We consider a parameter estimation problem to determine the drift coefficient for a large class of parabolic Stochastic PDEs driven by additive or multiplicative noise. In the first part of the talk, we derive several different classes of estimators based on the first N Fourier modes of a sample path observed continuously on a finite time interval. Second part of the talk will be devoted to Burgers equation driven either by additive or multiplicative noise. We study consistency and asymptotic normality of these estimators as number of Fourier coefficients increases, and we present some numerical simulation results.