UGC NET Computer Science and Applications Exam Pattern And Syllabus

Ugc Net

 The UGC NET Computer Science and Applications Exam is a national-level eligibility test conducted by the National Testing Agency on behalf of the University Grants Commission. This examination is organized to determine the eligibility of candidates for the posts of Assistant Professor and Junior Research Fellowship (JRF) in Computer Science and Applications across universities and colleges in India. The exam evaluates candidates’ knowledge of programming languages, data structures, algorithms, operating systems, database management systems, computer networks, software engineering, artificial intelligence, and other core computer science subjects.

It is conducted in Computer Based Test (CBT) mode and consists of two papers with objective-type multiple-choice questions. Thousands of candidates appear for this exam every year to build a career in teaching, research, and the IT sector. Qualifying the UGC NET Computer Science and Applications Exam provides excellent academic and professional opportunities in higher education and research fields across the country. 

UGC NET Computer Science and Applications: Overview Table 

ParticularsDetails
Organization NameUniversity Grants Commission (UGC)
Exam Conducting Body NameNational Testing Agency (NTA)
Exam NameUniversity Grants Commission-National Eligibility Test (UGC-NET) June 2026
Post Name / EligibilityJunior Research Fellowship (JRF), Assistant Professor, and Ph.D. Admission
Subject Name & CodeComputer Science and Applications (Code: 87)
Selection ProcessSingle Stage Computer Based Test (CBT)

UGC NET Computer Science and Applications: Exam Pattern 

ParticularsDetails
Total Questions150 Questions (Part I: 50 MCQs, Part II: 100 MCQs)
Total Marks300 Marks (Part I: 100 Marks, Part II: 200 Marks)
Exam Duration180 minutes (03 hours) without any break between Paper 1 & Paper 2
DurationThe total duration of the exam is 03 hours (180 minutes).
No BreaksThere is no break between Part I and Part II; the exam runs continuously.
Compulsory QuestionsAll 150 questions are compulsory.
Marks per QuestionEach correct response carries 02 (two) marks.
Negative MarkingThere is no negative marking for incorrect responses.
Unattempted QuestionsNo marks will be given for questions left unanswered, unattempted, or marked for review.

UGC NET: Paper 1 Exam Pattern

UnitSubject AreaNumber of Questions (Approx.)Total Marks
Unit 1Teaching Aptitude510
Unit 2Research Aptitude510
Unit 3Comprehension510
Unit 4Communication510
Unit 5Mathematical Reasoning and Aptitude510
Unit 6Logical Reasoning510
Unit 7Data Interpretation510
Unit 8Information and Communication Technology (ICT)510
Unit 9People, Development and Environment510
Unit 10Higher Education System510
TotalOverall Paper 150 Questions100 Marks

UGC NET Computer Science and Applications Paper 2 

UnitCore TopicsExpected QuestionsMarks Weightage
Unit 1: Discrete Structures and OptimizationMathematical Logic, Sets & Relations, Graph Theory, LPP12 – 1524 – 30
Unit 2: Computer System ArchitectureDigital Logic, Data Representation, Register Transfer, Memory Hierarchy7 – 914 – 18
Unit 3: Programming Languages and Computer GraphicsC/C++, OOPs Concepts, Web Programming, 2D/3D Transformations7 – 914 – 18
Unit 4: Database Management SystemsER-Model, Relational Model, SQL Queries, Normalization, Data Mining9 – 1118 – 22
Unit 5: System Software and Operating SystemCPU Scheduling, Deadlocks, Memory Management, Linux OS Basics10 – 1220 – 24
Unit 6: Software EngineeringSDLC Models, Software Design, Testing Techniques, Software Metrics8 – 1016 – 20
Unit 7: Data Structures and AlgorithmsArrays, Stacks, Trees, Graphs, Sorting, Algorithm Complexity, Greedy Methods9 – 1118 – 22
Unit 8: Theory of Computation and CompilersFinite Automata, Regular Expressions, Context-Free Grammars, Turing Machines9 – 1118 – 22
Unit 9: Data Communication and Computer NetworksOSI & TCP/IP Models, Routing Algorithms, Cryptography, Network Security9 – 1118 – 22
Unit 10: Artificial Intelligence (AI)Search Techniques, Knowledge Representation, Fuzzy Logic, Neural Networks9 – 1118 – 22
Total (Paper 2)100 Questions200 Marks

UGC NET Computer Science and Applications: Syllabus 

Part I: General Paper (Common for All Subjects)

