CS.com

Syllabus of B.tech. VIII SEM CSIT (RGPV)

Syllabus of B. Tech. VIII Sem CSIT (RGPV)

Syllabus of CSIT-801 Data Science

CSIT-801-Data-Science.pdf 
Source: (rgpv.ac.in)

UNIT-1 :

  • Data Science and Big Data Overview : Types of data Sources of data Data collection Data storage and management
  • Big Data Overview Characterization o f Big data Drivers of Big Data
  • Challenges Big Data Use Cases Defining Big Data Analytics and examples of its use cases
  • Data Analytics Lifecycle : Discovery Data Preparation Model Planning Model Building Communicate Results Operationalize.

UNIT-2 :

  • Advanced Analytical Theory and Methods : Clustering K-means Additional Clustering Algorithms Association Rules Apriori Algorithm
  • Applications of Association Rules Regression Linear Regression Logistic Regression
  • Classification Decision Trees Naive Bayes Additional Classification Methods
  • Text Analysis Text Analysis Steps Determining Sentiments.

UNIT-3 :

  • Advanced Analytics-Technology and Tools : Analytics for Unstructured Data Use Cases MapReduce Apache Hadoop
  • Traditional database vs. Hadoop Hadoop Core Components HDFS
  • Design of HDFS HDFS Components HDFS Architecture
  • Hadoop 2.0 Architecture Hadoop-2.0 Resource Management YARN.

UNIT-4 :

  • The Hadoop Ecosystem : Introduction to Hive Hbase
  • Hive Use Cases : Face book Healthcare;
  • Hive Architecture Hive Components.
  • Integrating Data Sources Dealing with Real-Time Data Streams Complex Event Processing
  • Overview of Pig Difference between Hive and Pig
  • Use Cases of Pig Pig program structure Pig Components Pig Execution Pig data models
  • Overview of Mahout Mahout working.

UNIT-5 :

  • Introduction to R : Basic Data Analytics Methods Using R
  • Communicating and Operationalizing an Analytics Project
  • Creating the Final Deliverables Data Visualization Basics.

LIST OF EXPERIMENTS :

    1. Introduction to R tool for data analytics science
    2. Basic Statistics and Visualization in R
    3. K-means Clustering
    4. Association Rules
    5. Linear Regression
    6. Logistic Regression
    7. Naive Bayesian Classifier
    8. Decision Trees
    9. Simulate Principal component analysis
    10. Simulate Singular Value Decomposition

  1.  

  1.  

  1.  

  1.  

  1.  

  1.  

  1.  

  1.  

  1.  

== END OF UNITS==

 

Syllabus of CSIT-802(A) Data Warehousing & Mining (Departmental Elective)

CSIT-802A-Data-Warehousing-Mining.pdf

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 : Data warehouse 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.

LIST OF EXPERIMENTS :

    1. Create an Employee Table with the help of Data Mining Tool WEKA.
    2. Create a Weather Table with the help of Data Mining Tool WEKA.
    3. Pre-Processing techniques to the training data set of Weather Table
    4. Apply Pre-Processing techniques to the training data set of Employee Table
    5. Normalize Weather Table data using Knowledge Flow
    6. .Normalize Employee Table data using Knowledge Flow.
    7. Finding Association Rules for Buying data.
    8. Finding Association Rules for Banking data.F
    9. inding Association Rules for Employee data.
    10. To Construct Decision Tree for Weather data and classify it.

  1.  

  1.  

  1.  

  1.  

  1.  

  1.  

  1.  

  1.  

  1.  

== END OF UNITS==

 

Syllabus of CSIT-802(B) Bio Informatics (Departmental Elective)

CSIT-802B-Bio-Informatics.pdf

Source: (rgpv.ac.in)

UNIT-1 :

  • Introduction: Introduction to bioinformatics objectives of bioinformatics
  • Basic chemistry of nucleic acids structure of DNA & RNA Genes
  • structure of bacterial chromosome cloning methodology
  • Data maintenance and Integrity Tasks

UNIT-2 :

  • Bioinformatics Databases & Image Processing : Types of databases Nucleotide sequence databases
  • Protein sequence databases Protein structure databases Normalization
  • Data cleaning and transformation Protein folding
  • protein function protein purification and characterization
  • Introduction to Java clients CORBA
  • Using MYSQL Feature Extraction.

