The future is no longer a mere prediction; it is an algorithm currently being written. The world of computing stands on the brink of its greatest leap since the invention of the transistor.
The future is no longer a mere prediction; it is an algorithm currently being written. The world of computing stands on the brink of its greatest leap since the invention of the transistor. As classical computers approach their physical limits, quantum computing has emerged as the only viable path to solving problems that remain beyond the reach of today’s supercomputers—ranging from simulating drug molecules and designing new materials to optimizing supply chains and discovering advanced AI algorithms. Yet, the key question remains: how can we harness this power? The answer lies in a layer beyond quantum physics itself: the realm of software and programming. The comprehensive "Quantum Language Programming" course takes you directly to the heart of this transformation. In this course, you will go beyond mere abstract theories; you will be introduced to three powerful, practical frameworks, each serving as a gateway to a distinct realm of computing: • Qiskit (IBM): For entering the industry-standard world of gate-based computing using discrete qubits. • PennyLane (Xanadu): For transcending traditional boundaries and entering the exciting domain of photonic computing, featuring seamless integration with machine learning (TensorFlow, PyTorch). • Ocean (D-Wave): For mastering the adiabatic model and solving complex, large-scale optimization problems at an industrial level.

Introduction to Quantum Computing and Quantum Programming
Bernstein–Vazirani Algorithm، Simon’s Algorithm
Fundamental Quantum Algorithms and Their Implementation with Qiskit
Bernstein–Vazirani Algorithm Simon’s Algorithm
Variational Quantum Algorithms and Their Implementation with Qiskit
Variational Algorithms، Quantum Approximate، Optimization Algorithm (QAOA)، MaxCut Problem
Ramezani Mehdi
Instructor
فاطمه لاجوردی
Instructor
ٌصادق سلامی
Instructor
Required Prerequisites (in order of priority): Basic familiarity with Python programming Basic knowledge of linear algebra concepts, including vectors, matrices, and simple operations on them Familiarity with probability, computational logic, and/or introductory quantum physics concepts Ability to work with programming environments such as Jupyter Notebook or similar platforms
The course will be conducted primarily in a theoretical format, while participants will also receive coding exercises and assignments to reinforce the concepts covered.
Quantum Teleportation Protocol and Its Implementation with Qiskit
Quantum Teleportation
Simulation of Quantum Processes Using AerSimulator and Qiskit Aer
AerSimulator and the qiskit-aer Module Different Simulation Methods and Their Comparison
Transpiling Quantum Circuits and Running Simulations on GPUs
Introduction to the Transpile Module in Qiskit، Why Quantum Circuit Transpilation Is Necessary، GPU Support in AerSimulator
Quantum Machine Learning and Its Implementation with Qiskit
Machine Learning، Neural Networks، Backpropagation Algorithm، Convolutional Neural Networks (CNNs)، Quantum Convolutional Neural Networks (QCNNs)
Noise Analysis and Its Implementation with Qiskit
Quantum Noise Channels
Price
Yes. The recorded sessions will be made available to participants through SpotPlayer.
Yes. Participants will receive a Certificate of Participation from Sharif University of Technology.
Price

Official Certificate
Receive a Certificate of Completion from Sharif University of Technology
Course Support
Academic and administrative support during and after the course
Access to Course Content
Access to recorded course videos and educational materials
Practice-Based Learning
Learn through hands-on exercises and explore problems related to each topic
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