS Credit Calculation *** | |||||
| Activity | Hours | Weeks | Student Workload Hours | Activity | Hours | Weeks | Student Workload Hours | |||
| home study | 2 | 15 | 30 | final exam | 10 | 2 | 20 | |||
| Lab Work | 2 | 15 | 30 | Exercises | 2 | 10 | 20 | |||
| Quizzes | 5 | 2 | 10 | mid-term exam | 20 | 2 | 40 | |||
| Total Workload Hours = | 150 | |||||||||
| *T= Teaching, P= Practice | ECTS Credit = | 6 | ||||||||
| Course Academic Quality Assurance: Semester Student Survey | Last Update Date: 27/03/2026 | |||||||||