UNIT-3 :

  • Sequence Alignment and database searching : Introduction to sequence analysis Models for sequence analysis
  • Methods of optimal alignment Tools for sequence alignment
  • Dynamics Programming Heuristic Methods
  • Multiple sequences Alignment

UNIT-4 :

  • Gene Finding and Expression : Cracking the Genome Biological decoder ring finding genes through mathematics & learning
  • Genes prediction tools Gene Mapping
  • Application of Mapping Modes of Gene Expression data
  • mining the Gene Expression Data

UNIT-5 :

  • Proteomics & Problem solving in Bioinformatics : Proteome analysis tools for proteome analysis Genetic networks Network properties and analysis
  • complete pathway simulation : E-cell
  • Genomic analysis for DNA & Protein sequences
  • Strategies and options for similarity search
  • flowcharts for protein structure prediction

LIST OF EXPERIMENTS :

    1. To find information in online databases.
    2. To retrieve the sequence of the Human keratin protein from UniProt database and to interpret the results.
    3. To retrieve the sequence of the Human keratin protein from Genbank database and to interpret the results.
    4. To find the similarity between sequences using BLAST.
    5. To find the similarity between sequences using FASTA
    6. To align more than two sequences and find out the similarity between those sequences using ClustalW.

  1.  

  1.  

  1.  

  1.  

  1.  

== END OF UNITS==

 

Syllabus of CSIT-802(C) Web & Information Retrieval (Departmental Elective)

CSIT-802C-Web-Information-Retrieval.pdf

Source: (rgpv.ac.in)

UNIT-1 :

  • Introduction : Information versus data retrieval the retrieval process
  • taxonomy of Information Retrieval Models.

UNIT-2 :

  • Classic Information Retrieval Techniques : Boolean Model Vector model Probabilistic Model
  • comparison of classical models.Intro
  • duction to alternative algebraic models such as Latent semantic Indexing etc.
  •  

  •  

UNIT-3 :

  • Keyword based Queries
  • User Relevance Feedback : Query Expansion and Rewriting
  • Document preprocessing and clustering
  • Indexing and Searching : Inverted Index construction
  • Introduction to Pattern matching.

UNIT-4 :

  • Web Search : Crawling and Indexes Search Engine architectures
  • Link Analysis and ranking algorithms such as HITS and Page Rank Meta searches
  • Performance Evaluation of search engines using various measures
  • Introduction to search engine optimization.

UNIT-5 :

  • Introduction to online IR Systems
  • Digital Library searches and web Personalization

LIST OF EXPERIMENTS :

    1. Students must experiment on various information retrieval systems like page rank etc

== END OF UNITS==

 

Syllabus of CSIT-802(D) Block Chain Technology (Departmental Elective)

CSIT-802D-Block-Chain-Technology.pdf

Source: (rgpv.ac.in)

UNIT-1 :

  • Introduction and crypto foundation : Elliptic curve cryptography ECDSA
  • Cryptographic hash function SHA-256 Merkle trees
  • Cryptocurrencies.

UNIT-2 :

  • Bitcoin Bitcoin addresses Bitcoin blockchain block header
  • mining proof of work (PoW) algorithm difficulty adjustment algorithm mining pools transactions double spending attack
  • The 51% attacker block format transaction format
  • Smart contacts (escrow micropayments decentralized lotteries) payment channels.

UNIT-3 :

  • Ethereum : Overview of differences between Ethereum and bitcoin
  • block format mining algorithm proof-of-stake (PoS) algorithm
  • account management contracts and transactions
  • Solidity language decentralized application using Ethereum

UNIT-4 :

  • Smart Contracts Different Blockchains and Consensus mechanisms

UNIT-5 :

  • Blockchain and Security R3 CORDA and Hyperledger System architecture
  • ledger format chain code
  • transaction flow and ordering private channels
  • membership service providers case studies.

LIST OF EXPERIMENTS :

    1. To Create a first block in blockchain
    2. To encrypt a block using Sha 256 Encryption Algorithm
    3. To Mine a Block in Blockchain
    4. To authenticate a mined block using consensus algorithm’
    5. To implement proof of work
    6. To secure a block using encryption
    7. To create a simple cryptocurrency
    8. To write a smart contract in solidity

  1.  

  1.  

  1.  

  1.  

  1.  

  1.  

  1.  

