Syllabus for
Bachelor of Technology (Information Technology)
Academic Year  (2022)

The Undergraduate program in Information Technology is aimed at creating computer science engineers by providing the fundamentals of engineering and basic skills in computing. The special focus on employability is clear from the inclusion of subjects based on demand of industry and mandatory internships. A well-chosen elective basket gives the ward an opportunity to widen their knowledge in any specific domain.

Programme Outcome/Programme Learning Goals/Programme Learning Outcome:

PO2: Think critically to identify, formulate, and solve complex computer science & engineering problems by developing models, evaluating validity and accuracy of solutions in terms of computer science and engineering validity measures.

PO3: Analyse, design of complex problems, implement, and evaluate a computer-based system, to meet expected needs with appropriate considerations such as economic / environmental/societal.

PO4: Conduct experiments to investigate problems based on changing requirements, analyze and interpret results.

PO5: Create, select, adapt appropriate techniques and use of the modern computational tools, techniques and skills, and best of engineering practices.

PO6: Understand the impact of contextual knowledge on social aspects and cultural issues.

PO7: Understand contemporary issues related to social & environmental context for sustainable development of engineering solutions.

PO8: Understand professional & ethical responsibility to contribute for societal and national needs.

PO9: Function and coordinate effectively as an individual, as a member or leader in diverse, multicultural& multidisciplinary teams

PO10: Communicate effectively.

PO11: Demonstrate an understanding of computer science and engineering & management principles to manage software projects.

Continuous internal Assesment-CIA-I,CIA-II,CIA-III

End Semester Examination

To learn the fundamentals of data models and to conceptualize and depict a database system using ER diagram. To make a study of SQL and relational database design. To understand the internal storage structures using different file and indexing techniques which will help in physical DB design. To know the fundamental concepts of transaction processing- concurrency control techniques and recovery procedure. To have an introductory knowledge about the emerging trends in the area of distributed DBOO DB- Data mining and Data Warehousing and XML. To implement the design of the tables in DBMS. To write queries to get optimized outputs. To store, retrieve and view the contents. To generate report based on customized need

Introduction to File and Database systems- Database system structure – Data Models – Introduction to Network and Hierarchical Models – ER model – Relational Model – Relational Algebra.

SQL – Data definition- Queries in SQL- Updates- Views – Integrity and Security – Relational Database design – Functional dependencies and Normalization for Relational Databases (up to BCNF).

Introduction to NOSQL Systems ,The CAP Theorem, Document-Based NOSQL Systems and MongoDB, NOSQL Key-Value Stores, Column-Based or Wide Column NOSQL Systems, NOSQL Graph Databases and Neo4j 

Record storage and Primary file organization- Secondary storage Devices- Operations on FilesHeap File- Sorted Files- Hashing Techniques – Index Structure for files –Different types of Indexes- B-Tree - B+ Tree – Query Processing.

Transaction management -Transaction Processing – Introduction- Need for Concurrency control- Desirable properties of Transaction- Schedule and Recoverability- Serializability and Schedules – Concurrency Control – Types of Locks- Two Phases locking- Deadlock- Time stamp based concurrency control – Recovery Techniques – Concepts- Immediate Update- Deferred Update - Shadow Paging.

Raghu Ramakrishnan, “Database Management System”, Tata McGraw-Hill Publishing Company, 2003

Online Resources: W1.http://db-book.com/db6/slide-dir

ESE:30/100

To understand the basic concept of data structures for storage and retrieval of ordered or unordered data. Data structures include: arrays, linked lists, binary trees, heaps, and hash tables.

Definition- Classification of data structures: primitive and non-primitive- Operations on data structures- Algorithm Analysis: Introduction. The Stack ADT: Definition, Array representation of stack, Operations on stack: Infix, prefix and postfix notations Conversion of an arithmetic Expression from Infix to postfix. Applications of stacks.

The Queue ADT: Definition, Array representation of queue, Types of queues: Simple queue, circular queue, double ended queue (de-queue) priority queue, operations on all types of Queues. The List ADT: singly linked list implementation, insertion, deletion and searching operations on linear list, circular linked list implementation, Double linked list implementation, insertion, deletion and searching operations. Applications of linked lists.

Preliminaries – Binary Trees – The Search Tree ADT – Binary Search Trees – AVL Trees – Tree Traversals – Hashing – General Idea – Hash Function – Separate Chaining – Open Addressing –Linear Probing – Priority Queues (Heaps) – Model – Simple implementations – Binary Heap

Preliminaries – Insertion Sort, Selection sort – Shell sort – Heap sort – Merge sort – Quicksort – External Sorting

Introduction to Graphs, Definitions –DFS, BFS, Minimum Spanning Tree – Prim’s and Kruskal's Algorithm. Single-Source Shortest Paths – Bellman-Ford algorithm and Dijkstra’s Algorithm – – Applications of Graphs

R2.Classic Data Structures , Debasis Samanta ,2nd Edition, PHI Learning PVT,2011

End Semester Examination 30%

Course Description: Software engineering course provides: Different life cycle models, Requirement dictation process, Analysis modelling and specification, Architectural and detailed design methods, Implementation and testing strategies, Verification and validation techniques, Project planning and management and Use of CASE tools.

