Contents: 1. Introduction; 2. Introduction to linear algebra; 3. Fourier analysis; 4. Signal spaces; 5. Shift-invariant spaces; 6. Subspace priors; 7. Smoothness priors; 8. Nonlinear sampling; 9. Resampling; 10. Unions of subspaces; 11. Compressed sensing; 12. Sampling over finite unions; 13. Sampling over shift-invariant unions; 14. Multiband sampling; 15. Finite rate of innovation sampling; Appendix A. Finite linear algebra; Appendix B. Stochastic signals.