UGC NET Computer Science and Applications Syllabus PDF 2023 (Latest) download free [English/Hindi]

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UGC NET Computer Science and Applications Syllabus PDF 2023 (Latest) download

UGC NET Computer Science and Applications

UGC NET Syllabus 2023: Considering the fact that the syllabus plays a prominent role in boosting up the preparation, we have provided the detailed UGC NET syllabus and exam pattern for 2023Paper-I & Paper-II. The students should prepare accordingly with the updated UGC NET Syllabus 2023 for the subjects they have registered for. In this article, we have provided the complete detail about UGC NET Syllabus & Exam Pattern for your reference. 

UGC NET Syllabus 2023

National Testing Agency had revised the UGC NET Syllabus and in this article we have covered the revised syllabus only. UGC NET exam is conducted in two papers (Paper-I and Paper-II) consisting of multiple-choice questions (MCQs) and all questions are compulsory. Candidates need to complete both papers in a single duration of three hours. To score good marks in the exam, read the detailed syllabus and start your preparation now.

UGC NET Exam Pattern 2023

UGC NET 2023 Examination will be conducted in online mode (Computer Based Test). Before looking into the detailed syllabus of the NTA UGC NET Syllabus 2023, the student must be familiar with the updated UGC NET Exam Pattern 2023, which has been discussed below.

PaperPattern of PaperNumber of QuestionsMarksTotal
Duration
Paper-IThe questions will be generic in nature, intending to assess the teaching/research aptitude of the candidate. 5010003 hours (180 minutes)
Paper-IIThis is based on the subject selected by the candidate and will assess domain knowledge.100200
Total150300

Important Points:
1. For each correct answer the candidate will get 2 marks in both Paper 1 & 2.
2. There is no negative marking for incorrect answers in UGC NET 2023 exam.
3. No marks will be given for questions Unanswered/Marked for Review.
4. All questions are mandatory.
5. If a question is found to be incorrect/ambiguous during the key challenge, the candidate who have attempted the question and chosen one of the correct answers would be given the credit. If there is any dropped question(s), marks will be awarded to all the candidates.

UGC NET Syllabus 2023

The first step of preparing for UGC NET is to be familiar with the UGC NET syllabus as this helps the aspirants to strategise their preparations in a well-defined manner. UGC NET 2023 exam will consist of 2 papers (Paper 1 & Paper 2), the UGC NET Paper 1 will be a common paper for all candidates while Paper 2 will be based on the subject selected by the candidate. Let’s have a look at the detailed UGC NET Syllabus for UGC NET 2023 Exam

UGC NET Syllabus for Paper 1

The UGC NET syllabus for Paper 1 consists of the subjects that will be helpful in analysing the candidate’s teaching and research ability, cognitive abilities, general awareness about teaching and learning processes in the higher education system. The detailed syllabus and UGC NET Paper-1 Syllabus PDF file link have been provided below:

Unit-I: Teaching Aptitude Syllabus

Teaching: Concept, Objectives, Levels of teaching (Memory, Understanding and Reflective), Characteristics and basic requirements.

Learner’s characteristics: Characteristics of adolescent and adult learners (Academic, Social, Emotional and Cognitive), Individual differences.

Factors affecting teaching related to Teacher, Learner, Support material, Instructional facilities, Learning environment and Institution.

Methods of teaching in Institutions of higher learning: Teacher centred vs. Learner-centred methods; offline vs. Online methods (Swayam, Swayamprabha, MOOCs etc.).

Teaching Support System: Traditional, Modern and ICT based.

Evaluation Systems: Elements and Types of evaluation, Evaluation in Choice Based Credit System in Higher education, Computer-based testing, Innovations in evaluation systems.

Unit-II: Research Aptitude Syllabus

Research: Meaning, Types, and Characteristics, Positivism and Postpositivistic approach to research.

Methods of Research: Experimental, Descriptive, Historical, Qualitative and Quantitative Methods, Steps of Research.

Thesis and Article writing: Format and styles of referencing.

Application of ICT in research.

Research ethics.

Unit-III Comprehension Syllabus

A passage of text is given. Questions are asked from the passage to be answered.

Unit-IV: Communication

Communication: Meaning, types and characteristics of communication.

Effective communication: Verbal and Non-verbal, Inter-Cultural and group communications, Classroom communication.

Barriers to effective communication.