Course objectives:  To be aware of Different life cycle models; Requirement dictation process; Analysis modeling and specification; Architectural and detailed design methods; Implementation and testing strategies; Verification and validation techniques; Project planning and management and Use of CASE tools.

Introduction –S/W Engineering Paradigm – life cycle models (waterfall, incremental, spiral, WINWIN spiral, evolutionary, prototyping, object-oriented) - system engineering – computer-based system – verification – validation – life cycle process – development process –system engineering hierarchy.

Functional and non-functional - user – System –requirement engineering process – feasibility studies – requirements – elicitation – validation and management – software prototyping – prototyping in the software process – rapid prototyping techniques – user interface prototyping -S/W document. Agile methods, Extreme Programming, SCRUM.

Design process and concepts – Modular design – design heuristic – design model and document. Architectural design – software architecture – data design – architectural design – transform and transaction mapping – user interface design – user interface design principles-Model representation- Real time systems - Real time software design – system design – real time executives – data acquisition system - monitoring and control system. SCM – Need for SCM – Version control – Introduction to SCM process – Software configuration items.

Taxonomy of software testing – levels – test activities – types of s/w test – black box testing – testing boundary conditions – structural testing – test coverage criteria based on data flow mechanisms – regression testing – testing in the large. S/W testing strategies – strategic approach and issues - unit testing – integration testing – validation testing – system testing and debugging.

Measures and measurements – S/W complexity and science measure – size measure – data and logic structure measure – information flow measure. Software cost estimation – function point models – COCOMO model- Delphi method.- Defining a Task Network – Scheduling – Earned Value Analysis – Error Tracking - Software changes – program evolution dynamics – software maintenance – Architectural evolution. Taxonomy of CASE tools – Agile based Case Study.

R2. Ian Sommerville, “Software engineering,” Pearson education Asia, 9th Edition, 2013.

R3. Pankaj Jalote- “An Integrated Approach to Software Engineering,” Narosa Publishing house, 2011.

R4.James F Peters and Witold Pedryez, “Software Engineering – An Engineering Approach”, John Wiley and Sons, New Delhi, 2010.

R5.Ali Behforooz and Frederick J Hudson, “Software Engineering Fundamentals”, OUP India 2012.

End Semester Exams ESE 50

Total 100

This mandatory course is aimed at providing a comprehensive overview of the different facets of Cyber Security.  In addition, the course will detail into specifics of Cyber Security with Cyber Laws both in Global and Indian Legal environments

Security Fundamentals-4 As Architecture Authentication Authorization Accountability, Social Media, Social Networking and Cyber Security.Cyber Laws, IT Act 2000-IT Act 2008-Laws for Cyber-Security, Comprehensive National Cyber-Security Initiative CNCI – Legalities

Cyber Attack and Cyber Services Computer Virus – Computer Worms – Trojan horse.Vulnerabilities -  Phishing -  Online Attacks – Pharming - Phoarging  –  Cyber Attacks  -  Cyber Threats -  Zombie- stuxnet - Denial of Service Vulnerabilities  - Server Hardening-TCP/IP attack-SYN Flood

Cyber Security Management Risk Management and Assessment - Risk Management Process - Threat Determination Process -Risk Assessment - Risk Management Lifecycle.Security Policy Management - Security Policies - Coverage Matrix Business Continuity Planning - DisasterTypes  -  Disaster Recovery Plan - Business Continuity Planning Process

Vulnerability - Assessment and Tools: Vulnerability Testing - Penetration Testing Black box- white box.Architectural Integration:  Security Zones - Devicesviz Routers, Firewalls, DMZ. Configuration Management - Certification and Accreditation for Cyber-Security.

Authentication and Cryptography: Authentication - Cryptosystems - Certificate Services, Securing Communications:  Securing Services -  Transport  –  Wireless  -  Steganography and NTFS Data Streams. Intrusion Detection and Prevention Systems:   Intrusion -  Defense in Depth  -  IDS/IPS  -IDS/IPS Weakness and Forensic AnalysisCyber Evolution: Cyber Organization – Cyber Future

R2. Thomas R, Justin Peltier, John, “Information Security Fundamentals”, Auerbach Publications.

R3. AtulKahate, “Cryptography and Network Security”,  2^nd Edition, Tata McGrawHill.2003

R4. Nina Godbole, SunitBelapure, “Cyber Security”, Wiley India 1^st Edition 2011

R5. Jennifer L. Bayuk and Jason Healey and Paul Rohmeyer and Marcus Sachs, “Cyber Security Policy Guidebook”, Wiley; 1 edition , 2012

R6. Dan Shoemaker and Wm. Arthur Conklin, “Cyber security: The Essential Body Of Knowledge”,   Delmar Cengage Learning; 1 edition, 2011

R7. Stallings, “Cryptography & Network Security - Principles & Practice”, Prentice Hall, 6th Edition 2014

Maximum Marks : 50

·

To study the fundamentals of digital circuits and concepts used in the analysis and design of various digital systems.

