Syllabus of B.tech. VII SEM CSE (RGPV)
Syllabus of B. Tech. VII Sem CSE (RGPV)
Syllabus of CS-701 Software Architectures
Source: (rgpv.ac.in)
UNIT-1 :
Overview of Software development methodology and software quality model,
different models of software development and their issues.
Introduction to software architecture,
evolution of software architecture,
software components and connectors,
common software architecture frameworks,
Architecture business cycle – architectural patterns – reference model.
UNIT-2 :
Software architecture models: structural models,
framework models, dynamic models,
process models.
Architectures styles: data flow architecture,
pipes and filters architecture,
call-and return architecture,
data-centered architecture,
layered architecture,
agent based architecture,
Micro-services architecture,
Reactive Architecture,
Representational state transfer architecture etc.
UNIT-3 :
Software architecture implementation technologies: Software Architecture Description Languages (ADLs),
Struts, Hibernate, Node JS, Angular JS, J2EE – JSP,
Servlets, EJBs;
middleware : JDBC, JNDI, JMS, RMI and CORBA etc.
Role of UML in software architecture.
UNIT-4 :
Software Architecture analysis and design : requirements for architecture
and the life-cycle view of architecture design and analysis methods,
architecture-based economic analysis: Cost Benefit Analysis Method (CBAM), Architecture Tradeoff Analysis Method (ATAM).
Active Reviews for Intermediate Design (ARID),
Attribute Driven Design method (ADD),
architecture reuse,
Domain –specific Software architecture.
UNIT-5 :
Software Architecture documentation : principles of sound documentation, refinement, context diagrams,
variability, software interfaces.
Documenting the behavior of software elements and software systems, documentation package using a seven-part template.
== END OF UNITS==
Syllabus of CS-702 (A) Computational Intelligence Networks (Departmental Elective)
Source: (rgpv.ac.in)
UNIT-1 :
Introduction to Computational Intelligence;
types of Computational Intelligence,
components of Computational Intelligence.
Concept of Learning/Training model.
Parametric Models, Nonparametric Models.
Multilayer Networks : Feed Forward network,
Feedback network.
UNIT-2 :
Fuzzy Systems : Fuzzy set theory: Fuzzy sets and operations,
Membership Functions,
Concept of Fuzzy relations and their composition,
Concept of Fuzzy Measures;
Fuzzy Logic : Fuzzy Rules, Inferencing;
Fuzzy Control - Selection of Membership Functions,
Fuzzyfication, Rule Based Design & Inferencing,
Defuzzyfication.
UNIT-3 :
Genetic Algorithms : Basic Genetics, Concepts,
Working Principle, Creation of Offsprings,
Encoding, Fitness Function, Selection Functions,
Genetic Operators-Reproduction,
Crossover, Mutation;
Genetic Modeling, Benefits.
UNIT-4 :
Rough Set Theory - Introduction,
Fundamental Concepts,
Set approximation,
Rough membership, Attributes,
Optimization.
Hidden Markov Models,
Decision tree model.
UNIT-5 :
Introduction to Swarm Intelligence,
Swarm Intelligence Techniques : Ant Colony Optimization,
Particle Swarm Optimization,
Bee Colony Optimization etc.
Applications of Computational Intelligence.
== END OF UNITS==
Syllabus of CS-702 (B) Deep & Reinforcement Learning (Departmental Elective)
Source: (rgpv.ac.in)
UNIT-1 :
History of Deep Learning,
McCulloch Pitts Neuron, Thresholding Logic,
Activation functions, Gradient Descent (GD),
Momentum Based GD, Nesterov Accelerated GD,
Stochastic GD, AdaGrad, RMSProp, Adam,
Eigenvalue Decomposition.
Recurrent Neural Networks,
Backpropagation through time (BPTT),
Vanishing and Exploding Gradients,
Truncated BPTT, GRU, LSTMs,
Encoder Decoder Models,
Attention Mechanism, Attention overimages.
