Syllabus of B.tech. VI SEM AIML (RGPV)
Syllabus of B. Tech. VI Sem AIML (RGPV)
Syllabus of AL-601 Theory of Computation
Source: (rgpv.ac.in)
UNIT-1 :
Introduction of Automata Theory: Examples of automata machines,
Finite Automata as a language acceptor and translator,
Moore machines and mealy machines, composite machine,
Conversion from Mealy to Moore and vice versa
UNIT-2 :
Types of Finite Automata: Non Deterministic Finite Automata (NDFA),
Deterministic finite automata machines,
conversion of NDFA to DFA,
minimization of automata machines, regular expression,
Arden’s theorem.
Meaning of union, intersection,
concatenation and closure,
2 way DFA.
UNIT-3 :
Grammars: Types of grammar, context sensitive grammar, and context free grammar, regular grammar.
Derivation trees, ambiguity in grammar,
simplification of context free grammar,
conversion of grammar to automata machine and vice versa,
Chomsky hierarchy of grammar, killing null and unit productions.
Chomsky normal form and Greibach normal form.
UNIT-4 :
Push down Automata: example of PDA,
deterministic and non-deterministic PDA,
conversion of PDA into context free grammar and vice versa,
CFG equivalent to PDA, Petrinet model.
UNIT-5 :
Turing Machine: Techniques for construction. Universal Turing machine Multitape, multihead and multidimensional Turing machine,
N-P complete problems.
Decidability and Recursively Enumerable Languages,
decidability, decidable languages, undecidable languages,
Halting problem of Turing machine & the post correspondence problem
LIST OF EXPERIMENTS :
Design a Program for creating machine that accepts three consecutive one.
Design a Program for creating machine that accepts the string always ending with 101.
Design a Program for Mode 3 Machine
Design a program for accepting decimal number divisible by 2.
Design a program for creating a machine which accepts string having equal no. of 1’s and 0’s.
Design a program for creating a machine which count number of 1’s and 0’s in a given string.
Design a Program to find 2’s complement of a given binary number.
Design a Program which will increment the given binary number by 1.
Design a Program to convert NDFA to DFA.
Design a Program to create PDA machine that accept the well-formed parenthesis.
Design a PDA to accept WCWR where w is any string and WR is reverse of that string and C is a Special symbol.
Design a Turing machine that’s accepts the following language an b n c n where n>0
== END OF UNITS==
Syllabus of AL-602 Computer Networks
Source: (rgpv.ac.in)
UNIT-1 :
Computer Network: Definitions, goals, components, Architecture, Classifications & Types.
Layered Architecture: Protocol hierarchy,
Design Issues, Interfaces and Services,
Connection Oriented & Connection less Services, Service primitives,
Design issues & its functionality.
ISOOSI Reference Model: Principle, Model, Descriptions of various layers and its comparison with TCP/IP.
Principals of physical layer: Media, Bandwidth, Data rate and Modulations.
UNIT-2 :
Data Link Layer: Need, Services Provided, Framing,
Flow Control, Error control.
Data Link Layer Protocol: Elementary & Sliding Window protocol: 1-bit, Go-Back-N, Selective Repeat,
Hybrid ARQ.
Protocol verification: Finite State Machine Models & Petri net models. ARP/RARP/GARP
UNIT-3 :
MAC Sub layer: MAC Addressing, Binary Exponential Back-off (BEB) Algorithm,
Distributed Random Access Schemes/Contention Schemes: for Data Services (ALOHA and Slotted ALOHA),
for Local-Area Networks (CSMA, CSMA/CD, CSMA/CA),
Collision Free Protocols: Basic Bit Map, BRAP, Binary Count Down,
MLMA Limited Contention Protocols: Adaptive Tree Walk,
Performance Measuring Metrics.
