Masters of Computer Applications:Artificial Intelligence and Applications

Semester I

Discrete Mathematical Structures
Elements of Electronics Engineering
Problem Solving and Programming in C
Operating Systems
Computer Organization and Architecture


Semester II

Data Structures
Fundamental of Microprocessors and Interfacing
Object Oriented Programming using c++ and Java
System Analysis and Design
Statistics and Combinatorics


Semester III

Software Engineering
Data Base Management System
Design and Analysis of Algorithms
Operations Research
Computer Networks


Semester IV

Advanced Java and Network Programming
Computer Graphics and Multimedia
ERP and Tools
Minor Project


Semester V

Information and Network Security
Software Project Management
Net Framework and C# Programming


Semester VI

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.