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Subject Syllabus

ME-703 (B) - Artificial Intelligence Techniques

ME · Semester 7

Course Modules

Learn topic-wise with Hyper AI and revise using mapped PYQs.

Main components and characteristics of AI (Feature Engineering,ANN,Deep Learning),Applications of AIAdvantages and disadvantages of AIGoals of AIComparision of Programming of a System with AI and without AI,Challenges in AIProgramming languges preferably used in AI,Techniques/Algorithms used in AI,AI Software plaforms,Future of AI
systems,Characteristics of production systemsStudy and comparison of breadth first search and depth first search.Techniques, other Search Techniques like hill ClimbingBest first Search.A* algorithmAO* algorithms etc, and various types of control strategies.
knowledge, knowledge representation using propositional and predicate logic, comparison of propositional and predicate logicResolution, refutation, deduction, theorem proving, inferencing, monotonic and nonmonotonic reasoning.Probabilistic reasoningBaye's theorem, semantic networks, scripts, schemas, frames, conceptual dependency, fuzzy logic, forward and backward reasoning.
the block world problem in roboticsIntroduction to understanding and natural languages processing.
Artificial neural networks, common sense, reasoningConvolution Neural Network,Feedforward Neural NetworkRecurrent Neural NetworkMultilayer perceptronArchitecture / Three Layers in Artificial Neural NetworksImplementation of ANN, Applications of ANN in images,signals and languagesome example of expert systems.