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2022-06-26T21:35:21Z

IT & SoftwareOther IT & SoftwareQuantum Computing

Quantum Mechanical Networks, QDeepMind & Quantum Encryption

Learn from basics of Quantum Mechanics & Bayesian Statistics to Quantum Machines (25+ Implementations in Qiskit)
Rating: 4.2 out of 54.2 (56 ratings)
12,296 students
Created by Junaid Zafar
Last updated 6/2022
English
English [Auto]

What you'll learn

  • Basics of Quantum Computing with its Qiskit Implementation
  • Quantum gates and Quantum codes in Qiskit and Pennylane
  • Quantum modeling using Quantum Variational Circuits
  • Measurements in Quantum Computing using Quantum Simulators
  • NISQs and Decoherence in Quantum Computing
  • Building a Quantum Computer
  • Fundamentals of Quantum Computing
  • Quantum Computing Exercises with Solutions
  • Quantum Encryption

Requirements

  • Students would be able to learn from scratch. No Pre- requisite is required
  • No programming skills are required.

Description

This course would enable you to gain insight into the realm of Quantum Computing. The students would be able to learn and develop expertise in Quantum algorithms, gates, and implementation of these codes. The undergraduate students would particularly find it very imperative for realizing their final year projects and reports.

Furthermore, this course is an introduction to the fundamental concepts of quantum circuits and algorithms. The course will provide tools that allow students to implement quantum circuits and algorithms using quantum computing libraries and to run them using quantum simulators as well as real hardware.

The following topics shall be covered;

1. Quantum Computing.

2. Classical Computing vs Quantum Computing.

3. Impact of Quantum Computing on Cloud Computing.

4. Quantum Superposition & Quantum Entanglement.

5. Quantum Gates.

6. Quantum Variational Circuits.

7. Optimization through Quantum Annealing.

8. Quantum Measurements.

9. Noisy Intermediate Scale Quantum Computing (NISQs).

10. Building a Quantum Computer

11. Impact of Quantum computing in cyberspace.

12. Quantum algorithms and code examples.

13. Implementation and testing of all codes in Qiskit.

14. Quantum Robot implementation in Qiskit.

15. Quantum Financial Systems and Markets.

16. Quantum Computing for Computer Vision.

17. Quantum Computing using NLP.

18. Quantum Programming Languages including .NET platform.

19. 25+ Coding Practice Problems with Solutions in QISKIT



At the end of the course the student will be able:

  • To describe the differences between quantum and classic computation.

  • To build quantum circuits connecting different types of quantum gates.

  • To implement quantum circuits and algorithms using quantum programming libraries.

  • To run quantum circuits and algorithms using quantum simulators and real quantum computers.

  • To understand how to design quantum algorithms to solve multifarious problems.

Who this course is for:

  • Beginners aspire to learn Quantum Computing from the very basics to the cutting edge topics
  • Learners aim to develop expertise of quantum simulators for modelling and testing
  • Research and Academic Students working in the realm of Data Science, Machine Learning, Quantum Computing and Reinforced Learning

Instructor

Junaid Zafar
Dr. Engr. Junaid Zafar- Academician with 20 years experience
Junaid Zafar
  • 4.0 Instructor Rating
  • 435 Reviews
  • 42,919 Students
  • 9 Courses

Prof. Dr. Engr. Junaid Zafar is currently working as Chairperson in Department of Electrical and Computer Engineering, Government College University, Lahore. He is also Director, Office of Research, innovation and Commercialization. He has completed his PhD in Electrical and Electronics Engineering, The University of Manchester University, UK, and BSc in Electrical Engineering from U.E.T Lahore. He is Academic visitor to the University of Cambridge, UK, MMU, UK and National University of Ireland. He remained Dual Degree programme coordinator at the Lancaster University, UK. Dr. Engr. Junaid Zafar received Roll of Honors for National Education Commission and Outstanding Teacher/ Researcher Awards from the Higher Education Commission, Pakistan. He is leading the macine learning and Artificial Intelligence centre with GC University, Lahore. He is member of Universal Association of Electronics & Computer Engineers, International Association of Computer Science & Information, and member of International Association of Engineers, IAENG Society of Artificial Intelligence, IAENG Society of Electrical Engineering, Science & Engineering Institute, IAENG Society of Imaging Engineering, Institute of Research Engineers & Doctors, and IAENG Society of Wireless Networks. He is member of editorial board in Journal of Future Technologies & Communications, Technical Programme committee, Frontiers of Information & Technologies, and Technical Programme Committee, Multi- Conference on Sciences & Technology. He is also serving as reviewer for IEEE Transactions on Microwave Theory & Techniques, IEEE Transactions on Antennas, IEEE Antenna & Wireless Propagation Letters, IEEE Transactions on Plasma Science, IEEE Transactions on Magnetics, International Journal of Electronics, and IET Antennas & Radio- wave Propagation. He has so far taught over twenty diffrent online courses based on outcome based student oriented models. He has also supervised more than 100 Masters/ MPhil thesis. He has published over 50 high impact factor publications and presented his work at several national and international renowned platforms.

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