All these results are called "spectral theorems". They depend on what hypotheses you adjoin to the problem other than just being self-adjoint.
The "nice" case is for compact self-adjoint operators. Here the statement of the spectral theorem is essentially the same as in the finite dimensional case: there is an orthonormal basis of the space made up of eigenvectors, and all eigenvalues are real. Everything here is the same except that the basis in question is a Schauder basis (i.e. basis representations are infinite sums rather than finite sums, so there is a limit process going on when we write a basis representation).
Probably the more important case for many physical applications (for example in quantum mechanics) is for bounded self-adjoint operators. Here the work is harder, and the resulting "diagonal basis" is not just a countable version of what we see in finite dimensions.
Instead we get a measure space $(X,\Sigma,\mu)$, a function $f \in L^\infty(X,\mu)$, and a unitary similarity transformation defined by $U : H \to L^2(X,\mu)$. This similarity transformation turns our given bounded self-adjoint operator into the multiplication operator $T : L^2(X,\mu) \to L^2(X,\mu)$ defined by $(T \varphi)(x) = f(x) \varphi(x)$.
Things are more complicated still in the unbounded case. I won't try to go there, but there are hypotheses that can be used in this case as well.