Week 19 Quiz

Machine Learning and AI Fundamentals

Student Information

Name:

Email:

Quiz Questions

1. What is machine learning in simple terms?

A) Programming every possible situation a robot might encounter B) Teaching a robot to get better at tasks by showing it lots of examples C) Making robots that can only follow pre-written instructions D) Building robots that never make mistakes

2. What is training data used for in machine learning?

A) To make the robot run faster B) To provide examples so the robot can learn patterns C) To charge the robot's battery D) To connect the robot to the internet

3. What is a decision tree in robotics?

A) A physical tree that robots climb B) A flowchart that asks yes/no questions to reach a decision C) A type of sensor that detects trees D) A way to organize robot parts

4. In a scoring system for robot decisions, what should the robot do?

A) Always choose the first option B) Choose the action with the highest score C) Choose the action with the lowest score D) Choose a random action

5. What is a feedback loop in robot learning?

A) A circular path the robot follows B) When the robot checks if its actions worked well and uses that to improve C) A type of sensor connection D) A way to charge the robot

6. What is the main difference between supervised and unsupervised learning?

A) Supervised learning uses a teacher, unsupervised doesn't B) Supervised learning has correct answers provided, unsupervised finds patterns on its own C) Supervised learning is faster than unsupervised D) There is no difference between them

7. Why is it useful for a robot to remember past experiences?

A) To use more memory and slow down B) To make better decisions based on what worked before C) To confuse the robot with too much information D) Memory is not useful for robots

8. What does "adaptive learning" mean for a robot?

A) The robot never changes its behavior B) The robot gets better at tasks over time through experience C) The robot only works in one specific environment D) The robot becomes more expensive over time

9. Describe how a robot could use machine learning to get better at avoiding obstacles. Give a specific example. (Short Answer)

10. Give an example of machine learning that you use in your daily life and explain how you think it works. (Short Answer)

← Back to Lesson 📚 Semester Overview Next: Week 20 →