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CE-803 (A) RGPV B.Tech

Artificial Intelligence (AI)

Previous year papers and the official syllabus are free to read, no account needed.

Previous Year Papers

6 papers, latest Jun 2025

Free
See all 6 papers

Syllabus, notes and important questions for CE-803 (A)

Syllabus units

Topics as the official RGPV syllabus lists them.

Unit 1 Introduction to Artificial Intelligence 10 topics
  • Main components and characteristics of AI (Feature Engineering, ANN, Deep Learning)
  • Applications of AI
  • Advantages and disadvantages of AI
  • Goals of AI
  • Comparison of programming a system with AI and without AI
  • Challenges in AI
  • Programming languages preferably used in AI
  • Techniques/Algorithms used in AI
  • AI software platforms
  • Future of AI
Unit 1 notes
Unit 2 Various types of production systems and search techniques 5 topics
  • Types of production systems
  • Characteristics of production systems
  • Study and comparison of breadth‑first search and depth‑first search
  • Other search techniques: hill climbing, best‑first search
  • A* algorithm, AO* algorithms, and various control strategies
Unit 2 notes
Unit 3 Knowledge Representation and Probabilistic Reasoning 10 topics
  • Problems in representing knowledge
  • Knowledge representation using propositional and predicate logic
  • Comparison of propositional and predicate logic
  • Resolution, refutation, deduction, theorem proving, inferencing
  • Monotonic and non‑monotonic reasoning
  • Probabilistic reasoning
  • Bayes' theorem
  • Semantic networks, scripts, schemas, frames, conceptual dependency
  • Fuzzy logic
  • Forward and backward reasoning
Unit 3 notes
Unit 4 Game playing techniques 5 topics
  • Minimax procedure
  • Alpha‑beta cut‑offs
  • Planning
  • Study of the block world problem in robotics
  • Introduction to natural language processing
Unit 4 notes
Unit 5 Introduction to learning, ANN 11 topics
  • Various techniques used in learning
  • Introduction to artificial neural networks
  • Common‑sense reasoning
  • Convolutional Neural Network (CNN)
  • Feedforward Neural Network (FNN)
  • Recurrent Neural Network (RNN)
  • Multilayer perceptron
  • Architecture / three layers in artificial neural networks
  • Implementation of ANN
  • Applications of ANN in images, signals and language
  • Examples of expert systems
Unit 5 notes
Read the full syllabus

Exam insights

Counted from 13 past CE-803 (A) papers.

Marks asked per paper, by unit

  • Unit 1 Introduction to Artificial Intelligence 27 marks
  • Unit 2 Various types of production systems and search techniques 11 marks
  • Unit 3 Knowledge Representation and Probabilistic Reasoning 14 marks
  • Unit 4 Game playing techniques 10 marks
  • Unit 5 Introduction to learning, ANN 11 marks

Average marks of the questions from each unit in one paper. You answer only some of them, so the total is more than the paper’s maximum.

Asked again and again

  1. Explain the Minimax procedure and its application in game playing.

    Asked 4 times: 2025, 2024, 2024, 2023

  2. Discuss the A* search algorithm and its importance in heuristic search strategies.

    Asked 4 times: 2025, 2024, 2024, 2023

  3. Explain the fundamentals of AI, including its goals and characteristics.

    Asked 4 times: 2025, 2024, 2023, 2022

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