UNIT-2 :
Autoencoders and relation to PCA,
Regularization in autoencoders,
Denoisingautoencoders,
Sparse autoencoders, Contractive autoencoders,
Regularization : Bias Variance Tradeoff,
L2 regularization, Early stopping,
Dataset augmentation,
Parameter sharing and tying,
Injecting noise at input, Ensemble methods,
Dropout, Batch Normalization,
Instance Normalization,
Group Normalization.
UNIT-3 :
Greedy Layerwise Pre-training,
Better activation functions,
Better weight initialization methods,
Learning Vectorial Representations Of Words,
Convolutional Neural Networks,
LeNet, AlexNet, ZF-Net, VGGNet,
GoogLeNet, ResNet,
Visualizing Convolutional Neural Networks,
Guided Backpropagation, Deep Dream,
Deep Art, Recent Trends in Deep Learning Architectures.
UNIT-4 :
Introduction to reinforcement learning(RL),
Bandit algorithms – UCB, PAC,Median Elimination,
Policy Gradient, Full RL & MDPs, Bellman Optimality,
Dynamic Programming - Value iteration,
Policy iteration, and Q-learning & Temporal Difference Methods,
Temporal-Difference Learning,
Eligibility Traces, Function Approximation,
Least Squares Methods
UNIT-5 :
Fitted Q, Deep Q-Learning ,
Advanced Q-learning algorithms ,
Learning policies by imitating optimal controllers ,
DQN & Policy Gradient, Policy Gradient Algorithms for Full RL,
Hierarchical RL,POMDPs,
Actor-Critic Method, Inverse reinforcement learning,
Maximum Entropy Deep Inverse Reinforcement Learning,
Generative Adversarial Imitation Learning,
Recent Trends in RL Architectures.
== END OF UNITS==
Syllabus of CS-702 (C) Wireless & Mobile Computing (Departmental Elective)
Source: (rgpv.ac.in)
UNIT-1 :
Review of traditional networks : Review of LAN, MAN, WAN, Intranet, Internet, and
interconnectivity devices : bridges, Routers etc.
Review of TCP/IP Protocol Architecture : ARP/RARP, IP addressing,
IP Datagram format and its Delivery,
Routing table format, ICMP Messages,
Subnetting, Supernetting and CIDR, DNS.
NAT : Private addressing and NAT,
SNAT, DNAT, NAT and firewalls,
VLANS : Concepts, Comparison with Real LANS,
Type of VLAN, Tagging,
IPV6 : address structure, address space and header.
UNIT-2 :
Study of traditional routing and transport : Routing Protocols: BGP- Concept of hidden network and autonomous system,
An Exterior gateway protocol, Different messages of BGP.
Interior Gateway protocol : RIP, OSPF.
Multiplexing and ports,
TCP : Segment format, Sockets,
Synchronization, Three Way Hand Shaking,
Variable window size and Flow control,
Timeout and Retransmission algorithms,
Connection Control, Silly window Syndrome.
Example of TCP : Taho, Reno, Sack etc.
UDP : Message Encapsulation,
Format and Pseudo header.
UNIT-3 :
Wireless LAN : Transmission Medium For WLANs,
MAC problems, Hidden and Exposed terminals,
Near and Far terminals,
Infrastructure and Ad hoc Networks,
IEEE 802.11- System arch,
Protocol arch, Physical layer,
Concept of spread spectrum,
MAC and its management,
Power management, Security.
Mobile IP: unsuitability of Traditional IP;
Goals, Terminology,
Agent advertisement and discovery,
Registration, Tunneling techniques.
Ad hoc network routing : Ad hoc Network routing v/s Traditional IP routing,
types of routing protocols,
Examples : OADV, DSDV, DSR, ZRP etc.
UNIT-4 :
Mobile transport layer : unsuitability of Traditional TCP;
I-TCP, S-TCP, M-TCP.
Wireless Cellular networks : Cellular system,
Cellular networks v/s WLAN, GSM – Services,
system architecture,
Localization and calling,
handover and Roaming.
