1.1 Calculate the total number of steps required by the algorithm, and express it as a function of n (fln)). 1.2 Determine the Time complexity of the algorithm using Big-O notation. O(n) the highest...

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Extracted text: 1.1 Calculate the total number of steps required by the algorithm, and express it as a function of n (fln)). 1.2 Determine the Time complexity of the algorithm using Big-O notation. O(n) the highest power of n


Extracted text: # 3x3 matrix X = [[12, 7, 3], [4, 5, 6], [7, 8, 9]] # 3x4 matrix Y = [[5, 8, 1, 2], [6, 7, 3, 0], [4, 5, 9, 1]] %3D # empty matrix to store the result Z = [[0, 0, 0, 0], [0, о, о, е], [0, е, в, е]] %3D def MatrixMultiplication(A,B,C): # iterating by row of A for i in range(len(A)): # iterating by columns by B for j in range(len(B[0])): # iterating by rows of B for k in range(len(B)): C[i][j] += A[i][k] * B[k][j] for r in C: print(r) # function call MatrixMultiplication(X,Y,z)