Lecture 9: Bonus Episode - Portfolio Optimization with Grover Adaptive Search

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Intro
- Welcome to this course!
- pre-course-survey
Week 1
- Lecture 1: Optimization problem classes
- Module 1: Optimization problem classes
- Lecture 2: From QUBO to Ising Hamiltonian
- Module 2: From QUBO to Ising Hamiltonian
- Lecture 3: Variational Quantum Eigensolver
- Lecture 3: Bonus Episode - Maxcut with Qiskit
- Module 3: Variational Quantum Eigensolver
- Lecture 4: The Adiabatic Theorem and Adiabatic Annealing
- Module 4: The Adiabatic Theorem and Adiabatic Annealing
- Lecture 5: From Adiabatic Annealing to QAOA
- Module 5: From Adiabatic Annealing to QAOA
- Material Week 1
Week 2
- Lecture 6: Extensions of QAOA - part 1
- Lecture 6: Extensions of QAOA - part 2
- Module 6: Extensions of QAOA
- Lecture 7: Executing QAOA on Superconducting Qubits
- Module 7: QAOA on Superconducting Qubits
- Lecture 8: Advanced Variational Algorithms
- Module 8: Advanced Variational Optimization
- Lecture 9: Optimization with Grover Search
- Lecture 9: Bonus Episode - Portfolio Optimization with Grover Adaptive Search
- Module 9: Optimization with Grover Search
- Lecture 10: Possible Applications
- Module 10: Possible Applications
- Lecture 11: Challenges and Outlook
- Module 11: Challenges & Outlook
- Material Week 2
Final exam
- Final Exam
I like, I wish
- I like, I wish - what is that?
- post-course survey