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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
What is the purpose of Big O notation?
💡 Hint: Think about the relationship between input size and algorithm performance.
Question 2
Easy
What is an example of a greedy algorithm?
💡 Hint: Consider a problem where you want to minimize the number of coins.
Practice 4 more questions and get performance evaluation
Interactive Quizzes
Engage in quick quizzes to reinforce what you've learned and check your comprehension.
Question 1
What does Big O notation measure?
- Memory usage
- Efficiency of algorithms
- Algorithm correctness
💡 Hint: Think about what aspect of algorithm performance you're analyzing.
Question 2
True or False: Greedy algorithms always guarantee optimal solutions.
- True
- False
💡 Hint: Consider scenarios where choosing locally optimal results fails.
Solve 1 more question and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
You are given a list of tasks with deadlines and profits. Describe how you would apply a greedy algorithm to maximize profit while respecting deadlines.
💡 Hint: Arrange and prioritize based on profit and timing.
Question 2
In the context of the Fibonacci sequence, illustrate how dynamic programming optimizes performance compared to a naive recursive approach.
💡 Hint: Visualize overlapping calculations in the naive method.
Challenge and get performance evaluation