IEEE Standards 802 series & their variant
UNIT-4 :
Network Layer: Need, Services Provided , Design issues,
Routing algorithms: Least Cost Routing algorithm, Dijkstra's algorithm,
Bellman-ford algorithm, Hierarchical Routing, Broadcast Routing, Multicast Routing.
IP Addresses, Header format, Packet forwarding,
Fragmentation and reassembly, ICMP, Comparative study of IPv4 & IPv6.
UNIT-5 :
Transport Layer: Design Issues,
UDP: Header Format, Per-Segment Checksum, Carrying Unicast/Multicast Real-Time Traffic,
TCP: Connection Management, Reliability of Data Transfers,
TCP Flow Control, TCP Congestion Control,
TCP Header Format, TCP Timer Management.
Application Layer: WWW and HTTP, FTP, SSH, Email (SMTP, MIME, IMAP), DNS, Network Management (SNMP).
LIST OF EXPERIMENTS :
Study of Different Type of LAN& Network Equipments.
Study and Verification of standard Network topologies i.e. Star, Bus, Ring etc.
LAN installations and Configurations.
Write a program to implement various types of error correcting techniques.
Write a program to implement various types of farming methods.
Study of Tool Command Language (TCL).
Study and Installation of Standard Network Simulator: N.S-2, N.S3.OpNet,QualNetetc.
Study & Installation of ONE (Opportunistic Network Environment) Simulator for High Mobility Networks .
Configure 802.11 WLAN.
Implement &Simulate various types of routing algorithm.
Study & Simulation of MAC Protocols like Aloha, CSMA, CSMA/CD and CSMA/CA using Standard Network Simulators.
Study of Application layer protocols-DNS, HTTP, HTTPS, FTP and TelNet.
== END OF UNITS==
Syllabus of AL-603 (A) Image and Video Processing (Departmental Elective)
Source: (rgpv.ac.in)
MODULE-1 :
Image representation and analysis,
Introduction to computer Vision,
Numerical representation of images,
Image augmentation, enhancement,
processing, color transforms, geometric transforms,
feature recognition and extraction
MODULE-2 :
Image Segmentation Object detection,
breaking image into parts,
finding contours and edges of various objects in image,
Background subtraction for video.
MODULE-3 :
Object Motion and tracking Tracking a single point over time,
motion models to define object movement over time,
analyze videos as sequences of individual image frames,
methods to track a set of features over time
matching features from image frame to other,
tracking a moving car using optical flow
MODULE-4 :
Robotic localization
Bayesian statistics to locate a robot in space,
sensor measurements to safely navigate an environment,
Gaussian uncertainty,
histogram filter for robot localization in python
MODULE-5 :
Degradation model,
noise models,
estimation of degradation function by modeling,
restoration using Weiner filters and Inverse filters
LIST OF EXPERIMENTS :
Various forms of image representation
Apply various image segmentation algorithms
Apply object motion and tracking
Apply object localization
Apply image restoration
== END OF UNITS==
Syllabus of AL-603 (B) Data and Visual Analytics (Departmental Elective)
Source: (rgpv.ac.in)
UNIT-1 : Data Definitions and Analysis Techniques
Elements, Variables, and Data categorization Levels of Measurement Data management and indexing
Introduction to Statistical Concepts: Sampling Distributions, Resampling,
Statistical Inference and Descriptive Statistics,
Measures of central tendency,
Measures of location of dispersions
UNIT-2 : Advance Data analysis techniques
Statistical hypothesis generation and testing,
Chi-Square test,
t-Test, Analysis of variance,
Correlation analysis, Maximum likelihood test,
Regression Modelling, Multivariate Analysis,
Bayesian Modelling, Inference and Bayesian Network,
Regression analysis
UNIT-3 : Data Wrangling
Intro to Data Wrangling,
Gathering Data,
Assessing Data, Cleaning Data.
Data Visualization in Data Analysis: Design of Visualizations,
Univariate Exploration of Data,
Bivariate Exploration of Data, Multivariate Exploration of Data,
Explanatory Visualizations.