Switching Theory: Laws of Boolean algebra, Theorems of Boolean algebra, Switching functions, Methods for specification of switching functions - Truth tables and Algebraic forms, Realization of functions using logic gates. Digital Logic Elements: Electronic logic gates, Positive and negative logic, Logic families -TTL, ECL and CMOS, Realization of logic gates.

Simplification of Boolean Expressions and Functions: Algebraic methods,     Canonical forms of Boolean functions, Minimization of functions using Karnaugh     maps, Minimization of functions using Quine-McClusky method.

Design of Combinational Logic Circuits: Gate level design of Small Scale     Integration (SSI) circuits, Modular combinational logic elements - Decoders,     Encoders, Priority encoders, Multiplexers and Demultiplexers. Design of Integer     Arithmetic Circuits using Combinational Logic: Integer adders - Ripple carry adder     and Carry look ahead adder, Integer subtractors using adders, Unsigned integer     multipliers - Combinational array circuits, Signed integer multipliers - Booth's     coding, Bit-pair recoding, Carry save addition and Wallace tree multiplier, Signed     integer division circuits - Combinational array circuits, Complexity and propagation     delay analysis of circuits. Design of Combinational Circuits using Programmable     Logic Devices (PLDs): Programmable Read Only Memories (PROMs),     Programmable Logic Arrays (PLAs), Programmable Array Logic (PAL) devices,     Design of multiple output circuits using PLDs.

Sequential Circuit Elements: Latches -RS latch and JK latch, Flip-flops-RS, JK, T     and D flip flops, Master-slave flip flops, Edge-triggered flip-flops. Analysis and     Design of Synchronous Sequential Circuits: Models of sequential circuits - Moore     machine and Mealy machine, Flip-flops - Characteristic table, Characteristic     equation and Excitation table, Analysis of sequential circuits- Flipflop input     expressions, Next state equations, Next state maps, State table and State transition     diagram, Design of sequential circuits - State transition diagram, State table, Next     state maps, Output maps, Expressions for flip-flop inputs and Expressions for circuit     outputs, Modular sequential logic circuits- Shift registers, Registers, Counters and  Random access memories, Design using programmable logic sequencers (PLSs).     Design of Arithmetic Circuits using Sequential Logic : Serial adder for integers,     Unsigned integer multiplier, Unsigned integer division circuits, Signed integer     division, Floating-pint adder/subtractor - Design of control circuit, Floating - point multiplier.

Case study: Learn the Fundamentals of Digital Logic Design with VHDL Informal Laboratory:

·         Design and implementation of binary adder / subtractor using basic gates

·         Design and implementation of applications using multiplexers

·         Design and implementation of Synchronous & Asynchronous Counters

·         Design and implementation of Shift Registers

Coding Combinational Circuits using Hardware Description Language (HDL)

T1 - Donald P Leach, Albert Paul Malvino&GoutamSaha, “Digital Principles and Applications” , Tata McGraw Hill 7^th Edition, 2010.

R2- R D Sudhaker Samuel, “Illustrative Approach to Logic Design. Sanguine-Pearson”, 2010.

R3- Charles H. Roth, “Fundamentals of Logic Design”, Cengage Learning, 5th Edition, 2004.

R4- Ronald J. Tocci, Neal S. Widmer. Gregory L. Moss, “Digital Systems Principles and     Applications, ” 10^th  Edition. Pearson Education, 2007

R5- M Morris Mano, “Digital Logic and Computer Design”, Pearson Education, 10th Edition, 2008.

Assessment of each paper

·         Continuous Internal Assessment (CIA) for Theory papers: 50% (50 marks out

of 100 marks)

·         End Semester Examination(ESE) : 50% (50 marks out of 100 marks)

Components of the CIA

CIA I   :   Mid Semester Examination (Theory)                    : 25 marks                  

CIA II  :  Assignments                                                            : 10 marks

CIA III            : Quizzes/Seminar/Case Studies/Project Work     : 10 marks

Attendance                                                                             : 05 marks

            Total                                                                                         : 50 marks

For subjects having practical as part of the subject

Assessment of Practical paper

Conduct of experiments                                                       : 25 marks

Observations/Lab Record                                                   : 15 marks

Viva voce                                                                                : 10 marks

Total                                                                                        : 50 marks

(All the above assessments are carried for each experiment during regular lab classes and averaged to max 50 marks at the end of the semester)

Course description:

The course Technical Writing consists; Introduction to Technical Communication, Technical Writing, Soft Skills, Professional Presentation Skills and Professional Etiquette. It provides awareness and practice to the learners in all aspects required for effective technical writing. 

Course objective:

This course aims to equip engineering students with effective individual and collaborative technical writing and presentation skills which are necessary to be effective technical communicators in academic and professional contexts.

Communication Process, Flow, Barriers.

Analyzing different kinds of technical documents, Reports/Engineering reports.

Vocabulary for professional writing. Idioms and collocations.

Writing drafts and revising, writing style and language.

Writing Emails, Resumes, Video resume, Interviews, Types of interviews.

Self development process, Personality development, Types of personality, Perception and attitudes, Emotional intelligence, Time Management, Values and beliefs, Personal goal setting, Creativity, Conflict management, Career planning

Writing a speech, Formal presentations, Public speaking, Presentation aids, Group communication, Discussions, Organizational GD, Meetings & Conferences.

