Past experience has shown that students get a lot more out of the course, if they understand Matlab well and have already already quite a bit of experience. The following may help to get you started or improve your Matlab skills.
The best way to learn a programming language is to use it. So in preparation to the course, try the following.
Write a program (without using any Matlab modules) that
(i) simulates data for a least-squares regression problem with multiple explanatory variables,
(ii) does the regression and calculates standard errors,
(iii) creates a figure that plots what the 1st regressand explains, the 1st & 2nd, the 1st, 2nd, & 3rd, etc.
Write a program (again without using any Matlab modules) that
(i) simulates data for a VAR,
(ii) estimates the VAR (write the program such that you can easily adjust the number of lags), and
(iii) calculates the impulse response functions if you use Cholesky decomposition (or just the IRFs associated with the reduced-form shocks)
It is important that you are familiar with the basics of DSGE models. There are many ways to do this, but one reference would be dynamic optimization or equilibrium models . In addition, the Dynare user guide available here. Finally, Wouter has a great collection of slides and teaching notes on topics related to the course here.
It will be very helpful if you are familiar with perturbation techniques (Dynare). Info can be found at slides on Dynare , official Dynare user guide. In addition, knowledge of model with heterogeneous agents will be helpful. Useful articles are
Aiyagari, S.R., 1994, Uninsured idiosyncratic risk and aggregate saving, Quarterly Journal of Economics 109, 659-684.
Krusell, P. and T. Smith, 1998, Income and wealth heterogeneity in the macroeconomy , Journal of Political Economy 106, 867-896.