Learn the fundamentals of neural quantum states in this comprehensive tutorial that explores how machine learning techniques can be applied to quantum many-body systems. Discover the theoretical foundations behind using neural networks as variational ansätze for quantum wavefunctions, understand the key algorithms for optimization and sampling, and explore practical applications in condensed matter physics and quantum chemistry. Master the mathematical framework connecting artificial neural networks to quantum state representation, examine different neural network architectures suitable for quantum problems, and gain hands-on insights into implementing these methods for solving complex quantum many-body problems.