This program offers 5 mock tests designed to assess your quantum computing knowledge. Each test covers key topics such as quantum mechanics, algorithms, hardware, and quantum programming, ensuring you’re fully prepared for real-world quantum computing assessments.
This assessment program includes 5 mock tests designed to evaluate your proficiency in Quantum Machine Learning (QML) concepts. It covers a wide range of QML topics, from quantum data encoding to quantum neural networks, offering a practical and structured way to prepare for certifications, interviews, or exams.
This assessment program includes 5 mock tests designed to evaluate your understanding of Quantum Optimization concepts. Each test covers key topics such as optimization problems, quantum annealing, and variational algorithms, helping you prepare for certifications, job interviews, or exams in quantum optimization.
Develop a quantum circuit visualization tool.
Implement quantum gates and state evolution.
Simulate quantum operations interactively.
Integrate with quantum frameworks (Qiskit/Cirq).
Analyze quantum state changes and superposition.
Deploy a functional quantum gate simulator.
This capstone explores QAOA for solving the MaxCut problem. Participants will implement QAOA, optimize graph partitioning, and compare quantum vs. classical performance using real-world datasets and quantum computing frameworks.
This capstone explores QKNN for classification, leveraging quantum computing to enhance distance-based learning. Participants will implement and analyze QKNN using quantum frameworks and real-world datasets.
Understand quantum optimization fundamentals.
Implement QAOA and quantum annealing algorithms.
Compare classical vs. quantum portfolio strategies.
Work with financial datasets for asset allocation.
Optimize risk-return trade-offs using quantum techniques.
Evaluate performance metrics and real-world applicability.
This capstone explores QSVM for quantum-enhanced classification. Participants will implement QSVM, compare classical vs. quantum SVM, and analyze performance on real-world datasets using quantum computing frameworks.