Quantum simulations can give insights into quantum many-body systems' equilibrium properties and dynamics. Nowadays, a high level of control provides the means to implement different paradigmatic models in the laboratory. However, identifying the structure and quantifying the parameters of the implemented Hamiltonian is challenging. Here, Hamiltonian learning offers a new way of verification. After introducing Hamiltonian learning in general, we will discuss its extension for effective field theory Hamiltonians. Finally, we will discuss the connection to recent experiments with tunnel-coupled condensates.