Quantum Formalism (QF) Academy

Quantum Formalism Academy presents a comprehensive course bridging advanced mathematical theory of Lie Groups with practical applications in machine learning and quantum computing.

Topics Highlight:

• Introduction to Lie Groups: Basic notions, fundamental examples, Lie subgroups, and homogeneous spaces.
• Lie Algebras & Exponential Map: Matrix Lie algebras, the exponential map, and the Baker–Campbell–Hausdorff formula.
• Representation Theory: Group representations, SU(2) theory, and the Peter–Weyl theorem.
• Applications in Quantum Mechanics & Quantum Computing: Symmetry in quantum systems, quantum gates, and Hamiltonian evolution.
• Symmetry in Machine Learning: Group equivariant convolutional neural networks and geometric deep learning.
• Equivariant Neural Networks: Designing architectures that respect continuous symmetries and integrating physics-informed models.
• Case Studies & Future Directions: Recent research, interdisciplinary applications, and open problems.

What This Course Offers:

• Self-paced video lectures with premium production quality.
• Interactive quizzes to reinforce your understanding.
• In-depth coverage of both theoretical and practical aspects of Lie theory.
• Interactive Jupyter notebooks with stunning visualizations.
• Personalized office hour sessions for individualized learning.
• Project-based certification upon successful completion.

Who Should Take It?

• Researchers and engineers in Machine Learning, Quantum Computing, and related fields.
• Students and professionals motivated to learn advanced mathematics for emerging technologies.