Exponential time algorithms take time proportional to Θ(a^n) for some constant a, indicating that their running time grows rapidly with input size. In contrast, polynomial time algorithms operate within Θ(P(n)), where P is a polynomial function of the input size. A common example of polynomial time is illustrated through nested loops, where the time complexity can be expressed as n^2. Understanding these concepts is crucial for analyzing algorithm efficiency. The discussion emphasizes the importance of recognizing the differences between exponential and polynomial time complexities in algorithm design.