UNIT-5 :
Mobile Device Operating Systems : Special Constraints & Requirements, Commercial Mobile Operating Systems.
Software Development Kit: iOS,
Android etc.MCommerce : Structure , Pros &Cons,
Mobile Payment System ,
Security Issues
== END OF UNITS==
Syllabus of CS-702 (D) Big Data (Departmental Elective )
Source: (rgpv.ac.in)
UNIT-1 :
Introduction to Big data,
Big data characteristics,
Types of big data,
Traditional versus Big data,
Evolution of Big data,
challenges with Big Data,
Technologies available for Big Data,
Infrastructure for Big data,
Use of Data Analytics,
Desired properties of Big Data system.
UNIT- 2 :
Introduction to Hadoop,
Core Hadoop components,
Hadoop Eco system,
Hive Physical Architecture,
Hadoop limitations, RDBMS Versus Hadoop,
Hadoop Distributed File system,
Processing Data with Hadoop,
Managing Resources and Application with Hadoop YARN,
MapReduce programming
UNIT-3 :
Introduction to Hive Hive Architecture,
Hive Data types, Hive Query Language,
Introduction to Pig, Anatomy of Pig,
Pig on Hadoop, Use Case for Pig,
ETL Processing, Data types in Pig running Pig,
Execution model of Pig,
Operators, functions,Data types of Pig.
UNIT-4 :
Introduction to NoSQL, NoSQL Business Drivers,
NoSQL Data architectural patterns,
Variations of NOSQL architectural patterns using NoSQL to Manage Big Data,
Introduction to MangoDB
UNIT-5 :
Mining social Network Graphs : Introduction Applications of social Network mining, Social Networks as a Graph,
Types of social Networks,
Clustering of social Graphs Direct Discovery of communities in a social graph,
Introduction to recommender system.
== END OF UNITS==
Syllabus of CS-703 (A) Cryptography & Information Security (Open Elective)
Source: (rgpv.ac.in)
UNIT-1 :
Mathematical Background for Cryptography : Abstract Algebra, Number Theory, Modular Inverse, Extended Euclid Algorithm,
Fermat's Little Theorem, Euler Phi-Function,
Euler's theorem.
Mathematical Background for Cryptography : Abstract Algebra,
Number Theory, Modular Inverse,
Extended Euclid Algorithm, Fermat's Little Theorem,
Euler Phi-Function, Euler's theorem.
Introduction to Cryptography : Principles of Cryptography,
Classical Cryptosystem,
Cryptanalysis on Substitution Cipher (Frequency Analysis),
Play Fair Cipher, Block Cipher. Data Encryption Standard (DES),
Triple DES, Modes of Operation, Stream Cipher.
Principles of Cryptography, Classical Cryptosystem,
Cryptanalysis on Substitution Cipher (Frequency Analysis),
Play Fair Cipher, Block Cipher.
Data Encryption Standard (DES),
Triple DES, Modes of Operation,
Stream Cipher.
UNIT-2 :
Advanced Encryption Standard (AES),
Introduction to Public Key Cryptosystem,
Discrete Logarithmic Problem,
Diffie-Hellman Key Exchange Computational & Decisional Diffie-Hellman Problem, RSA Assumptions & Cryptosystem,
RSA Signatures & Schnorr Identification Schemes,
Primarily Testing, Elliptic Curve over the Reals,
Elliptic curve Modulo a Prime.,
Chinese Remainder Theorem.
UNIT-3 :
Message Authentication,
Digital Signature, Key Management,
Key Exchange, Hash Function.
Universal Hashing,
Cryptographic Hash Function,
MD, Secure Hash Algorithm (SHA),
Digital Signature Standard (DSS),
Cryptanalysis : Time-Memory Trade-off Attack,
Differential Cryptanalysis.
Secure channel and authentication system like Kerberos.