Mass-Media and Society.

Unit-V: Mathematical Reasoning and Aptitude Syllabus

Types of reasoning.

Number series, Letter series, Codes and Relationships.

Mathematical Aptitude (Fraction, Time & Distance, Ratio, Proportion and Percentage, Profit and Loss, Interest and Discounting, Averages etc.).

Unit-VI: Logical Reasoning Syllabus

Understanding the structure of arguments: argument forms, the structure of categorical propositions, Mood and Figure, Formal and Informal fallacies, Uses of language, Connotations and denotations of terms, Classical square of opposition.

Evaluating and distinguishing deductive and inductive reasoning.

Analogies.

Venn diagram: Simple and multiple uses for establishing the validity of arguments.

Indian Logic: Means of knowledge.

Pramanas: Pratyaksha (Perception), Anumana (Inference), Upamana (Comparison), Shabda (Verbal testimony), Arthapatti (Implication) and Anupalabddhi (Non-apprehension).

Structure and kinds of Anumana (inference), Vyapti (invariable relation), Hetvabhasas (fallacies of inference).

Unit-VII: Data Interpretation Syllabus

Sources, acquisition and classification of Data.

Quantitative and Qualitative Data.

Graphical representation (Bar-chart, Histograms, Pie-chart, Table-chart and Line-chart) and mapping of Data.

Data Interpretation.

Data and Governance.

Unit-VIII: Information and Communication Technology (ICT) Syllabus

ICT: General abbreviations and terminology.

Basics of the Internet, Intranet, E-mail, Audio and Video-conferencing.

Digital initiatives in higher education.

ICT and Governance.

Unit-IX: People, Development and Environment Syllabus

Development and environment: Millennium development and Sustainable development goals.

Human and environment interaction: Anthropogenic activities and their impacts on the environment.

Environmental issues: Local, Regional and Global; Air pollution, Water pollution, Soil pollution, Noise pollution, Waste (solid, liquid, biomedical, hazardous, electronic), Climate change and its Socio-Economic and Political dimensions.

Impacts of pollutants on human health.

Natural and energy resources: Solar, Wind, Soil, Hydro, Geothermal, Biomass, Nuclear and Forests.

Natural hazards and disasters: Mitigation strategies.

Environmental Protection Act (1986), National Action Plan on Climate Change, International agreements/efforts -Montreal Protocol, Rio Summit, Convention on Biodiversity, Kyoto Protocol, Paris Agreement, International Solar Alliance.

Unit-X: Higher Education System Syllabus

Institutions of higher learning and education in ancient India.

Evolution of higher learning and research in Post Independence India.

Oriental, Conventional and Non-conventional learning programmes in India.

Professional, Technical and Skill-Based education.

Value education and environmental education.

Policies, Governance, and Administration.

NOTE: (i) Five questions each carrying 2 marks are to be set from each Module.
(ii) Whenever graphical/pictorial question(s) are set for sighted candidates, a passage followed by an equal number of questions and weightage be set for visually impaired candidates.

UGC NET Computer Science and Applications Syllabus 2023

UGC NET Syllabus for Computer Science and Applications Paper I tests the reasoning ability, reading comprehension, divergent thinking, and general awareness of the candidate.

UGC NET Computer Science and Applications Paper I syllabus will have 50 questions worth 100 marks. Paper I syllabus has 10 units, and precisely 5 questions will be asked from each unit.

Here you can check the latest UGC NET Computer Science and Applications Syllabus Paper-II 2023

Unit – 1: Discrete Structures and Optimization

  • Mathematical Logic: Propositional and Predicate Logic, Propositional Equivalences, Normal Forms, Predicates and Quantifiers, Nested Quantifiers, Rules of Inference.
  • Sets and Relations: Set Operations, Representation and Properties of Relations, Equivalence Relations, Partially Ordering.
  • Counting, Mathematical Induction and Discrete Probability: Basics of Counting, Pigeonhole Principle, Permutations and Combinations, Inclusion-Exclusion Principle, Mathematical Induction, Probability, Bayes’ Theorem.
  • Group Theory: Groups, Subgroups, Semi Groups, Product and Quotients of Algebraic Structures, Isomorphism, Homomorphism, Automorphism, Rings, Integral Domains, Fields, Applications of Group Theory.
  • Graph Theory: Simple Graph, Multigraph, Weighted Graph, Paths and Circuits, Shortest Paths in Weighted Graphs, Eulerian Paths and Circuits, Hamiltonian Paths and Circuits, Planner graph, Graph Coloring, Bipartite Graphs, Trees and Rooted Trees, Prefix Codes, Tree Traversals, Spanning Trees and Cut-Sets.
  • Boolean Algebra: Boolean Functions and its Representation, Simplifications of Boolean Functions.
  • Optimization: Linear Programming – Mathematical Model, Graphical Solution, Simplex and Dual Simplex Method, Sensitive Analysis; Integer Programming, Transportation and Assignment Models, PERT-CPM: Diagram Representation, Critical Path Calculations, Resource Levelling, Cost Consideration in Project Scheduling.