UnitSubject AreaDetailed Topics Covered
Unit ITeaching Aptitude
  • Teaching: Concept and objectives
  • Levels of teaching
    • Memory level
    • Understanding level
    • Reflective level
  • Learner characteristics
    • Adolescent learners
    • Adult learners
  • Factors affecting teaching
  • Methods of teaching in higher learning institutions
    • Teacher-centered methods
    • Learner-centered methods
    • Offline teaching
    • Online teaching
  • Teaching support systems
    • Traditional methods
    • Modern methods
    • ICT-based systems
  • Evaluation systems
  • Choice Based Credit System (CBCS)
Unit IIResearch Aptitude
  • Meaning and characteristics of research
  • Types of research
  • Positivism and post-positivistic approach
  • Research methods
    • Experimental research
    • Descriptive research
    • Historical research
    • Qualitative research
    • Quantitative research
  • Steps of research
  • Thesis and article writing
    • Format
    • Referencing styles
  • Application of ICT in research
  • Research ethics
Unit IIIComprehension
  • Reading comprehension passage
  • Understanding and analysis-based questions
  • Interpretation of ideas and arguments
Unit IVCommunication
  • Meaning, types, and characteristics of communication
  • Effective communication
    • Verbal communication
    • Non-verbal communication
    • Intercultural communication
    • Group communication
    • Classroom communication
  • Barriers to effective communication
  • Mass media and society
Unit VMathematical Reasoning and Aptitude
  • Types of reasoning
  • Number series
  • Letter series
  • Codes and relationships
  • Mathematical aptitude topics
    • Fractions
    • Time and distance
    • Ratio and proportion
    • Percentage
    • Profit and loss
    • Interest
    • Discounting
    • Averages
Unit VILogical Reasoning
  • Structure of arguments
    • Premises
    • Deductive reasoning
    • Inductive reasoning
  • Evaluating and distinguishing arguments
  • Venn diagrams
  • Analogies
  • Indian Logic
    • Pramanas (Means of knowledge)
      • Pratyaksha
      • Anumana
      • Upamana
      • Shabda
      • Arthapatti
      • Anupalabdhi
  • Structure and kinds of Anumana (Inference)
  • Vyapti
  • Hetvabhasas
Unit VIIData Interpretation
  • Sources of data
  • Acquisition and classification of data
  • Quantitative data
  • Qualitative data
  • Graphical representation of data
    • Bar chart
    • Histogram
    • Pie chart
    • Table chart
    • Line chart
  • Mapping of data
  • Data interpretation
  • Data and governance
Unit VIIIInformation and Communication Technology (ICT)
  • ICT abbreviations and terminology
  • Basics of Internet and Intranet
  • E-mail
  • Audio conferencing
  • Video conferencing
  • Digital initiatives in higher education
  • ICT and governance
Unit IXPeople, Development and Environment
  • Development and environment
    • Millennium Development Goals (MDGs)
    • Sustainable Development Goals (SDGs)
  • Human and environment interaction
  • Anthropogenic activities
  • Environmental issues
    • Air pollution
    • Water pollution
    • Soil pollution
    • Noise pollution
    • Climate change
  • Impact of pollutants on human health
  • Natural resources
  • Energy resources
  • Natural hazards and disasters
  • Environmental Protection Act, 1986
  • National Action Plan on Climate Change (NAPCC)
  • International agreements
    • Kyoto Protocol
    • Paris Agreement
    • International Solar Alliance (ISA)
Unit XHigher Education System
  • Institutions of higher learning and education in ancient India
  • Evolution of higher learning and research in post-independence India
  • Learning programs
    • Oriental learning
    • Conventional learning
    • Non-conventional learning
  • Professional education
  • Technical education
  • Skill-based education
  • Value education
  • Environmental education
  • Policies, governance, and administration of higher education

UGC NET Computer Science and Applications Paper 2 Syllabus

UnitDetailed Syllabus Topics
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 Microoperations: Register Transfer Language, Bus and Memory Transfers, Arithmetic, Logic and Shift Microoperations.
  • 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 Argumaents, 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; Time-line 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, Russels’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 Network, 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 and IPv6: 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: Malwares, 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 Prgamatics.
  • 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.

Preparation Tips

  • Balance Paper 1 and Paper 2: Many Computer Science candidates focus solely on their technical domain (Part II) and neglect the teaching/research aptitude section (Part I). Remember, Part I constitutes a third of your total score. Dedicate at least 1-1.5 hours daily to practicing reading comprehension, data interpretation, and logical reasoning to secure easy marks.
  • Master the High-Weightage Core Subjects: In Computer Science, units like Data Structures and Algorithms, Database Management Systems, Theory of Computation, and Computer Networks consistently carry high weightage. Ensure your foundational concepts in these areas are crystal clear.
  • Practice with Mock Tests and CBT Guidelines: The exam is conducted exclusively in Computer Based Test (CBT) mode. Familiarize yourself with the interface to avoid wasting time on exam day. The NTA provides CBT guidelines and Mock Tests on their website (https://www.nta.ac.in/Quiz), which you should practice extensively. Get comfortable with the “Mark for Review” feature and the on-screen timer.
  • Leverage the “No Negative Marking” Rule: Since there is no penalty for wrong answers, never leave a question un-attempted. If you are running out of time, employ intelligent guessing or elimination strategies for the remaining questions.
  • Create Short Revision Notes: Computer Science encompasses a massive amount of theory, formulas, and syntax. Create cheat sheets for quick revision—especially for things like CPU scheduling formulas, Normalization rules, IP addressing classes, and Big-O complexities.
  • Review Previous Years’ Question Papers (PYQs): Analyzing the last 5-7 years of UGC NET CS papers is the most effective way to understand the trend and difficulty level of questions. It helps you identify recurring topics (like SQL queries, subnetting problems, and Turing machine recognizability) so you can prioritize your study time efficiently.

Some Important Links

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UGC NET Management Exam pattern and syllabusClick Here

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