Email etiquettes, Telephone Etiquettes, Engineering ethics, Role and responsibility of engineer, Work culture in jobs.

T2: Diane Hacker, Pocket Style Manual, Bedford Publication, New York, 2003. (ISBN 0312406843)

T3: Raman Sharma, Technical Communications, Oxford Publication, London, 2004

R2. Sharma, R. and Mohan, K. Business Correspondence and Report Writing, TMH New Delhi 2002.

R3. Xebec, Presentation Book, TMH New Delhi, 2000. (ISBN 0402213)

W1. Watch Hans Rosling’s presentation on TED Talks: “The best stats you’ve ever seen.” Watch the opening to this presentation.

W2.  Use your search engine and search for “The Brand Called You.” The result you're looking for should be from the Fast Company website

The course is to:

●                 Develop the knowledge of the concepts needed to test the logic of a program.

●                 Create logical knowledge which has applications in Data Structures, Analysis of  Algorithms, Programming languages, Theory of Compilers, Artificial Intelligence and

             Database

●                 Identify structures on discrete levels

●                 Construct relation matrix and graph , define partially ordered set and Boolean algebra

●                 Classify types of error correction in coding and decoding using binary digits

●                 Interpret the concepts and properties of algebraic structures such as semigroups, monoids and groups.

Propositions Logical connectives Compound propositions Conditional and bi conditional propositions Truth tables Tautologies and contradictions Contrapositive Logical equivalences and implications De Morgans Laws - Normal forms Principal conjunctive and disjunctive normal forms Rules of inference Arguments - Validity of arguments.

Predicates, Statement Function , Variables - Free and bound variables , Quantifiers , Universe of discourse,  Logical equivalences and implications for quantified statements , Theory of inference, The rules of universal specification and generalization , Validity of arguments

Basic concepts Notations Subset Algebra of sets The power set Ordered pairs and Cartesian product Relations on sets Types of relations and their properties Matrix and Graph representation of a relation Partial ordering Poset Hasse diagram Lattices and their properties Sublattices Boolean algebra.

Definitions of functions Classification of functions Types of functions - Examples Composition of functions Inverse functions Characteristic function of a set Hashing functions Permutation functions.

Groups - Properties Subgroups - Cosets and Lagranges theorem Normal subgroups Algebraic system with two binary operations Preliminaries of Coding - Hamming Metric - group codes: Basic notions of error correction - Error recovery in group codes.

T1. Trembly J.P and Manohar R, Discrete Mathematical Structures with Applications to Computer Science, Tata McGrawHill Pub.Co. Ltd, New Delhi, 2003. 

T2. Ralph. P. Grimaldi, Discrete and Combinatorial Mathematics: An Applied Introduction, Fifth Edition, Pearson Education Asia,Delhi, 2009.

1.      R1. Bernard Kolman, Robert C. Busby, Sharan Cutler Ross, Discrete Mathematical Structures,  Fourth Indian reprint, Pearson Education Pvt Ltd., New Delhi, 2003.

2.      R2. Kenneth H. Rosen, Discrete Mathematics and its Applications, Fifth Edition, Tata McGraw Hill Pub. Co. Ltd., New Delhi, 2003.

3.      R3. Richard Johnsonbaugh, Discrete Mathematics, Fifth Edition,Pearson Education Asia, New Delhi, 2002.

End Semester Examination(ESE)      : 50% (50 marks out of 100 marks) 

Components of the CIA

CIA I  :  Subject Assignments / Online Tests                  : 10 marks

CIA II :   Mid Semester Examination (Theory)                : 25 marks            

CIAIII:Quiz/Seminar/Case Studies/Project/Innovative Assignments/presentations/publications : 10 marks

Attendance                                                                           : 05 marks

            Total                                                                                       : 50 marks

Mid Semester Examination (MSE) : Theory Papers:

• The MSE is conducted for 50 marks of 2 hours duration.
• Question paper pattern; Five out of Six questions have to be answered. Each  question carries 10 marks

End Semester Examination (ESE):

The ESE is conducted for 100 marks of 3 hours duration.

The syllabus for the theory papers are divided into FIVE units and each unit carries equal Weightage in terms of marks distribution.

Question paper pattern is as follows.

Two full questions with either or choice will be drawn from each unit. Each question carries 20 marks. There could be a maximum of three sub divisions in a question. The emphasis on the questions is to test the objectiveness, analytical skill and application skill of the concept, from a question bank which reviewed and updated every year

The criteria for drawing the questions from the Question Bank are as follows

50 % - Medium Level questions

25 % - Simple level questions

25 % - Complex level questions

Understanding and application of MATLAB and TINKERCAD for biological analysis which would results in better healthcare and any engineer, irrespective of the parent discipline (mechanical, electrical, civil, computer, electronics, etc.,) can use the disciplinary skills toward designing/improving biological systems. This course is designed to convey the essentials of human physiology.

The course will introduce to the students the various fundamental concepts in MATLAB and TINKERCAD for numerical analysis and circuit design using arduino.