Unit – 2: Computer System Architecture

  • Digital Logic Circuits and Components: Digital Computers, Logic Gates, Boolean Algebra, Map Simplifications, Combinational Circuits, Flip-Flops, Sequential Circuits, Integrated Circuits, Decoders, Multiplexers, Registers and Counters, Memory Unit.
  • Data Representation: Data Types, Number Systems and Conversion Complements, Fixed Point Representation, Floating-Point Representation, Error Detection Codes, Computer Arithmetic – Addition, Subtraction, Multiplication and Division Algorithms.
  • Register Transfer and Micro operations: Register Transfer Language, Bus and Memory Transfers, Arithmetic, Logic and Shift Micro operations.
  • Basic Computer Organization and Design: Stored Program Organization and Instruction Codes, Computer Registers, Computer Instructions, Timing and Control, Instruction Cycle, Memory-Reference Instructions, Input-Output, Interrupt.
  • Programming the Basic Computer: Machine Language, Assembly Language, Assembler, Program Loops, Subroutines, Input-Output Programming.
  • Microprogrammed Control: Control Memory, Address Sequencing, Design of Control Unit.
  • Central Processing Unit: General Register Organization, Stack Organization, Instruction Formats, Addressing Modes, RISC Computer, CISC Computer.
  • Pipeline and Vector Processing: Parallel Processing, Pipelining, Arithmetic Pipeline, Instruction Pipeline, Vector Processing Array Processors.
  • Input-Output Organization: Peripheral Devices, Input-Output Interface, Asynchronous Data Transfer, Modes of Transfer, Priority Interrupt, DMA, Serial Communication.
  • Memory Hierarchy: Main Memory, Auxillary Memory, Associative Memory, Cache Memory, Virtual Memory, Memory Management Hardware.
  • Multiprocessors: Characteristics of Multiprocessors, Interconnection Structures, Interprocessor Arbitration, Interprocessor Communication and Synchronization, Cache Coherence, Multicore Processors.

Unit – 3: Programming Languages and Computer Graphics

  • Language Design and Translation Issues: Programming Language Concepts, Paradigms and Models, Programming Environments, Virtual Computers and Binding Times, Programming Language Syntax, Stages in Translation, Formal Transition Models.
  • Elementary Data Types: Properties of Types and Objects; Scalar and Composite Data Types.
  • Programming in C: Tokens, Identifiers, Data Types, Sequence Control, Subprogram Control, Arrays, Structures, Union, String, Pointers, Functions, File Handling, Command-Line Arguments, Preprocessors.
  • Object-Oriented Programming: Class, Object, Instantiation, Inheritance, Encapsulation, Abstract Class, Polymorphism.
  • Programming in C++: Tokens, Identifiers, Variables and Constants; Data types, Operators, Control statements, Functions Parameter Passing, Virtual Functions, Class and Objects; Constructors and Destructors; Overloading, Inheritance, Templates, Exception and Event Handling; Streams and Files; Multifile Programs.
  • Web Programming: HTML, DHTML, XML, Scripting, Java, Servlets, Applets.
  • Computer Graphics: Video-Display Devices, Raster-Scan and Random-Scan Systems; Graphics Monitors, Input Devices, Points and Lines; Line Drawing Algorithms, Mid-Point Circle and Ellipse Algorithms; Scan Line Polygon Fill Algorithm, Boundary-Fill and Flood-Fill.
  • 2-D Geometrical Transforms and Viewing: Translation, Scaling, Rotation, Reflection and Shear Transformations; Matrix Representations and Homogeneous Coordinates; Composite Transforms, Transformations Between Coordinate Systems, Viewing Pipeline, Viewing Coordinate Reference Frame, Window to View-Port Coordinate Transformation, Viewing Functions, Line and Polygon Clipping Algorithms.
  • 3-D Object Representation, Geometric Transformations and Viewing: Polygon Surfaces, Quadric Surfaces, Spline Representation, Bezier and B-Spline Curves; Bezier and B-Spline Surfaces; Illumination Models, Polygon Rendering Methods, Viewing Pipeline and Coordinates; General Projection Transforms and Cipping.