== END OF UNITS==

 

Syllabus of CSIT-803 (A) Digital Marketing and SEO (Open Elective)

CSIT-803-A-Digital-Marketing-and-SEO.pdf

Source: (rgpv.ac.in)

UNIT-1 :

  • Digital Marketing : Introduction Moving from Traditional to Digital Marketing
  • Integrating Traditional and Digital Marketing Reasons for Growth.
  • Need for a comprehensive Digital Marketing Strategy.
  • Concepts : Search Engine Optimization (SEO);
  • Concept of Pay Per Click

UNIT-2 :

  • Social Media Marketing : Introduction Process – Goals Channels Implementation
  • Analyze Tools : Google and the Search Engine Facebook Twitter YouTube and LinkedIn Issues : Credibility Fake News Paid Influencers Social Media and Hate/ Phobic campaigns
  • Analytics and linkage with Social Media
  • The Social Community.

UNIT-3 :

  • Email Marketing : Introduction email marketing process design and content delivery discovery.
  • Mobile Marketing : Introduction and concept
  • Process of mobile marketing : goals setup monitor analyze;
  • Enhancing Digital Experiences with Mobile Apps. Pros and Cons;
  • Targeted advertising.
  • Issues : Data Collection Privacy Data Mining Money and Apps Security Spam. Growth Areas.

UNIT-4 :

  • Managing Digital Marketing: Content Production;
  • Video based marketing;
  • Credibility and Digital Marketing;
  • IoT;
  • User Experience;
  • Future of Digital Marketing.

UNIT-5 :

  • SEO Analytics Monitoring & Reporting : Google Search Console (GSC)Key Sections & Features of GSC;
  • How to monitor SEO progress with Key Features of GSC : Overview Performance URL Inspection
  • Coverage Sitemaps Speed Mobile Usability
  • Backlinks Referring Domains Security & Manual Actions
  • How to do SEO Reporting

== END OF UNITS==

 

Syllabus of CSIT-803(B) Quantum Computing (Open Elective)

CSIT-803-B-Quantum-Computing.pdf

Source: (rgpv.ac.in)

UNIT-1 :

  • Introduction to quantum mechanics : Postulates of quantum mechanics
  • Qubit and quantum states Vector Spaces
  • Single Qubit Gates multiple Qubit Gates Controlled Gates
  • Composite Gates Matrices and operators.

UNIT- 2 :

  • Density operators : Density Operator for a Pure State Density Operator for a Mixed State
  • Properties of a Density Operator Characterizing Mixed States
  • Completely Mixed States Partial Trace and Reduced Density Operator.
  • Quantum measurement theory : Distinguishing Quantum States and Measurement Projective Measurements
  • Measurements on Composite Systems Generalized Measurements
  • Positive Operator Valued Measures.

UNIT-3 :

  • Entanglement : Quantum state entanglement Bell’s Theorem The Pauli Representation
  • Using Bell States For Density Operator Representation
  • Quantum gates and circuits : Single Qubit Gates The Z Y Decomposition Basic Quantum Circuit Diagrams Controlled Gates
  • Application of Entanglement in teleportation and supper dense coding.
  • Distributed quantum communication
  • Quantum Computer : Guiding Principles Conditions for Quantum Computation Harmonic Oscillator Quantum Computer
  • Optical Photon Quantum Computer – Optical cavity Quantum electrodynamics Ion traps Nuclear Magnetic resonance.

UNIT-4 :

  • Quantum Algorithm : Hadamard Gates The Phase Gate Matrix Representation of Serial and Parallel Operations
  • Quantum Interference Quantum Parallelism and Function Evaluation
  • Deutsch -Jozsa Algorithm Quantum Fourier Transform
  • Phase Estimation Shor’s Algorithm
  • Quantum Searching and Grover’s Algorithm

UNIT-5 :

  • Quantum Error Correction : Introduction Shor code Theory of Quantum Error Correction
  • Constructing Quantum Codes Stabilizer codes Fault Tolerant Quantum Computation
  • Entropy and information –Shannon Entropy
  • Basic properties of EntropyVon Neumann
  • Strong Sub Additivity Data Compression
  • Entanglement as a physical resource.

== END OF UNITS==

 

Syllabus of CSIT- 803 (C) Cyber Laws and Forensics (Open Elective)

CSIT-803-C-Cyber-Laws-and-Forensics.pdf

Source: (rgpv.ac.in)

UNIT-1 :

  • Introduction to cybercrime definition cyber crime and information security classification of cybercrimes
  • Cybercrime : the legal perspectives an Indian perspective cybercrime and the Indian ITA 2000 a global perspective on cybercrime
  • Cyber offences : How criminals plan them Tools and methods used in cyber crime Need of cyber law
  • The Indian IT act challenges to Indian law and cybercrime scenario in India digital signature and Indian IT act

UNIT-2 :

  • Law and framework for information security law for intellectual property rights (IPR) patent law copy right law
  • Indian copyright act privacy issue and law in Hong Kong Japan and Australia data protection act in Europe
  • health insurance portability and accountability act of 1996(HIPAA)
  • Gramm-leach-Bliley act of 1999(GLAB)
  • Sarbanes-Oxley(SOX)
  • legal issue in data mining.

