Simulating Stochastic Differential equations

I am just learning about Stochastic differential equations if I have a SDE of dX(t) = -μ*X(t)*dt + σ*W(t) X0=x0>0 where W(t) is the Wiener process and I am trying to simulate it using

X(n+1)=X(n)−μX(n)∆t+σ*sqrt(∆t)*ηn, where ∆t = T /N :and ηn ∼ N (0, 1) normal distribution

So far I am here but not sure how to proceed and if I am simulating correctly and how the initial condition X0=x0>0 comes into it

dt_large = T / N;

 t = linspace ( 0, T, N + 1 );
  x = zeros ( 1, N + 1 );

  x(1) = x0;
  for j = 1 : n
    dw = sqrt ( dt_large ) * randn ( 1, r );
    x(j+1) = x(j) - x(j)* mu*dt_large  + sigma * sum ( dw(1:r) );
  end