Quesion bank

Module 1 - Question Bank

No	Questions
	Define Artificial Intelligence.
	How does AI work? List the advantages and disadvantages of AI.
	What are the different types of AI? Briefly explain any three.
	Explain different types of AI based on capabilities.
	Explain different types of AI based on functionalities.
	What is Machine Learning? With a neat diagram, illustrate the relation between AI, ML, DL and NLP.
	Explain how AI is related to Machine Learning.
	Compare traditional programming and machine learning programming.
	Explain Artificial Intelligence, Machine Learning and Deep Learning.
	Briefly explain the working of AI.
	What are the different components of Intelligence?
	Briefly explain different components of Agent and Environment.
	List the different types of Agent and briefly explain any three.
	List the different types of Environment and briefly explain any four.
	What is Uninformed search? Briefly explain Depth First Search (DFS).
	Briefly explain Depth Limited Search (DLS).
	Briefly explain Breadth First Search (BFS).
	Briefly explain Uniform Cost Search (UCS).
	Briefly explain Iterative Deepening Depth First Search (IDDFS).
	Briefly explain Bi-Directional Search.
	What is informed search? Briefly explain Heuristic Search.
	Briefly explain Best-First Search Algorithm (Greedy Search Algorithm).

Module 2 - Question Bank

No	Questions
	Write a short note on Large Language Model.
	Write a short note on Generative AI. With a neat diagram illustrate the relation between AI, LLM and Generative AI.
	What is Prompt Engineering? Why is it required? With example explain Bad Prompt and Good Prompt.
	What is Instruction Prompt Technique?
	List the different types of Prompts and explain them.
	With different steps explain how prompt engineering works?
	Briefly explain the role of prompt engineering in communication.
	What are the advantages of prompt engineering?
	Write a short note on the future of Large Language Model communication.
	Why is Prompt Engineering important? Write a note on the future of Prompt Engineering.
	With examples briefly explain what is Zero, One, and Few Shot Prompting.
	Write a note on Self Consistency Prompt and explain its key features.
	What are the key principles for fostering innovation in prompt engineering?
	Write 5 prompts for unlocking imagination and innovation explaining the prompt and its usefulness.
	What are the different types of writing prompts?
	Briefly explain igniting the writing process with prompts in effective prompt writing.

Module 3 - Question Bank

No	Questions
	Write Basic neural network model explaining the function of each layer.
	“ML Model is a combination of Task, Performance and Experience”, Explain with suitable an example.
	Is Labelled data supervised or unsupervised machine learning? Extend your answer explaining different types of machine learning.
	Outline K-Means Algorithm with merits and demerits.
	A company decides to carry out its business operations on a rented space. If the cost of the rental space is Rs 20000 plus Rs 500 per employee per day, then compute monthly rental for space given that the company is open 5 days a week. Show a linear equation for this scenario with explanation.
	Explain the four steps to create Decision Trees with suitable example for each step.
	Explain how Linear Regression, Logistic Regression, and Polynomial Regression can be applied to analyze and predict real-world data in Artificial Intelligence and Machine Learning.
	Define conditional probability and the Bayes rule with examples.
	Differentiate between the following: (i) Supervised and Unsupervised Machine Learning (ii) Forward and Backward Propagation (iii) Classification and Regression
	Explain how Machine Learning, Deep Learning, and Natural Language Processing techniques can be applied to solve real-world problems in Artificial Intelligence.
	Summarize the features of: (i) Reinforcement Learning (ii) Support Vector Machines (SVM)
	How does computer vision work with deep learning? Explain the tasks involved in computer vision.
	Briefly explain Support Vector Machine.
	Briefly explain AI as a Process of Reverse-Engineering Human Traits.
	Briefly explain different techniques in AI.
	Explain how the machine learning works.
	Explain the working of deep learning.
	Explain the Forward propagation and Backward propagation.
	Briefly explain how computer vision works.
	What are the difference between GPU and CPU?
	Briefly explain the working of Reinforcement Learning.
	Explain the working of KNN algorithm.

Module 4 - Question Bank

No	Questions
	List and explain any four Trusted AI principles.
	What is expert system? Explain three components of expert system.
	Relate the role of ethics in AI.
	Explain the working of an expert system taking any example.
	AI could be programmed to do something beneficial, but the method used to achieve its goal can be highly destructive, Explain why?
	What is Artificial Intelligence of Things (AIoT). Explain how Does AIoT Work?
	What is Neuromorphic Computing? Explain its architecture, features resembling the human brain, and how it contributes toward achieving Artificial General Intelligence (AGI).
	Describe the concept of AI as a Service (AIaaS). Outline two advantages and two challenges of using AIaaS in organizations.
	List and explain the risks associated with Artificial Intelligence and their societal impact.
	Explain AI Bias. Describe the sources of bias, real-world examples, and methods to mitigate bias in AI systems.
	Explain the major components of an Expert System with their functions.
	Differentiate between the following: (i) AI Programs and Robots (ii) Human-controlled and Fully-autonomous Bots
	Where does AI unlock IoT?
	List the applications of AIoT.
	Describe the steps in development of Expert System.
	List the applications of Expert System.

Module 5 - Question Bank

No	Questions
	List different types of Robots. Identify and explain industry application of Robots.
	What is No-Code AI? Explain why No-Code AI Must be Used?
	Explain the role of AI in early disease prevention.
	What is the role of AI in Medical Diagnosis? Identify three applications of AI in Medical Diagnosis.
	Relate the role of AI in Biology and Environmental Sciences.
	What is Low Code AI? Compare Traditional tools with Low Code AI.
	Identify the application of AI in education, specifically in personalized learning experiences. Explain with examples, how adaptive learning platforms and intelligent tutoring systems use AI to tailor educational content and provide customized support for students.
	Explain how AI contributes to environmental science by breaking down its role in climate modelling, air and water quality monitoring, waste management, and resource conservation. Describe the specific data, techniques, and decision-making processes involved in each area.
	Identify the role of AI in scientific experimentation by examining how it supports different disciplines and breaking down the specific experimental activities such as data collection, pattern identification, simulation, and hypothesis testing that AI enhances.
	Compare AI-enabled precision farming with traditional farming. Outline the key differences in data usage, cost, and productivity.
	Explain AI in Healthcare.
	Explain AI in Finance.
	Explain AI in Retail.
	Explain AI in Agriculture.
	Explain AI in Education.
	Explain AI in Transportation.