BAYES Business School of London University offers a 16-hour course on Quantum Machine Learning with application in Finance. The course will provide a deep understanding of quantum computations and quantum machine learning methods. The methods will be set within the standard machine learning workflow and applied to a real financial data set. With Algorithms being tested on real quantum computers.
Students are expected to spend at least one hour of self-study per week to review and practice the techniques covered during each session. Projects that will be assigned to them will serve as their on-ground training, as they will be applying the techniques in real data environments.
Students who will be enrolled in this class will be introduced to concepts of quantum computations and key points to qubit notions. Part of the program will be on standard operating procedures for one or more qubits including quantum teleportation. Two machine learning methods will be focused on: the first will be the quantum vector machine and the second is the quantum neural network.
The following are the modules for the entire course:
- Topic 1: Introduction to quantum information technology and quantum computation
- Topic 2: Elementary quantum algorithms
- Topic 3: Programming on quantum computers
- Topic 4: Quantum and Classical Support Vector Machine
- Topic 5: Quantum Neural Networks
- Topic 6: More on quantum machine learning (in the ideal setting)
- Topic 7: Quantum Assisted Monte-Carlo Methods
- Topic 8: Quantum Assisted Monte-Carlo Methods
Students who are willing to enroll are advised to have the background and basic knowledge of Python (ability to run simple commands preferably using Jupyter Notebooks), and basic skills in Mathematics and Statistics. This course will be beneficial to both professionals and researchers working with machine learning techniques.
Read more about the online course here.
