Artificial Intelligence (AI) for NTA NET Computer Science & Applications
- Approaches to AI : Turing Test and Rational Agent Approaches; State Space Representation of Problems, Heuristic Search Techniques, Game Playing, Min-Max Search, Alpha Beta Cut-off Procedures.
- Knowledge Representation : Logic, Semantic Networks, Frames, Rules, Scripts, Conceptual Dependency and Ontologies; Expert Systems, Handling Uncertainty in Knowledge.
- Planning : Components of a Planning System, Linear and Non-Linear Planning; Goal Stack Planning, Hierarchical Planning, STRIPS, Partial Order Planning.
- Natural Language Processing : Grammar and Language; Parsing Techniques, Semantic Analysis and Prgamatics.
- Multi Agent Systems : Agents and Objects; Agents and Expert Systems; Generic Structure of Multiagent System, Semantic Web, Agent Communication, Knowledge Sharing using Ontologies, Agent Development Tools.
- Fuzzy Sets : Notion of Fuzziness, Membership Functions, Fuzzification and Defuzzification; Operations on Fuzzy Sets, Fuzzy Functions and Linguistic Variables; Fuzzy Relations, Fuzzy Rules and Fuzzy Inference; Fuzzy Control System and Fuzzy Rule Based Systems.
- Genetic Algorithms (GA) : Encoding Strategies, Genetic Operators, Fitness Functions and GA Cycle; Problem Solving using GA.
- Artificial Neural Networks (ANN) : Supervised, Unsupervised and Reinforcement Learning; Single Perceptron, Multi-Layer Perceptron, Self-Organizing Maps, Hopfield Network
90 Days form the date of registration.
Minimum System Requirements
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- Lectures 0
- Quizzes 0
- Duration 50 hours
- Skill level All levels
- Language English
- Students 2
- Assessments Yes