AI Presentation (For 2023 Batch)

📢 IMPORTANT INSTRUCTIONS – READ CAREFULLY

Presentation Topic Allotment Process:

  • You need to select ONE topic out of the 45 topics listed below.
  • Topics will be allotted on a FIRST COME FIRST SERVE basis.
  • Once a topic is selected by a student, it will not be available for others.
  • Check the Presentation Topic Allotment Form (Responses) Google Sheet (link shared in AI WhatsApp group) to see which topics are already taken.
  • Submit the Presentation Topic Allotment Form at the earliest (DEADLINE: 26-10-2025) to secure your preferred presentation topic.

PRESENTATION TOPIC ALLOTMENT FORM

  • Check Presentation Guidelines after the Presentation Topic List.

Presentation Topic List:

Topic 01: What is Artificial Intelligence? – Definition and Scope
Topic 02: History and Evolution of AI
Topic 03: Applications of AI in Daily Life
Topic 04: Intelligent Agents – Types and Examples
Topic 05: PEAS Description of Agents
Topic 06: Problem-Solving Agents
Topic 07: Problem Formulation in AI
Topic 08: Uninformed Search – Breadth First Search
Topic 09: Uninformed Search – Depth First Search
Topic 10: Informed Search – Greedy Best-First Search

Topic 11: A* Search Algorithm with Example
Topic 12: Heuristic Functions and Their Use
Topic 13: Semantic Networks for Knowledge Representation
Topic 14: Frames in AI – Structure and Examples
Topic 15: Production Rules in AI
Topic 16: Forward Chaining Method
Topic 17: Need for Probabilistic Reasoning
Topic 18: Bayesian Networks – Introduction
Topic 19: Dempster-Shafer Theory Overview
Topic 20: Certainty Factors in AI
Topic 21: Introduction to Machine Learning
Topic 22: Supervised Learning – Concept and Examples
Topic 23: Unsupervised Learning – Concept and Examples
Topic 24: Backward Chaining Method in AI
Topic 25: Difference Between Uninformed and Informed Search
Topic 26: Properties of Search Algorithms – Completeness and Optimality
Topic 27: Comparison of BFS and DFS
Topic 28: Inference in First Order Logic
Topic 29: Reinforcement Learning – Basic Concepts
Topic 30: What is an Expert System? – Components and Architecture

Topic 31: Knowledge Base in Expert Systems
Topic 32: Inference Engine – Working and Functions
Topic 33: Rule-Based Expert Systems
Topic 34: Expert System Development Life Cycle
Topic 35: Advantages and Limitations of Expert Systems
Topic 36: Knowledge Acquisition in Expert Systems
Topic 37: Expert Systems vs Traditional Programs
Topic 38: Propositional Logic – Syntax and Semantics
Topic 39: Logical Connectives – AND, OR, NOT, Implication
Topic 40: Predicate Logic – Introduction and Need
Topic 41: Quantifiers in Logic – Universal and Existential
Topic 42: Introduction to Prolog Programming Language
Topic 43: Facts, Rules and Queries in Prolog
Topic 44: Resolution in Logic
Topic 45: Logic Programming vs Procedural Programming

Presentation Guidelines:

  • Duration: 5-10 minutes
  • Format: Video presentation (MP4 format only)
  • Content: Cover the topic clearly with examples and explanations

Important Deadlines:

  • Topic Selection: By 26-10-2025
  • Final Video Submission: By 02-11-2025

Video File Naming Convention:

  • File name format: RollNo_TopicNo_video.mp4
  • Example: 23251A17XX_TopicXX_video.mp4

Submission Link

AI PRESENTATION SUBMISSION

CONSENT FORM (for uploading best presentation videos in CHANDRAS EDU Youtube channel) [Optional]