Practice Course Schedule - 1.6 | 1. Welcome to the NPTEL MOOC on Design and Analysis of Algorithms | Design & Analysis of Algorithms - Vol 1
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1.6 - Course Schedule

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Learning

Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

Define asymptotic complexity.

💡 Hint: Think about how algorithms perform on larger datasets.

Question 2

Easy

What is Big O notation used for?

💡 Hint: Consider how we measure algorithm efficiency.

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 primarily measure?

  • Memory consumption
  • Time complexity
  • Algorithm correctness

💡 Hint: Think about how we gauge efficiency in algorithms.

Question 2

True or False: Greedy algorithms always result in the optimal solution.

  • True
  • False

💡 Hint: Consider edge cases where greedy choices might lead to suboptimal results.

Solve and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

Propose a situation where a greedy algorithm might yield a suboptimal solution and discuss why that happens.

💡 Hint: Look into examples of change-making problems.

Question 2

Design a small algorithm that uses dynamic programming to optimize a problem. Provide the steps involved.

💡 Hint: Think about how overlapping sub-problems can be stored.

Challenge and get performance evaluation