1.      To familiarize with Matlab Online and getting used to basic functionalities used in Matlab (arrays, matrices, tables, functions)

2.      To calculate the Body Mass Index (BMI) of a person and determine under what category the person falls under – underweight, normal, overweight

3.      To determine the R peaks in given ECG and to find HRV using Matlab.

4.      To determine the R peaks in given ECG and to find HRV using Matlab.

5.      To determine the R peaks in given ECG and to find HRV using Matlab.

6.      Introduction to Tinkercad and using the various tools available for running a simple program of lighting a LED bulb using Arduino (digital).

7.      To design a driver motor in Tinkercad using Arduino and driver motor

8.      To design a temperature sensor in Tinkercad using Arduino and TMP36

9.      To design and simulate gas sensors using potentiometers, Arduino and servo motors

10.  To design and simulate measuring pulse sensors using photodiodes, IR LED and Arduino

11.  Preparation of biopolymers (polylactic acid) at home using home-based ingredients.

Course objectives:  This course is an overview of different types of operating systems. They also include understanding of the components of an operating system, process management, and knowledge of storage management and the concepts of I/O and file systems is also covered as an introductory level.

Introduction : What operating systems do, Computer System Architecture, Operating System Structure, Operating System Operations, Process Management,  Memory Management, Storage Management, Protection and Security; System Structures: Operating System Services, User Operating System Interface, System Calls, Types of System Calls.

Process Management: Process Concept, Process Scheduling, Operations on Processes, Inter-process Communication; Threads: Overview, Multithreading Models, Thread Libraries; CPU Scheduling: Basic Concepts, Scheduling Criteria, Scheduling Algorithms, Multiple- Processor Scheduling

Process Synchronization: Background, The Critical Section Problem, Peterson’s Solution, Synchronization Hardware, Semaphores, Classical Problems of Synchronization, Monitors, Synchronization Examples

Memory Management: Background, Swapping, Contiguous Memory Allocation, Paging.

Virtual Memory : Background, Demand Paging, Copy on Write, Page Replacement, Allocation of frames, Thrashing, Allocating Kernel Memory

File System Interface: File System: File Concept, Access Methods, Directory Structure, File System Mounting, File Sharing, Protection.

File System Implementation & Mass Storage Structure: Implementing File Systems: File System Structure, File System Implementation, Directory Implementation, Allocation Methods, Free Space Management. Disk structure, Disk Attachment, Disk Scheduling Methods, Disk Management, Swap-Space Management

T1. Abraham Silberschatz, , Peter Baer Galvin and Greg Gagne “Operating System Concepts”, John Wiley & Sons (ASIA) Pvt. Ltd,Ninth Edition ,2013.                                            

T2.  Martina Seidl, Marion Scholz, Christian Huemer and GertiKappel , “UML @ Classroom An Introduction to Object-Oriented Modeling Series: Undergraduate Topics in Computer Science”, Springer, 2015

R1. Harvey M. Deitel, “Operating Systems”, Pearson Education Pvt. Ltd, Third Edition, 2007.                    

R2. Andrew S. Tanenbaum, “Modern Operating Systems”, Prentice Hall of India Pvt.Ltd, 2009.        

R3. William Stallings, “Operating System”, Pearson Education, 2009.                                      

R4. Pramod Chandra P. Bhatt – “An Introduction to Operating Systems, Concepts

End Semester Examination 30%

Software development in business environment has become more sophisticated, the software implementation is becoming increasingly complex and requires the best programming paradigm which helps to eliminate complexity of large projects. Object Oriented Programming (OOP) has become the predominant technique for writing software at present. Many other important software development techniques are based upon the fundamental ideas captured by object-oriented programming. The course also caters to the understanding of event driven programming, generic programming and concurrent programming. By the end of this COURSE, the student should acquire the basic knowledge and skills necessary to implement the concepts of various programming paradigms.

Review of OOP - Objects and classes in Java – defining classes – methods - access specifiers – static members – constructors – finalize method – Arrays – Strings - Packages – JavaDoc comments. 

Inheritance – class hierarchy – polymorphism – dynamic binding – final keyword – abstract classes – the Object class – Reflection – interfaces – object cloning – inner classes.

Graphics programming – Frame – Components – working with 2D shapes – Using color, fonts, and images - Basics of event handling – event handlers – adapter classes – actions – mouse events – AWT event hierarchy – introduction to Swing – Model-View- Controller design pattern – buttons – layout management – Swing Components

Motivation for generic programming – generic classes – generic methods – generic code and virtual machine – inheritance and generics – reflection and generics – exceptions – exception hierarchy – throwing and catching exceptions.

Multi-threaded programming – interrupting threads – thread states – thread properties – thread synchronization – thread-safe Collections – Executors – synchronizers – threads and event-driven programming, Parallel programming –fork, join framework.

2.              Cay S. Horstmann and Gary Cornell, “Core Java: Volume I – undamentals”, Eighth Edition, Sun Microsystems Press, 2008.