UNIT-4 : Data Ecosystem
Overview of the Data Analyst Ecosystem, Types of Data,
Understanding Different Types of File Formats,
Sources of Data, Overview of Data Repositories, NoSQL,
Data Marts, Data Lakes, ETL, and Data Pipelines,
Foundations of Big Data,
Big Data processing tools such as Hadoop, Hadoop Distributed File System (HDFS),
Hive, and Spark
UNIT-5 : Data Visualization tools
Python visualization libraries (matplotlib, pandas, seaborn, ggplot, plotly),
Introduction to PowerBI tools,
Examples of inspiring (industry) projects-
Exercise: create your own visualization of a complex dataset.
== END OF UNITS==
Syllabus of AL-603 (C) Pattern Recognition (Departmental Elective)
Source: (rgpv.ac.in)
MODULE-1 :
Introduction and mathematical Preliminaries Principles of pattern recognition: Uses, mathematics,
Classification and Bayesian rules,
Clustering vs classification,
Basics of linear algebra and vector spaces,
Eigen values and eigen vectors,
Rank of matrix and SVD
MODULE- 2 :
Pattern Recognition basics Bayesian decision theory,
Classifiers, Discriminant functions,
Decision surfaces, Parameter estimation methods,
Hidden Markov models, dimension reduction methods,
Fisher discriminant analysis,
Principal component analysis, non-parametric techniques for density estimation,
non metric methods for pattern classification,
unsupervised learning,
algorithms for clustering: K means, Hierarchical and other methods
MODULE-3 :
Feature Selection and extraction Problem statement and uses,
Branch and bound algorithm,
Sequential forward and backward selection,
Cauchy Schwartz inequality,
Feature selection criteria function: Probabilistic separability based and Inter class distance based,
Feature Extraction: principles.
MODULE-4 :
Visual Recognition Human visual recognition system,
Recognition methods: Low-level modelling (e.g. features), Midlevel abstraction (e.g. segmentation), High-level reasoning (e.g. scene understanding);
Detection/Segmentation methods;
Context and scenes, Importance and saliency,
Large-scale search and recognition,
Egocentric vision, systems,
Human-in-the-loop interactive systems,
3D scene understanding
MODULE-5 :
Recent advancements in Pattern Recognition Comparison between performance of classifiers,
Basics of statistics, covariance and their properties,
Data condensation, feature clustering,
Data visualization, Probability density estimation,
Visualization and Aggregation,
FCM and softcomputing techniques,
Examples of real-life datasets
LIST OF EXPERIMENTS :
Data extraction
Pre-processing of images
Image segmentation
Image classification AICTE
== END OF UNITS==
Syllabus of AL-604 (A) Cloud Computing (Open Elective)
Source: (rgpv.ac.in)
UNIT-1 :
Introduction of Grid and Cloud computing, characteristics, components,
business and IT perspective,
cloud services requirements, cloud models,
Security in public model, public verses private clouds,
Cloud computing platforms: Amazon EC2,
Platform as Service: Google App Engine, Microsoft Azure, Utility Computing, Elastic Computing.
UNIT-2 :
Cloud services- SAAS, PAAS, IAAS,
cloud design and implementation using SOA,
conceptual cloud model, cloud stack, computing on demand,
Information life cycle management, cloud analytics,
information security, virtual desktop infrastructure, storage cloud.
UNIT-3 :
Virtualization technology: Definition, benefits, sensor virtualization,
HVM, study of hypervisor,
logical partitioning- LPAR, Storage virtualization, SAN, NAS,
cloud server virtualization,
virtualized data center.
