Sample Module 2
2M
1. Define Artificial Intelligence and give two real-world applications.
Artificial Intelligence (AI) is a branch of computer science that focuses on creating
machines or software capable of performing tasks that normally require human
intelligence—such as learning, reasoning, problem-solving, perception, and language
understanding
1. Healthcare – Disease Diagnosis
AI systems analyze medical images (like X-rays, MRIs, CT scans) and patient data to detect
diseases such as cancer, diabetes, and heart conditions.
• AI helps doctors identify abnormalities faster and more accurately.
• It can also predict disease risks and recommend personalized treatments.
2. Finance – Fraud Detection
Banks and financial institutions use AI to detect unusual transactions and prevent fraud.
• Machine learning models analyze spending patterns.
• When something suspicious occurs, the system alerts the bank or blocks the
transaction automatically.
2. What is the difference between BFS and DFS
Feature BFS (Breadth-First Search) DFS (Depth-First Search)
Traversal Order Level by level Deep along one branch, then
backtrack
Data Structure Used Queue (FIFO) Stack (LIFO) or recursion
Approach Explores neighbours first Explores deeper nodes first
Shortest Path in Yes No
Unweighted Graph
Memory Usage Higher for wide graphs Higher for deep graphs
Applications Shortest path, level-order Cycle detection, topological
traversal, finding connected sorting, puzzle solving, deep
components exploration
, 3. What is a Constraint Satisfaction Problem (CSP)? Give one example.
A Constraint Satisfaction Problem (CSP) is a type of problem defined by:
1. Variables – a set of unknowns that need to be assigned values
2. Domains – each variable has a domain of possible values
3. Constraints – restrictions that specify allowable combinations of values for the
variables
The goal is to assign a value to every variable such that all constraints are satisfied.
• Example: Map Coloring
• Variables: Regions on a map (e.g., A, B, C)
• Domain: {Red, Green, Blue}
• Constraints: Adjacent regions cannot share the same color
4. What is supervised learning? Give one example.
Supervised learning is a type of machine learning where a model is trained using labeled
data, meaning each input comes with a correct output. The model learns to map inputs to
outputs and can then predict the output for new, unseen data.
Example: Predicting house prices using a dataset that includes house features (size,
location) along with their actual prices.
5. Mention two applications of AI in the healthcare sector.
1. Refer Q1
2. Healthcare – Robotic Surgery
AI-powered robotic systems assist surgeons in performing complex procedures with higher
precision and minimal invasiveness.
• They enhance accuracy and reduce the risk of human error during surgery.
• Patients benefit from smaller incisions, faster recovery, and reduced hospital stays.
6. State the purpose of a heuristic function in informed searc
A heuristic function in informed search provides an estimate of the cost or distance from
the current state to the goal. Its purpose is to guide the search process by prioritizing paths
that appear more promising, helping the algorithm avoid exploring irrelevant or less
optimal routes. This makes the search faster, more efficient, and more goal-directed
compared to uninformed methods.
2M
1. Define Artificial Intelligence and give two real-world applications.
Artificial Intelligence (AI) is a branch of computer science that focuses on creating
machines or software capable of performing tasks that normally require human
intelligence—such as learning, reasoning, problem-solving, perception, and language
understanding
1. Healthcare – Disease Diagnosis
AI systems analyze medical images (like X-rays, MRIs, CT scans) and patient data to detect
diseases such as cancer, diabetes, and heart conditions.
• AI helps doctors identify abnormalities faster and more accurately.
• It can also predict disease risks and recommend personalized treatments.
2. Finance – Fraud Detection
Banks and financial institutions use AI to detect unusual transactions and prevent fraud.
• Machine learning models analyze spending patterns.
• When something suspicious occurs, the system alerts the bank or blocks the
transaction automatically.
2. What is the difference between BFS and DFS
Feature BFS (Breadth-First Search) DFS (Depth-First Search)
Traversal Order Level by level Deep along one branch, then
backtrack
Data Structure Used Queue (FIFO) Stack (LIFO) or recursion
Approach Explores neighbours first Explores deeper nodes first
Shortest Path in Yes No
Unweighted Graph
Memory Usage Higher for wide graphs Higher for deep graphs
Applications Shortest path, level-order Cycle detection, topological
traversal, finding connected sorting, puzzle solving, deep
components exploration
, 3. What is a Constraint Satisfaction Problem (CSP)? Give one example.
A Constraint Satisfaction Problem (CSP) is a type of problem defined by:
1. Variables – a set of unknowns that need to be assigned values
2. Domains – each variable has a domain of possible values
3. Constraints – restrictions that specify allowable combinations of values for the
variables
The goal is to assign a value to every variable such that all constraints are satisfied.
• Example: Map Coloring
• Variables: Regions on a map (e.g., A, B, C)
• Domain: {Red, Green, Blue}
• Constraints: Adjacent regions cannot share the same color
4. What is supervised learning? Give one example.
Supervised learning is a type of machine learning where a model is trained using labeled
data, meaning each input comes with a correct output. The model learns to map inputs to
outputs and can then predict the output for new, unseen data.
Example: Predicting house prices using a dataset that includes house features (size,
location) along with their actual prices.
5. Mention two applications of AI in the healthcare sector.
1. Refer Q1
2. Healthcare – Robotic Surgery
AI-powered robotic systems assist surgeons in performing complex procedures with higher
precision and minimal invasiveness.
• They enhance accuracy and reduce the risk of human error during surgery.
• Patients benefit from smaller incisions, faster recovery, and reduced hospital stays.
6. State the purpose of a heuristic function in informed searc
A heuristic function in informed search provides an estimate of the cost or distance from
the current state to the goal. Its purpose is to guide the search process by prioritizing paths
that appear more promising, helping the algorithm avoid exploring irrelevant or less
optimal routes. This makes the search faster, more efficient, and more goal-directed
compared to uninformed methods.