2.             Ivan BratikoPROLOG: Programming for Artificial Intelligence, Third Edition, Pearson Publisher, 2002.

3.            Bruce Eckel, “Thinking in Java”, 4th Edition, February 20, 2006.

4.          Doug Rosenberg, Matt Stephens, “Use Case Driven Object Modeling with UML: Theory and Practice (Expert's Voice in UML Modeling)”, January 16, 2013.

• To have an understanding of finite state and pushdown automata.
• To have a knowledge of regular languages and context free languages.
• To know the relation between regular language, context free language and corresponding recognizers
• To study the Turing machine and classes of problems.

Automata - Introduction to formal proof – Additional forms of proof – Inductive proofs –Finite Automata (FA) – Central concepts of Automata Theory, Representation of Automata, Deterministic Finite Automata (DFA) – Non-deterministic Finite Automata (NFA) – Finite Automata with Epsilon transitions. Introduction to automata simulation tools

Regular Expression – FA and Regular Expressions – Proving languages not to be regular – Closure properties of regular languages – Equivalence and minimization of Automata.

Context-Free Grammar (CFG) – LMD, RMD, Parse Trees – Ambiguity in grammars and languages – Definition of the Pushdown automata – Languages of a Pushdown Automata, Designing of a PDA and string acceptance – Equivalence of Pushdown automata and CFG, Non-Deterministic Pushdown Automata.

Simplifications of CFG, Normal forms for CFG – Pumping Lemma for CFL - Closure Properties of CFL – Turing Machines – Definition, Problems, Language accepted, String acceptance, Programming Techniques for TM.

A language that is not Recursively Enumerable (RE) – An undecidable problem that is RE – Undecidable problems about Turing Machine – Post’s Correspondence Problem - The classes P and NP, Linear Bounded Automata - Definition and examples

T1. J.E.Hopcroft, R.Motwani and J.D Ullman, “Introduction to Automata Theory, Languages and Computations”, Pearson Education, 2008.

T2. Peter Linz  “An Introduction to formal languages and automata”, sixth edition, Jones and Bartlett Learning, 2016.

R1. H.R.Lewis and C.H.Papadimitriou, “Elements of The theory of Computation”, Second Edition, Pearson Education/PHI, 2003

R2. J.Martin, “Introduction to Languages and the Theory of Computation”, 3rd Edition, TMH, 2003.

R3. MichealSipser, “Introduction of the Theory and Computation”, Thomson Brokecole, 3rd Edition, 1997

ESE = 50% out of 100

This course will help the students to learn about basic structure of computer system, design of arithmetic and logic unit with the implementation of fixed and floating point numbers. Further, it will give knowledge about design of control unit and pipelined processing concepts. It discusses about various parallel processing architectures, different memory systems and I/O Communication systems

Functional Units – Basic Operational Concepts – Performance – Instructions: Language of the Computer – Operations, Operands – Instruction representation – Logical operations – decision making – MIPS Addressing.

Addition and Subtraction – Multiplication – Division – Floating Point Representation – Floating Point Operations – Subword Parallelism

A Basic MIPS implementation – Building a Datapath – Control Implementation Scheme – Pipelining – Pipelined data path and control – Handling Data Hazards & Control Hazards – Exceptions.

Parallel processing challenges – Flynn‘s classification – SISD, MIMD, SIMD, SPMD, and Vector Architectures - Hardware multithreading – Multi-core processors and other Shared Memory Multiprocessors - Introduction to Graphics Processing Units, Clusters, Warehouse Scale Computers and other Message-Passing Multiprocessors.

Memory Hierarchy - memory technologies – cache memory – measuring and improving cache performance – virtual memory, TLB‘s – Accessing I/O Devices – Interrupts – Direct Memory Access – Bus structure – Bus operation – Arbitration – Interface circuits - USB.

T1. David A. Patterson and John L. Hennessy, “Computer Organization and Design: The Hardware/Software Interface”, Fifth Edition, Morgan Kaufmann / Elsevier, 2014.

T2. Carl Hamacher, ZvonkoVranesic, SafwatZaky and NaraigManjikian, “Computer Organization and Embedded Systems”, Sixth Edition, Tata McGraw Hill, 2012.

R1. William Stallings, “Computer Organization and Architecture – Designing for Performance”, Sixth Edition, Pearson Education, 2003.

R2.  John L. Hennessey and David A. Patterson, “Computer Architecture –A Quantitative Approach”, Fifth Edition, Morgan Kaufmann / Elsevier Publishers,2012.

ESE - 30% out of 100

● Discuss the core concepts Statistical Analytics and Regression

● Apply the basic principles, models, and algorithms for Multiple and Non Linear Regression

● Analyze the structures and algorithms of Convolutional Neural Networks

● Explain notions and theories associated to Convolutional Neural Networks

● Solve problems in Deep Unsupervised Learning

Relationship between attributes using Covariance and Correlation, Relationship between multiple variables: Regression (Linear,

Multivariate) in prediction. Residual Analysis, Identifying significant features, feature reduction using AIC, multi-collinearity,

Non-normality and Heteroscedasticity

Polynomial Regression, Regularization methods, Lasso, Ridge and Elastic nets, Categorical Variables in Regression, Logit function and

interpretation, Types of error measures (ROCR), Logistic Regression in classification

Invariance, stability. Variability models (deformation model, stochastic model). Scattering networks, Group Formalism,

Supervised Learning: classification. Properties of CNN representations: invertibility, stability, invariance.

