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Enrollment Now Open | Start Date September 7, 2026

Ä¢¹½ÊÓƵ's Introduction to Quantum Computing microcredential offers an accessible, hands-on exploration of quantum computing for learners with a foundational understanding of linear algebra and matrices. The course breaks down complex quantum concepts into intuitive, interactive modules that introduce the principles of quantum information science. Participants will investigate how quantum systems operate, why they differ from classical computing, and how they are poised to transform areas such as secure communication and cryptography.

Using web-based simulations and guided experiments, learners will model quantum behaviors, test algorithms, and gain a deeper understanding of the potential applications of quantum technologies. Delivered primarily online, the course includes a collaborative discussion board and optional in-person sessions for hands-on labs, Q&A, and networking.

Cost $849 | Early Bird Discount for Registrations Received by August 15 |

Course Details

Two Optional In-Person Lab Dates: TBD

Credential Educational Goals:

Upon completing the micro-credential, learners will be prepared to:

• Develop foundational technical competency in quantum computing
• Interpret and communicate complex quantum concepts clearly and intuitively
• Recognize the emerging workforce impact of quantum technologies 

Learner Outcomes:

Upon completion of the credential program, the learner will have the ability to:

• Explain the differences between bits and qubits and describe how quantum information is represented.
• Apply 1-qubit and 2-qubit gate operations to build simple quantum circuits, demonstrating familiarity with fundamental quantum gate behavior.
• Describe and analyze the concepts of superposition and entanglement, including the ability to evaluate basic quantum state transformations.
• Explain and compare introductory quantum algorithms, such as the Deutsch and Grover algorithms, including their effectiveness relative to classical algorithms.
• Identify sources of noise in quantum systems and analyze the effectiveness of simple quantum error correction codes in mitigating these effects.
• Describe the implications of quantum computing for cryptography, including the ability to explain key concepts such as quantum teleportation and their relevance to secure communication. 

Recommended Prerequisites:

1) Math: Basic Linear Algebra and Probability
2) Programming (helpful, but not required)
3) Logical Thinking
4) Interest in Emerging Technologies.

Course Features

This self-paced micro-credential includes a comprehensive set of materials designed to support your learning and skill development:

• 30+ engaging lecture videos
• 20 detailed lecture notes
• 10 hands-on lab experiments
• 15 short quizzes for reinforcement
• 4 tests to assess your understanding 

These resources provide structured, interactive, and in-depth instruction, whether you're exploring quantum computing for the first time or expanding your technical foundation.

Enrollment Now Open | Start Date October 12, 2026

Build on your foundational knowledge of quantum computing through an applied introduction to quantum optimization and simulation. This course explores QAOA and VQE through practical examples in molecular energy, protein structure analysis, automotive systems, and graph-based optimization. Designed for learners ready to move beyond introductory concepts, it offers a focused next step toward more advanced study and technical application.

Cost $1005 | Early Bird Discount for Registrations Received by September 30th
Students who have completed Ä¢¹½ÊÓƵ's Intro to Quantum Computing qualify for an additional discount.

Quantum Optimization and Simulation moves beyond introductory quantum concepts to examine how quantum algorithms can be used to address complex optimization and simulation problems.

Designed as the next step following Ä¢¹½ÊÓƵ's Introduction to Quantum Computing, this applied course focuses on two important variational quantum algorithms: the Quantum Approximate Optimization Algorithm, or QAOA, and the Variational Quantum Eigensolver, or VQE.

QAOA is used to explore approximate solutions to combinatorial optimization problems, while VQE combines quantum and classical computing methods to estimate properties of quantum systems. These algorithms provide an important foundation for understanding how emerging quantum methods may be applied to scientific, engineering, manufacturing, logistics, and computational challenges.

Through guided instruction and practical implementation, participants will examine applications involving:

• Molecular energy estimation
• Protein structure analysis using the hydrophobic-polar, or HP, model
• Automotive suspension system optimization
• Max-Cut graph problems
• Knapsack and resource-allocation problems

The course emphasizes not only how the algorithms work, but also how problems are formulated, how results are evaluated, and when a quantum or hybrid approach may or may not be appropriate.

Upon successful completion of the course, participants should be able to:

1. Explain the purposes and basic structures of QAOA and VQE.
2. Distinguish between optimization problems appropriate for QAOA and simulation problems commonly approached through VQE.
3. Translate an applied problem into an objective function, constraint structure, Hamiltonian, graph, or other computational representation.
4. Construct and execute a basic variational quantum workflow.
5. Apply QAOA or VQE to selected scientific, engineering, or optimization problems.
6. Evaluate algorithm convergence, parameter behavior, circuit depth, and output quality.
7. Compare results produced through quantum, hybrid, and classical methods.
8. Identify the practical limitations of current quantum optimization and simulation approaches.
9. Interpret computational results and communicate conclusions in relation to an applied problem, research question, or decision context.

Build practical knowledge of quantum communication security while developing experience with the error correction and mitigation strategies needed to work with today's quantum systems.

This advanced microcredential introduces quantum key distribution protocols, common sources of quantum error, foundational approaches to quantum error correction, and practical error mitigation techniques. Through guided Qiskit experiments, learners will examine how quantum information can be transmitted securely, how noise affects quantum systems, and how researchers and practitioners work to improve the reliability of quantum computations.

The course is designed for technically prepared professionals, researchers, engineers, programmers, and advanced learners interested in quantum communications, cybersecurity, quantum computing, and emerging technology applications.

By completing this course, learners will be able to:

• Explain the principles of quantum communication and the security foundations of quantum key distribution.
• Compare selected QKD protocols and evaluate their potential applications and limitations.
• Identify common sources of noise, decoherence, and computational error in quantum systems.
• Explain foundational quantum error correction methods and their role in reliable quantum computing.
• Apply selected error mitigation techniques through hands-on Qiskit experiments.
• Interpret experimental results and assess the effectiveness of correction and mitigation strategies.