Masters of Computer Applications:Artificial Intelligence and ApplicationsThapar University
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Frequent Asked Questions
Recognised Bachelors degree of minimum 3 years duration in any discipline with Mathematics at least at 10+2 school level and has also qualified in the Entrance Test to be conducted by the University.OR Recognised Bachelor's Degree of minimum 3 years duration in any discipline with Mathematics as one of the subjects and has also qualified in the Entrance Test to be conducted by the University.
Discrete Mathematical Structures
Elements of Electronics Engineering
Problem Solving and Programming in C
Computer Organization and Architecture
Fundamental of Microprocessors and Interfacing
Object Oriented Programming using c++ and Java
System Analysis and Design
Statistics and Combinatorics
Data Base Management System
Design and Analysis of Algorithms
Advanced Java and Network Programming
Computer Graphics and Multimedia
ERP and Tools
Information and Network Security
Software Project Management
Net Framework and C# Programming
System Development Project
Artificial Intelligence and Applications
Introduction to expert systems, various subsets of expert systems as AI, ANNs, Fuzzy Set theory, the differences & comparisons of various theories
Introduction and Overview of AI: Historical foundations, development of logic, turning test, problem spaces, problem characteristics, characteristics of intelligent algorithm, structures and strategies for state space search.
Problem Solving Techniques: Heuristic search, A* algorithm, AO* algorithm, generate and test, hill climbing. Problem reduction, Constraint propagation
Knowledge representation: predicate logic, resolution in predicate logic, question answering, theorem proving.
Semantic networks, Frames and scripts, conceptual graphs. Game playing: Minimax and alpha beta procedures
Natural language Processing: role of knowledge in language understanding, the natural language problem, syntax, specification and parsing using context free grammar.
Fundamentals of Neural Networks, Supervised and Unsupervised Learning, learning tasks & learning strategies, single layer & multiplayer Perceptions, Back propagation, Hopfield nets, Adaptive resonance theory , Recent trends and Future Directions
Fuzzy set Theory: Introduction, Basic definitions & terminology, Fuzzy union, intersection, complement. Fuzzy rules, relations & principles, Fuzzy inference systems
Laboratory Work: Programming in Prolog to implement Arithmetic operators, List Processing, Defining Human Relationships, Cut Operations, Files, Trees, Graphs and Natural Language Processing. Implementation of Heuristic and Minimax Searches using C/C++/Java.