The inner loop has linear growth till i, which is in $\Theta(i)$, How ever i grows exponentially to n, The trick here is to observe that
$$\sum_{i = 0}^{n}2^i = 2^{i+1}$$
However, using a number greater than 2, (4 in our example), we get a number way smaller than $4^{(i+1)}$, namely $(4^{(i+1)}-1)/3$, in our case however, we are summing up till the sum is n, which means we are summing $\Theta(k = \log(N))$ steps and in each step we have linear growth to i, which is (using the trick) in $\Theta(4^{\log(n)+1}) = \Theta(n)$
Mathematically speaking:
$$6*4^k = n^{5/2}$$
$$\log(6) + \log(4^k) = \log(n^{5/2})$$
$$\log(4^k) = \log(n^{5/2}) - \log(6)$$
$$ k = \frac{5/2\log(n) - \log(6)}{\log(4)} \in \Theta(\log(n))$$
And in everystep we are having a linear growth of j till i, which is in
$$\sum_{k=0}^{log(n)}4^k = (4^{log(n)+1}-1)/3 \in \Theta(n)$$.