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In this course you will learn how to use Qiskit for working with quantum computers. Qiskit is an SDK for working at the level of pulses, circuits, algorithms and application modules. During the first week you will explore the available tools to run your experiments on IBM Quantum computers in the cloud, write your first lines of Qiskit code, do a recap of the fundamentals of quantum computing and understand how to run experiments both on simulators and on quantum devices. During the second week you will use everything you have learnt to implement two of the first quantum computing algorithms.
Language: English
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Advanced, Quantum Computing
Course information
In this course you will learn how to use Qiskit for working with quantum computers. Qiskit is an SDK for working at the level of pulses, circuits, algorithms and application modules. During the first week you will explore the available tools to run your experiments on IBM Quantum computers in the cloud (IBM Quantum Composer and IBM Quantum Lab), write your first lines of Qiskit code, do a recap of the fundamentals of quantum computing and understand how to run experiments both on simulators and on quantum devices. During the second week you will use everything you have learnt to implement two of the first quantum computing algorithms. You will first learn about the Deutsch-Jozsa algorithm, one of the first examples showing the speed-up of quantum algorithms. Then you will learn how to find solutions faster with Grover’s algorithm, implement it with Qiskit and apply it to solve a satisfiability problem. As you will see when implementing your circuits on real hardware, present day quantum computers are subject to various kinds of noise. The principle behind error mitigation is to reduce the effects from a specific source of error by classically post-processing the counts. In the final lecture, you will learn how to mitigate measurement errors, i.e., errors in determining the correct quantum state from measurements performed on qubits.
Quantum Computing Summer School:
Please note that this course has been reactivated as part of the Quantum Computing Summer School. You have the opportunity to complete the course independently with a record of achievement.
New deadline for submitting graded assignments: Tuesday, October 15, 2024, at 11:55 PM UTC.
Attention: This course is currently in self-study mode, in which you do not have access to graded assignments/exams. Therefore, we can only issue you a certificate of participation.
Course contents
Intro
Week 1:
In the first week, we will have a look at what Qiskit actually is and what IBM is planning for the next months and years. Get to know the IBM Quantum Services Platform, recap the main quantum computing concepts and write your first code. Visualisation Tools and Simulators are part of the first course week as well as running circuits on quantum hardware as a basis for quantum algorithms that we will have a look at in week 2.Week 2:
In Week 2, we will start implementing real algorithms such as Grover's Algorithm or Deutsch-Jozsa and we will have a look at Measurement Error Mitigation.Final exam
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Learners
Certificate Requirements
- Gain a Record of Achievement by earning at least 50% of the maximum number of points from all graded assignments.
- Gain a Confirmation of Participation by completing at least 50% of the course material.
- Gain an Open Badge by completing the course.
Find out more in the certificate guidelines.
This course is offered by
Elisa just finished her PhD at ETH Zurich in quantum information theory. She is now working for the IBM Quantum Community Team focusing on enabling researchers adopting Qiskit as well as on outreaching events and creating educational content.
Carmen is a mathematician specialized in Applied Mathematics. She is currently working as an advocate in the IBM Quantum community team. She focuses on outreach, education and community activities around Quantum Computing.