UNIT-4 :
Information Security : Threats in Networks,
Network Security Controls–Architecture,
Wireless Security, Honey pots,
Traffic Flow Security, Firewalls – Design and Types of Firewalls,
Personal Firewalls, IDS,
Email Security : Services Security for Email Attacks Through Emails, Privacy-Authentication of Source Message,
Pretty Good Privacy(PGP), S-MIME.
IP Security : Overview of IPSec,
IP& IP version 6 Authentication,
Encapsulation Security Payload ESP,
Internet Key Exchange IKE,
Web Security : SSL/TLS, Basic protocols of security.
Encoding –Secure Electronic Transaction SET.
UNIT-5 :
Cryptography and Information Security Tools : Spoofing tools: like Arping etc., Foot printing Tools (ex-nslookup, dig, Whois,etc..),
Vulnerabilities Scanning Tools (i.e. Angry IP, HPing2,
IP Scanner, Global Network Inventory Scanner,
Net Tools Suite Pack.),
NetBIOS Enumeration Using NetView Tool,
Steganography Merge Streams,
Image Hide, Stealth Files, Blindsideusing:STools, Steghide, Steganos.
Stegdetect, Steganalysis - Stego Watch- Stego Detection Tool, StegSpy.
Trojans Detection Tools( i.e. Netstat, fPort, TCPView,
CurrPorts Tool, Process Viewer),
Lan Scanner Tools (i.e.look@LAN,
Wireshark, Tcpdump).
DoS Attack Understanding Tools- Jolt2, Bubonic.c,
Land and LaTierra, Targa, Nemesy Blast,
Panther2, Crazy Pinger, Some Trouble,
UDP Flood, FSMax.
== END OF UNITS==
Syllabus of CS-703 (B) Data Mining And Warehousing (Open Elective)
Source: (rgpv.ac.in)
UNIT-1 :
Data Warehousing : Introduction, Delivery Process,
Data warehouse Architecture,
Data Preprocessing : Data cleaning,
Data Integration and transformation, Data reduction.
Data warehouse Design : Datawarehouse schema,
Partitioning strategy Data warehouse Implementation,
Data Marts, Meta Data,
Example of a Multidimensional Data model.
Introduction to Pattern Warehousing.
UNIT-2 :
OLAP Systems : Basic concepts,
OLAP queries, Types of OLAP servers,
OLAP operations etc.
Data Warehouse Hardware and Operational Design : Security,
Backup And Recovery,
UNIT-3 :
Introduction to Data& Data Mining : Data Types, Quality of data,
Data Preprocessing, Similarity measures,
Summary statistics, Data distributions,
Basic data mining tasks,
Data Mining V/s knowledge discovery in databases.
Issues in Data mining.
Introduction to Fuzzy sets and fuzzy logic.
UNIT-4 :
Supervised Learning : Classification: Statistical-based algorithms,
Distance-based algorithms,
Decision tree-based algorithms,
Neural network-based algorithms,
Rule-based algorithms,
Probabilistic Classifiers
UNIT-5 :
Clustering & Association Rule mining : Hierarchical algorithms,
Partitional algorithms, Clustering large databases – BIRCH,
DBSCAN, CURE algorithms.
Association rules : Parallel and distributed algorithms such as Apriori and FP growth algorithms.
== END OF UNITS==
Syllabus of CS-703 (C) Agile Software Development (Open Elective )
Source: (rgpv.ac.in)
UNIT-1 :
Fundamentals of Agile Process : Introduction and background,
Agile Manifesto and Principles,
Stakeholders and Challenges,
Overview of Agile Development Models : Scrum, Extreme Programming,
Feature Driven Development,
Crystal, Kanban, and Lean Software Development.
UNIT-2 :
Agile Projects : Planning for Agile Teams: Scrum Teams,
XP Teams, General Agile Teams,
Team Distribution;
Agile Project Lifecycles : Typical Agile Project Lifecycles,
Phase Activities, Product Vision,
Release Planning : Creating the Product Backlog,
User Stories, Prioritizing and Estimating,
Creating the Release Plan;
Monitoring and Adapting : Managing Risks and Issues,
Retrospectives.