Unit – 4: Database Management Systems

  • Database system concepts and Architecture: Data Models, Schemas, and Instances; Three-Schema Architecture and Data Independence; Database Languages and Interfaces; Centralized and Client/Server Architectures for DBMS.
  • Data Modeling: Entity-Relationship Diagram, Relational Model – Constraints, Languages, Design, and Programming, Relational Database Schemas, Update Operations and Dealing with Constraint Violations; Relational Algebra and Relational Calculus; Codd Rules.
  • SQL: Data Definition and Data Types; Constraints, Queries, Insert, Delete, and Update Statements; Views, Stored Procedures and Functions; Database Triggers, SQL Injection.
  • Normalization for Relational Databases: Functional Dependencies and Normalization; Algorithms for Query Processing and Optimization; Transaction Processing, Concurrency Control Techniques, Database Recovery Techniques, Object and Object-Relational Databases; Database Security and Authorization.
  • Enhanced Data Models: Temporal Database Concepts, Multimedia Databases, Deductive Databases, XML and Internet Databases; Mobile Databases, Geographic Information Systems, Genome Data Management, Distributed Databases and Client-Server Architectures.
  • Data Warehousing and Data Mining: Data Modeling for Data Warehouses, Concept Hierarchy, OLAP and OLTP; Association Rules, Classification, Clustering, Regression,
    Support Vector Machine, K-Nearest Neighbour, Hidden Markov Model, Summarization, Dependency Modeling, Link Analysis, Sequencing Analysis, Social Network Analysis.
  • Big Data Systems: Big Data Characteristics, Types of Big Data, Big Data Architecture, Introduction to Map-Reduce and Hadoop; Distributed File System, HDFS.
  • NoSQL: NoSQL and Query Optimization; Different NOSQL Products, Querying and Managing NOSQL; Indexing and Ordering Data Sets; NoSQL in Cloud.

Unit – 5: System Software and Operating System

  • System Software: Machine, Assembly and High-Level Languages; Compilers and Interpreters; Loading, Linking and Relocation; Macros, Debuggers.
  • Basics of Operating Systems: Operating System Structure, Operations and Services; System Calls, Operating-System Design and Implementation; System Boot.
  • Process Management: Process Scheduling and Operations; Interprocess Communication, Communication in Client-Server Systems, Process Synchronization, Critical-Section Problem, Peterson’s Solution, Semaphores, Synchronization.
  • Threads: Multicore Programming, Multithreading Models, Thread Libraries, Implicit Threading, Threading Issues.
  • CPU Scheduling: Scheduling Criteria and Algorithms; Thread Scheduling, Multiple-Processor Scheduling, Real-Time CPU Scheduling.
  • Deadlocks: Deadlock Characterization, Methods for Handling Deadlocks, Deadlock Prevention, Avoidance and Detection; Recovery from Deadlock.
  • Memory Management: Contiguous Memory Allocation, Swapping, Paging, Segmentation, Demand Paging, Page Replacement, Allocation of Frames, Thrashing, Memory-Mapped Files.
  • Storage Management: Mass-Storage Structure, Disk Structure, Scheduling and Management, RAID Structure.
  • File and Input/Output Systems: Access Methods, Directory and Disk Structure; File-System Mounting, File Sharing, File-System Structure and Implementation; Directory Implementation, Allocation Methods, Free-Space Management, Efficiency and Performance; Recovery, I/O Hardware, Application I/O Interface, Kernel I/O Subsystem, Transforming I/O Requests to Hardware Operations.
  • Security: Protection, Access Matrix, Access Control, Revocation of Access Rights, Program Threats, System and Network Threats; Cryptography as a Security Tool, User Authentication, Implementing Security Defenses.
  • Virtual Machines: Types of Virtual Machines and Implementations; Virtualization.
  • Linux Operating Systems: Design Principles, Kernel Modules, Process Management, Scheduling, Memory Management, File Systems, Input and Output; Interprocess Communication, Network Structure.
  • Windows Operating Systems: Design Principles, System Components, Terminal Services and Fast User Switching; File System, Networking.
  • Distributed Systems: Types of Network-based Operating Systems, Network Structure, Communication Structure and Protocols; Robustness, Design Issues, Distributed File Systems.