Covariance/invariance: capsules and related models.

Connections with other models: dictionary learning, LISTA. Other tasks: localization, regression. Embeddings (DrLim), inverse problems, Extensions to non-euclidean domains Dynamical systems: RNNs.

Autoencoders (standard, denoising, contractive, Variational Autoencoders Adversarial Generative Networks, Maximum Entropy Distributions

T2.Sebastian Raschka and Vahid MirjaliliPython Machine Learning: Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow 2, 3rd Edition, Packt, 2019

R2. Jeremy Arkes, Regression Analysis: A Practical Introduction, Routledge, 2019

R3. Aurelien Geron, Hands-On Machine Learning with Scikit-Learn, Keras and Tensor Flow: Concepts, Tools and Techniques to Build Intelligent Systems, Shroff/O'Reilly, 2019

R4. Andreas Muller, Introduction to Machine Learning with Python: A Guide for Data Scientists, Shroff/O'Reilly, 2016

R5. François Chollet, Deep Learning with Python, Manning Publications, 2017

ESE:30

After learning the course for a semester, the student will be aware of the hacking concepts in cyber security for addressing cryptography, data protection, information-network security and detection of attacks. The student would also get a clear idea on some of the cases with their analytical studies in cyber-attacks and hacking in the related fields.

Introduction to ethical hacking, IP addressing, Network routing protocols, network security, network scanning, and vulnerability assessment OpenVAS, Nessus, etc. of computation device (mobile, pc, etc.) and network of the system

Computation system hacking, modes of gathering information, password cracking, penetration testing including backdoor issues, Malware threats and different cyber-related attacks

Introduction to Mobile Hacking, encryption types and attacks, different mobile platforms and corresponding vulnerabilities

Evading firewalls, standard detection systems and frameworks, and other possible ways of detecting attacks

Case studies: various hacking scenarios and their information gathering along with possible solutions.

2.     Weidman, Georgia. Penetration testing: a hands-on introduction to hacking. No Starch Press, 2014.

3.     Dwivedi, Himanshu. Mobile application security. Tata McGraw-Hill Education, 2010

2.     McNab, Chris. Network security assessment: know your network. " O'Reilly Media, Inc.", 2007.

3.     Simpson, Michael T., Kent Backman, and James Corley. Hands-on ethical hacking and network defense. Cengage Learning, 2010

ESE-30

Course objectives:

To Understand big data for business intelligence

To Learn business case studies for big data analytics

To Understand Nosql big data management

To manage Big data without SQL

To understanding map-reduce analytics using Hadoop and related tools 

Introduction to ethical hacking, IP addressing, Network routing protocols, network security, network scanning, and vulnerability assessment OpenVAS, Nessus, etc. of computation device (mobile, pc, etc.) and network of the systemIntroduction to ethical hacking, IP addressing, Network routing protocols, network security, network scanning, and vulnerability assessment OpenVAS, Nessus, etc. of computation device (mobile, pc, etc.) and network of the system

Computation system hacking, modes of gathering information, password cracking, penetration testing including backdoor issues, Malware threats and different cyber-related attacks

Introduction to Mobile Hacking, encryption types and attacks, different mobile platforms and corresponding vulnerabilities

Case studies: various hacking scenarios and their information gathering along with possible solutions.

T2. Eric Sammer, "Hadoop Operations",1^st Edition, O'Reilley, 2012.

R1. VigneshPrajapati, Big data analytics with R and Hadoop, SPD 2013.

R2. E. Capriolo, D. Wampler, and J. Rutherglen, "Programming Hive", O'Reilley, 2012.

R3. Lars George, "HBase: The Definitive Guide", O'Reilley, 2011.

R4. Alan Gates, "Programming Pig", O'Reilley, 2011.

ESE - 30%

To understand the scope and importance of environmental science towards developing a conscious community for environmental issues, both at global and local scale.  

CO2. Explain the necessity of natural resources management (L2, PO1, PO2 and PO7)

CO3.Relate the causes and impacts of environmental pollution (L4, PO1, PO2, and PO3, PO4)

CO4.Relate climate change/global atmospheric changes and adaptation (L4,PO7)

CO5. Appraise the role of technology and institutional mechanisms for environmental protection (L5, PO8)

Environment and Eco systems – Definition, Scope and importance. Components of environment. Concept and Structure of eco systems. Material Cycles – Nitrogen, Carbon, Sulphur, Phosphorous, Oxygen. Energy Flow and classification of Eco systems.   