UNIT-4 :
Cloud security fundamentals,
Vulnerability assessment tool for cloud,
Privacy and Security in cloud,
Cloud computing security architecture: Architectural Considerations- General Issues,
Trusted Cloud computing,
Secure Execution Environments and Communications,
Micro architectures;
Identity Management and Access control-Identity management,
Access control, Autonomic Security,
Cloud computing security challenges: Virtualization security management virtual threats,
VM Security Recommendations,
VM-Specific Security techniques,
Secure Execution Environments and Communications in cloud
UNIT-5 :
SOA and cloud, SOA and IAAS,
cloud infrastructure benchmarks, OLAP, business intelligence,
e-Business, ISV,
Cloud performance monitoring commands, issues in cloud computing.
QOS issues in cloud, mobile cloud computing,
Inter cloud issues, Sky computing,
Cloud Computing Platform, Xen Cloud Platform,
Eucalyptus, OpenNebula, Nimbus, TPlatform,
Apache Virtual Computing Lab (VCL),
Anomaly Elastic Computing Platform.
== END OF UNITS==
Syllabus of AL-604 (B) Information Security & Management (Open Elective)
Source: (rgpv.ac.in)
UNIT-1 :
Introduction: Needs for Security;
Basic security terminologies e.g. threats, vulnerability, exploit etc.;
Security principles(CIA), authentication, non repudiation;
security attacks and their classifications;
Mathematical foundation - Prime Number;
Modular Arithmetic;
Fermat’s and Euler’s Theorem;
The Euclidean Algorithms;
The Chinese Remainder Theorem;
Discrete logarithms.
UNIT-2 :
Symmetric Key Cryptography: Classical cryptography – substitution, transposition and their cryptanalysis;
Symmetric Cryptography Algorithm – DES, 3DES, AES etc.;
Modes of operation: ECB, CBC etc.;
Cryptanalysis of Symmetric Key Ciphers: Linear Cryptanalysis, Differential Cryptanalysis.
UNIT-3 :
Asymmetric Key Cryptography: Key Distribution and Management,
Diffie-Hellman Key Exchange algorithm;
Asymmetric Key Cryptography Algorithm– RSA, ECC etc.;
Various types of attacks on Crypto systems.
UNIT-4 :
Authentication & Integrity – MAC, Hash function, SHA, MD5, HMAC,
Digital signature and authentication protocols;
Authorization;
Access control mechanism;
X.509 Digital Certificate
UNIT-5 :
E-mail, IP and Web Security: E-mail security – PGP, MIME, S/MIME;
IP security protocols;
Web security – TLS, SSL etc.;
Secure Electronic Transaction(SET);
Firewall and its types;
Introduction to IDPS;
Risk Management;
Security Planning
== END OF UNITS==
Syllabus of AL-604 (C) Intelligent Systems for Robotics (Open Elective)
Source: (rgpv.ac.in)
UNIT-1 :
Introduction: Introduction to Robotics Fundamentals of Robotics,
Robot Kinematics: Position Analysis,
Dynamic Analysis and Forces,
Robot Programming languages & systems: Introduction, the three levels of robot programming,
requirements of a robot programming language,
problems peculiar to robot programming languages.
UNIT-2 :
Need of AI in Robotics: History, state of the art, Need for AI in Robotics.
Thinking and acting humanly,
intelligent agents,
structure of agents.
UNIT-3 :
Game Playing: AI and game playing,
plausible move generator,
static evaluation move generator,
game playing strategies,
problems in game playing.
UNIT-4 :
Robotics fundamentals: Robot Classification, Robot Specification,
notation, kinematic representations and transformations,
dynamics techniques;
trajectory planning and control.
UNIT-5 :
Robotics and Its applications: DDD concept, Intelligent robots,
Robot anatomy-Definition, law of robotics,
History and Terminology of Robotics-Accuracy and repeatability of Robotics-Simple problems-Specifications of Robot-Speed of Robot,
Robot joints and links-Robot classifications Architecture of robotic systems-Robot Drive systems-Hydraulic,
Pneumatic and Electric system
== END OF UNITS==