Let $T$ be an endomorphism of a finite dimensional vector space $V$. Suppose that $(v_1,\ldots v_n)$ is an ordered basis of $V$. And let $[T]$ be the matrix of $T$ with respect to this basis.
Is there a way to compute the matrix of $\Lambda^k(T)$ with respect to the obvious basis given $[T]$? The 'obvious' basis is the $\binom{n}{k}$ $k$-wedge tuples from $\{v_1,\ldots,v_n\}$ with increasing indices.
There have been many questions on here about how to compute the characteristic polynomial and the coefficients $(-1)^k\text{tr}(\Lambda^k(T))$, but I haven't seen any interest in the matrix of $\Lambda^k(T)$ itself. I suspect it can be built from the minors of $[T]$, but I have no idea how to proceed.
Let $T(v_i) = \sum_j a_{ji} \cdot v_j$, so that $(a_{ji})$ is the matrix of $T$ w.r.t. to $(v_1,\dotsc,v_n)$. The wedges $v_{i_1} \wedge \dotsc \wedge v_{i_k}$ with $i_1<\dotsc<i_k$ form a basis of $\Lambda^k(V)$. We have:
$$\Lambda^k(T)(v_{i_1} \wedge \dotsc \wedge v_{i_k}) = T(v_{i_1}) \wedge \dotsc \wedge T(v_{i_k})=\sum_{j_1,\dotsc,j_k} a_{j_1,i_1} \dotsc a_{j_k,i_j} \cdot v_{j_1} \wedge \dotsc \wedge v_{j_k}$$
If the indices $j_\ell$ are not pairwise distinct, the summand is zero. If not, we may choose a permutation to order the indices. The result is: $$\sum_{j_1<\dotsc<j_k} \sum_{\pi \in \Sigma_k} \mathrm{sgn}(\sigma) a_{j_{\pi(1)},i_1} \dotsc a_{j_{\pi(k)},i_j} \cdot v_{j_1} \wedge \dotsc \wedge v_{j_k}$$ Thus, the entry of the matrix of $\Lambda^k(T)$ in the row $(j_1<\dotsc<j_k)$ and the column $(i_1<\dotsc<i_k)$ is $$ \sum_{\pi \in \Sigma_k} \mathrm{sgn}(\sigma) a_{j_{\pi(1)},i_1} \dotsc a_{j_{\pi(k)},i_j} .$$ This is nothing else than the determinant of the submatrix of $(a_{ji})$ corresponding to the rows $(j_1<\dotsc<j_k)$ and the columns $(i_1<\dotsc<i_k)$.
Conclusion: The entries of the matrix of $\Lambda^k(T)$ are the $k$-minors of the matrix of $T$.