Unit – 6: Software Engineering

  • Software Process Models: Software Process, Generic Process Model – Framework Activity, Task Set and Process Patterns; Process Lifecycle, Prescriptive Process Models, Project Management, Component-Based Development, Aspect-Oriented Software Development, Formal Methods, Agile Process Models – Extreme Programming (XP), Adaptive Software Development, Scrum, Dynamic System Development Model, Feature Driven Development, Crystal, Web Engineering.
  • Software Requirements: Functional and Non-Functional Requirements; Eliciting Requirements, Developing Use Cases, Requirement Analysis and Modelling; Requirements Review, Software Requirement and Specification (SRS) Document.
  • Software Design: Abstraction, Architecture, Patterns, Separation of Concerns, Modularity, Information Hiding, Functional Independence, Cohesion and Coupling; Object-Oriented Design, Data Design, Architectural Design, User Interface Design, Component Level Design.
  • Software Quality: McCall’s Quality Factors, ISO 9126 Quality Factors, Quality Control, Quality Assurance, Risk Management, Risk Mitigation, Monitoring and Management (RMMM); Software Reliability.
  • Estimation and Scheduling of Software Projects: Software Sizing, LOC and FP based Estimations; Estimating Cost and Effort; Estimation Models, Constructive Cost Model (COCOMO), Project Scheduling and Staffing; Timeline Charts.
  • Software Testing: Verification and Validation; Error, Fault, Bug and Failure; Unit and Integration Testing; White-box and Black-box Testing; Basis Path Testing, Control Structure Testing, Deriving Test Cases, Alpha and Beta Testing; Regression Testing, Performance Testing, Stress Testing.
  • Software Configuration Management: Change Control and Version Control; Software Reuse, Software Re-engineering, Reverse Engineering.

Unit – 7: Data Structures and Algorithms

  • Data Structures: Arrays and their Applications; Sparse Matrix, Stacks, Queues, Priority Queues, Linked Lists, Trees, Forest, Binary Tree, Threaded Binary Tree, Binary Search Tree, AVL Tree, B Tree, B+ Tree, B* Tree, Data Structure for Sets, Graphs, Sorting and Searching Algorithms; Hashing.
  • Performance Analysis of Algorithms and Recurrences: Time and Space Complexities; Asymptotic Notation, Recurrence Relations.
  • Design Techniques: Divide and Conquer; Dynamic Programming, Greedy Algorithms, Backtracking, Branch and Bound.
  • Lower Bound Theory: Comparison Trees, Lower Bounds through Reductions.
  • Graph Algorithms: Breadth-First Search, Depth-First Search, Shortest Paths, Maximum Flow, Minimum Spanning Trees.
  • Complexity Theory: P and NP Class Problems; NP-completeness and Reducibility.
  • Selected Topics: Number Theoretic Algorithms, Polynomial Arithmetic, Fast Fourier Transform, String Matching Algorithms.
  • Advanced Algorithms: Parallel Algorithms for Sorting, Searching and Merging, Approximation Algorithms, Randomized Algorithms.

