CSE - Centurion University

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Module 1 18Hrs 7 TH SEMESTER PCCS4101 ARTIFICIAL INTELLIGENCE What is Artificial Intelligence? AI Technique, Level of the Model,Problem Spaces, and Search: Defining the Problem as a State Space Search, Production Systems, Problem Characteristics, Production System Characteristics, Issues in the Design of Search Programs.Heuristic Search Techniques: Generate-and-Test, Hill Climbing, Best-first Search, Problem Reduction, Constraint Satisfaction, Means-ends Analysis,Knowledge Representation: Representations and Mappings, Approaches to Knowledge Representation, Using Predicate Logic: Representing Simple Facts in Logic, Representing Instance and ISA Relationships, Computable Functions and Predicates, Resolution, Natural Deduction.Using Rules: Procedural Versus Declarative Knowledge, Logic Programming, Forward Versus Backward Reasoning, Matching, Control Knowledge.Symbolic Reasoning Under Uncertainty: Introduction to Nonmonotonic Reasoning, Logics for Nonmonotonic Reasoning, Implementation Issues, Augmenting a Problem-solver, Depth-first Search, Breadth-first Search.Weak and Strong Slot-and-Filler Structures: Semantic Nets, Frames, Conceptual DependencyScripts, CYC. Module 2 16Hrs Game Playing: The Minimax Search Procedure, Adding Alpha-beta Cutoffs, Iterative Deepening.Planning: The Blocks World, Components of a Planning System, Goal Stack Planning, Nonlinear Planning Using Constraint Posting, Hierarchical PlanningOther Planning Techniques.Understanding: What is Understanding, What Makes Understanding Hard?, Understanding as Constraint Satisfaction.Natural Language Processing: Introduction, Syntactic Processing, Semantic Analysis, Discourse and Pragmatic Processing, Statistical Natural Language Processing, Spell Checking. Module 3 16Hrs Learning: Rote Learning, Learning by Taking Advice, Learning in Problem-solving, Learning from Examples: Induction, Explanation-based Learning, Discovery, Analogy, Formal Learning Theory, Neural Net Learning and Genetic Learning. Expert Systems: Representing and Using Domain Knowledge, Expert System Shells, Explanation, Knowledge Acquisition. Text Book: 1. Elaine Rich, Kevin Knight, &Shivashankar B Nair, Artificial Intelligence, McGraw Hill, 3rd ed.,2009 References: 1) Introduction to Artificial Intelligence & Expert Systems, Dan W Patterson, PHI.,2010 2) S Kaushik, Artificial Intelligence, Cengage Learning, 1st ed.2011 64
MODULE-I (14 Hrs) PCCS4102 ADVANCED JAVA PROGRAMMING Introduction to JDBC:JDBC Drivers & Architecture. Database Programming using JDBC. Studying Javax.sql.* package , Accessing a Database . Java Beans: Introduction to Java Beans, Java Beans API Introduction to J2EE, J2EE Overview, Why J2EE? J2EE Architecture, J2EE APIs, J2EE Containers MODULE-II:(16 Hrs) Web Servers and Servlets: Tomcat web server, Web Application Basics, Architecture and challenges of Web Application. Introduction to Servlets: Lifecycle of a Servlet, The Servlet API, The javax.servlet Package, Initializing a Servlet, Reading Servlet parameters, Reading Initialization parameters. Developing and Deploying Servlets: Exploring Deployment Descriptor (web.xml). The javax.servlet HTTP package, Handling Http Request & Responses, Session Tracking & Management, Dealing with cookies.Filtering Request and Response, ProgrammingFilter, FilterMapping, Servlet Listeners MODULE-III:(16 Hrs) Java Server Pages: Basic JSP Architecture, Life Cycle of JSP,JSP Tags and Expressions, Role of JSP in MVC-2,JSP with Database, JSP Implicit Objects, TagLibraries, JSP Expression Language (EL),Using Custom Tag,JSPCapabilities:,ExceptionHandling,SessionManagement,Directives,JSP with Java Bean Framework: Introduction to the web MVC framework/Struts/Spring etc. Reference Books 1. Ed Roman, “Mastering Enterprise Java Beans”, John Wiley & Sons Inc., 1999. (UNIT III and UNIT V) 2. Web reference: http://java.sun.com. 3. J2EE The Complete Reference 4. Server Programming , Black Book 65
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COURSE STRUCTURE AND SYLLABI FOR B.
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THIRD SEMESTER BSMA2201 MATHEMATICS
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