UNIT-3 :

  • Digital forensics Science The need for computer forensics
  • Understanding computer forensics computer forensics versus other related disciplines A brief History of computer Forensics
  • Cyber forensics and digital evidence Digital forensics lifecycle chain of custody concept
  • Network forensics Approaching a computer forensics investigation setting up a computer forensics laboratory
  • Forensics and social networking sites computer forensics from compliance perspective
  • challenges in computer forensics forensics auditing anti forensics.

UNIT-4 :

  • Current Computer Forensics Tools Evaluating Computer Forensics Tool Needs
  • Types of Computer Forensics Tools
  • Tasks Performed by Computer Forensics Tools Tool Comparisons
  • Other Considerations for Tools Computer Forensics Software Tools
  • Command-Line Forensics Tools UNIX/Linux Forensics Tools
  • Other GUI Forensics Tools Computer Forensics Hardware Tools Forensic Workstations

UNIT-5 :

  • Forensics of hand held devices Investigating Network Intrusions and Cyber Crime
  • Network Forensics and investigating logs investigating network Traffic
  • Investigating Web attacks Router Forensics.
  • Cyber forensics tools and case studies

== END OF UNITS=

 

Syllabus of CSIT-803 (D) ROBOTICS (Open Elective)

CSIT-803-D-ROBOTICS.pdf

Source: (rgpv.ac.in)

UNIT-1 :

  • Fundamentals of Robot : Robot – Definition – Robot Anatomy

  • Co-ordinate Systems Work Envelope types and classification

  • Specifications – Pitch Yaw Roll Joint Notations Speed of Motion

  • Pay Load – Robot Parts and Functions

  • Need for Robots – Different Applications

UNIT- 2 :

  • Robot Drive Systems and End Effectors : Pneumatic Drives Hydraulic Drives Mechanical Drives Electrical Drives
  • D.C. Servo Motors Stepper Motor A.C. Servo Motors – Salient Features
  • Applications and Comparison of Drives End Effectors – Grippers – Mechanical Grippers
  • Pneumatic and Hydraulic Grippers Magnetic Grippers Vacuum Grippers;
  • Two Fingered and Three Fingered Grippers;
  • Internal Grippers and External Grippers;
  • Selection and Design Considerations.

UNIT-3 :

  • Sensors and Machine Vision : Requirements of a sensor Principles and

  • Applications of the following types of sensors– Position of sensors (Piezo Electric Sensor LVDT Resolvers
  • Optical Encoders Pneumatic Position Sensors)
  • Range Sensors (Triangulation Principle Structured Lighting Approach Time of Flight Range Finders Laser Range Meters)
  • Proximity Sensors (Inductive Hall Effect Capacitive Ultrasonic and Optical Proximity Sensors)Touch Sensors (Binary Sensors Analogue Sensors)
  • Wrist Sensors Compliance Sensors Slip Sensors. Camera Frame Grabber
  • Sensing and Digitizing Image Data – Signal Conversion Image Storage Lighting Techniques.
  • Image Processing and Analysis
  • Data Reduction : Edge detection Feature Extraction and Object Recognition -Algorithms.
  • Applications– Inspection Identification Visual Serving and Navigation

UNIT-4 :

  • Robot Kinematics and Robot Programming : Forward Kinematics Inverse Kinematics and Differences;
  • Forward Kinematics and Reverse Kinematics of Manipulators with Two Three Degrees of Freedom (In 2Dimensional)
  • Four Degrees of Freedom (In 3 Dimensional) – Deviations and Problems.
  • Teach Pendant Programming Lead through programming
  • Robot programming Languages – VAL Programming – Motion Commands
  • Sensor Commands End effecter commands and Simple programs

UNIT-5 :

  • Implementation and Robot Economics : RGV AGV;
  • Implementation of Robots in Industries – Various Steps;
  • Safety Considerations for Robot Operations;
  • Economic Analysis of Robots – Pay back Method EUAC Method Rate of Return Method.

== END OF UNITS==

==End of Syllabus==