Unit – 8: Theory of Computation and Compilers

  • Theory of Computation: Formal Language, Non-Computational Problems, Diagonal Argument, Russell’s Paradox.
  • Regular Language Models: Deterministic Finite Automaton (DFA), Non-Deterministic Finite Automaton (NDFA), Equivalence of DFA and NDFA, Regular Languages, Regular Grammars, Regular Expressions, Properties of Regular Language, Pumping Lemma, Non-Regular Languages, Lexical Analysis.
  • Context-Free Language: Pushdown Automaton (PDA), Non-Deterministic Pushdown Automaton (NPDA), Context-Free Grammar, Chomsky Normal Form, Greibach Normal Form, Ambiguity, Parse Tree Representation of Derivation Trees, Equivalence of PDA’s and Context-Free Grammars; Properties of Context-Free Language.
  • Turing Machines (TM): Standard Turing Machine and its Variations; Universal Turing Machines, Models of Computation and Church-Turing Thesis; Recursive and Recursively-Enumerable Languages; Context-Sensitive Languages, Unrestricted Grammars, Chomsky Hierarchy of Languages, Construction of TM for Simple Problems.
  • Unsolvable Problems and Computational Complexity: Unsolvable Problem, Halting Problem, Post Correspondence Problem, Unsolvable Problems for Context-Free Languages, Measuring and Classifying Complexity, Tractable and Intractable Problems.
  • Syntax Analysis: Associativity, Precedence, Grammar Transformations, Top-Down Parsing, Recursive Descent Predictive Parsing, LL(1) Parsing, Bottom-up Parsing, LR Parser, LALR(1) Parser.
  • Semantic Analysis: Attribute Grammar, Syntax Directed Definitions, Inherited and Synthesized Attributes; Dependency Graph, Evaluation Order, S-attributed and L-attributed Definitions; Type-Checking.
  • Run-Time System: Storage Organization, Activation Tree, Activation Record, Stack Allocation of Activation Records, Parameter Passing Mechanisms, Symbol Table.
  • Intermediate Code Generation: Intermediate Representations, Translation of Declarations, Assignments, Control Flow, Boolean Expressions and Procedure Calls.
  • Code Generation and Code Optimization: Control-flow, Data-flow Analysis, Local Optimization, Global Optimization, Loop Optimization, Peep-Hole Optimization, Instruction Scheduling.

Unit – 9: Data Communication and Computer Networks

  • Data Communication: Components of a Data Communication System, Simplex, Half-Duplex and Duplex Modes of Communication; Analog and Digital Signals; Noiseless and Noisy Channels; Bandwidth, Throughput and Latency; Digital and Analog Transmission; Data Encoding and Modulation Techniques; Broadband and Baseband Transmission; Multiplexing, Transmission Media, Transmission Errors, Error Handling Mechanisms.
  • Computer Networks: Network Topologies, Local Area Networks, Metropolitan Area Networks, Wide Area Networks, Wireless Networks, Internet.
  • Network Models: Layered Architecture, OSI Reference Model and its Protocols; TCP/IP Protocol Suite, Physical, Logical, Port and Specific Addresses; Switching Techniques.
  • Functions of OSI and TCP/IP Layers: Framing, Error Detection and Correction; Flow and Error Control; Sliding Window Protocol, HDLC, Multiple Access – CSMA/CD, CSMA/CA, Reservation, Polling, Token Passing, FDMA, CDMA, TDMA, Network Devices, Backbone Networks, Virtual LANs.
  • IPv4 Structure and Address Space; Classful and Classless Addressing; Datagram, Fragmentation and Checksum; IPv6 Packet Format, Mapping Logical to Physical Address (ARP), Direct and Indirect Network Layer Delivery; Routing Algorithms, TCP, UDP and SCTP Protocols; Flow Control, Error Control and Congestion Control in TCP and SCTP.
  • World Wide Web (WWW): Uniform Resource Locator (URL), Domain Name Service (DNS), Resolution – Mapping Names to Addresses and Addresses to Names; Electronic Mail Architecture, SMTP, POP and IMAP; TELNET and FTP.
  • Network Security: Malware, Cryptography and Steganography; Secret-Key Algorithms, Public-Key Algorithms, Digital Signature, Virtual Private Networks, Firewalls.
  • Mobile Technology: GSM and CDMA; Services and Architecture of GSM and Mobile Computing; Middleware and Gateway for Mobile Computing; Mobile IP and Mobile Communication Protocol; Communication Satellites, Wireless Networks and Topologies; Cellular Topology, Mobile Adhoc Networks, Wireless Transmission and Wireless LANs; Wireless Geolocation Systems, GPRS and SMS.
  • Cloud Computing and IoT: SaaS, PaaS, IaaS, Public and Private Cloud; Virtualization, Virtual Server, Cloud Storage, Database Storage, Resource Management, Service Level Agreement, Basics of IoT.

Unit – 10: Artificial Intelligence (AI)

  • Approaches to AI: Turing Test and Rational Agent Approaches; State Space Representation of Problems, Heuristic Search Techniques, Game Playing, Min-Max Search, Alpha Beta Cutoff 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 Pragmatics.
  • 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.

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