Classification and importance- Forest, Water, Mineral, Food, Energy. Management of natural resources – challenges and methods. Sustainable development – Goals, Agriculture, Industries

Causes and Impacts – Air pollution, Water pollution, Soil Pollution, Noise Pollution, Marine Pollution, Municipal Solid Wastes, Bio Medical and E-Waste. Solid Waste Management

Global Temperature, Greenhouse effect, global energy balance, Global warming potential, International Panel for Climate Change (IPCC) Emission scenarios, Oceans and climate change. Adaptation methods. Green Climate fund. Climate change related planning- small islands and coastal region. Impact on women, children, youths and marginalized communities

Technology, Modern Tools – GIS and  Remote Sensing,. Institutional Mechanisms - Environmental Acts and Regulations, Role of government, Legal aspects. Role of Nongovernmental Organizations (NGOs) , Environmental Education and Entrepreneurship

T2Asthana and Asthana, “A text Book of Environmental Studies”, S. Chand, New Delhi, Revised Edition, 2010 [Unit: I, II, III and V]

T3Nandini. N, Sunitha. N and Tandon. S, “environmental Studies” , Sapana, Bangalore,  June 2019 [Unit: I, II, III and IV]

T4R Rajagopalan, “Environmental Studies – From Crisis to Cure”, Oxford, Seventh University Press, 2017, [Unit: I, II, III and IV]

R2.Masters, G andEla, W.P (2015), Introduction to environmental Engineering and Science, 3rd Edition. Pearson., New Delhi, 2013.

R3.Raman Sivakumar, “Principals of Environmental Science and Engineering”, Second Edition, Cengage learning Singapore, 2005.

R4.P. Meenakshi, “Elements of Environmental Science and Engineering”, Prentice Hall of India Private Limited, New Delhi, 2006.

R5.S.M. Prakash, “Environmental Studies”, Elite Publishers Mangalore, 2007

R6.ErachBharucha, “Textbook of Environmental Studies”, for UGC, University press, 2005.

R7. Dr. Pratiba Sing, Dr. AnoopSingh and Dr. PiyushMalaviya, “Textbook of Environmental and Ecology”, Acme Learning Pvt. Ltd. New Delhi.

Understand the importance of Values and Ethics in their personal lives and professional careers

Introduction to Professional Ethics : Definition, Nature, Scope- Moral Dilemmas- moral Autonomy-Kohlberg’s theory- Gilligan’s theory, Profession Persuasive, Definitions, Multiple motives, Models of professional goals. Moral Reasoning and Ethical theories – Professional Ideals and Virtues- Theories of Right Action, Self- interest, Customs and Regions- Use of ethical Theories

Engineering as Social Experimentation and Responsibility For Safety Engineering as experimentation- Engineers as responsible experimenters, the challenger case, Codes of Ethics, A balanced outlook on law. Concept of safety and risk, assessment of safety and risk- risk benefit analysis and reducing the risk- three- mile island, Chernobyl and safe exists.

Global Issues and Introduction To Intellectual Property - Multinational corporations- Environmental ethics- Computer ethics and Weapons developments. Meaning and Types of Intellectual Property, Intellectual Property. Law Basics, Agencies responsible for intellectual property registration, International Organizations, Agencies and Treaties, Importance of Intellectual Property Rights.

Foundations of Trademarks - Meaning of Trademarks, Purpose and Functions of Trademarks, types of Marks, Acquisition of Trademark rights, Common Law rights, Categories of Marks, Trade names and Business Name, Protectable Matter, Exclusions from Trademark Protection.

Foundations of Copyrights Law - Meaning of Copyrights, Common Law rights and Rights under the 1976 copyright Act, Recent developments of the Copyright Act, The United States Copyright Office

T2. Govindarajan M, Natarajan S, Senthil Kumar V. S, “Engineering Ethics”, Prentice Hall of India,  New  Delhi, 2004.

R2.  Govindarajan, Natarajan and Senthilkumar “Engineering Ethics”, PHI:009.

R3.  Nagarajan “A Text Book on Professional ethics and Human values”, New Age International, 2009.

R4.  Charles &Fleddermann “Engineering Ethics”, Pearson, 2009.

R5.  Rachana Singh Puri and Arvind Viswanathan, I.K.”Practical Approach to Intellectual Property rights”, International Publishing House, New Delhi. 2010.

R6.  A.B.Rao “Business Ethics and Professional Values”, Excel, 2009

CIA II - Evaluated out of (50) ---> CIA II cnverted to ( 25) 

CIA III - Evaluated out of (20) ----> CIA III cnverted to (10)

Total CIA is scaled down to 20

Att. Marks5

ESE Evaluated out of (50) ---> ESE converted to (25) 

Total marks - 50

1.      At the end of the course, the students would have a fundamental knowledge of the basic probability concepts.

2.      Have a well – founded knowledge of standard distributions which can describe real life phenomena.

3.      Acquire skills in handling situations involving more than one random variable and functions of random variables.

4.      Understand and characterize phenomena which evolve with respect to time in a probabilistic manner.

5.      Be exposed to basic characteristic features of a queuing system and acquire skills in analyzing queuing models.

Axioms of probability - Conditional probability - Total probability – Baye’s theorem Random variable - Probability mass function - Probability density function - Properties – Moments - Moment generating functions and their properties.

Poisson, Geometric, Negative Binomial, Uniform, Exponential, Gamma, Weibull and Normal distributions and their properties - Functions of a random variable.

Joint distributions - Marginal and conditional distributions Covariance– Correlation and regression - Transformation of random variables - Central limit theorem.

Classification - Stationary process - Markov process - Poisson process - Birth and death process - