Prove that The beta distribution is a conjugate for the Bernoulli distribution ?

Proving that Beta is conjugate to Bernoulli: 3) Let y= Cy,. .. ., yn) be ind sample with y; GEo, 1} (i= 1 , - --n ) How to prove that Beta distriation is conjugate to Bernoulli distributions. (In the case that we assume a Bernoulli likelihood LEXI4) with success probability of and a Beta (a, B ) prior : TC (O ) = 4(2 -2) ( 1- 4) 13 - 2 B ( x, 13 ) the posterior ic (olx) follows a Beta (x+ z yi , Ban - SMS distribution. 6) using the first part, determine a Bayesian point estimator which is asymptotically unbiased . explain the solution