UNIT-3 :
Introduction to Scrum : Agile Scrum Framework,
\Scrum Artifacts, Meetings,
Activities and Roles, Scrum Team Simulation,
Scrum Planning Principles, Product and Release Planning,
Sprinting : Planning, Execution,
Review and Retrospective; User story definition and Characteristics,
Acceptance tests and Verifying stories,
Burn down chart, Daily scrum,
Scrum Case Study.
UNIT-4 :
Introduction to Extreme Programming (XP) : XP Lifecycle, The XP Team,
XP Concepts : Refactoring, Technical Debt,
Timeboxing, Stories, Velocity;
Adopting XP : Pre-requisites, Challenges;
Applying XP : Thinking- Pair Programming, Collaborating,
Release, Planning, Development;
XP Case Study.
UNIT-5 :
Agile Software Design and Development : Agile design practices,
Role of design Principles,
Need and significance of Refactoring,
Refactoring Techniques, Continuous Integration,
Automated build tools, Version control;
Agility and Quality Assurance : Agile Interaction Design,
Agile approach to Quality Assurance,
Test Driven Development,
Pair programming: Issues and Challenges.
== END OF UNITS==
Syllabus of CS-703 (D) Disaster Management (Open Elective )
Source: (rgpv.ac.in)
UNIT-1 : INTRODUCTION TO DISASTERS
Definition : Disaster, Hazard, Vulnerability, Resilience,
Risks – Disasters: Types of disasters – Earthquake,
Landslide, Flood, Drought,
Fire etc - Classification, Causes,
Impacts including social, economic,
political, environmental, health,
psychosocial, etc.
Differential impacts- in terms of caste, class, gender, age, location,
disability - Global trends in disasters: urban disasters,
pandemics, complexemergencies,
Climatechange-DosandDont’sduringvarious types of Disasters
UNIT-2 : APPROACHES TO DISASTER RISK REDUCTION
Disaster cycle - Phases, Culture of safety,
prevention, mitigation and preparedness community based DRR,
Structural- nonstructural measures,
Roles and responsibilities of- community,
Panchayati Raj Institutions/Urban Local Bodies (PRIs/ULBs),
States, Centre, and other stake-holders- Institutional Processess and Framework at State and Central Level- State Disaster Management Authority(SDMA) – Early Warning System – Advisories from Appropriate Agencies.
UNIT-3 : INTER-RELATIONSHIP BETWEEN DISASTERS AND DEVELOPMENT
Factors affecting Vulnerabilities,
differential impacts,
impact of Development projects such as dams,
embankments, changes in Land-use etc.
Climate Change Adaptation- IPCC Scenario and Scenarios in the context of India - Relevance of indigenous knowledge,
appropriate technology and local resources
UNIT-4 : DISASTER RISK MANAGEMENT IN INDIA
Hazard and Vulnerability profile of India,
Components of Disaster Relief : Water, Food, Sanitation,
Shelter, Health, Waste Management,
Institutional arrangements (Mitigation, Response and Preparedness)
Disaster Management Act and Policy - Other related policies,
plans, programmes and legislation – Role of GIS and Information Technology Components in Preparedness,
Risk Assessment, Response and Recovery
Phases of Disaster – Disaster Damage Assessment
UNIT-5 : DISASTER MANAGEMENT : APPLICATIONS AND CASE STUDIES AND FIELD WORKS
Landslide Hazard Zonation : Case Studies,
Earthquake Vulnerability Assessment of Buildings and Infrastructure : Case Studies,
Drought Assessment : Case Studies,
Coastal Flooding : Storm Surge Assessment,
Floods : Fluvial and Pluvial
Flooding : Case Studies;
Forest Fire : Case Studies,
Man Made disasters : Case Studies,
Space Based Inputs for Disaster Mitigation and Management and field works related to disaster management.
== END OF UNITS==