You've learned probability DP. You can now:
Compute probabilities using weighted sums over transitions.
Handle expected values by weighting outcomes.
Recognize when to count paths vs compute probabilities.
Apply tricks like scaling and early termination for large inputs. The observation: probability DP is just regular DP with weighted transitions. Instead of min or max, you sum with weights. That's it. For training, solve the problems here's problemset. Then move on to DP Optimizations where you'll learn to make DP faster.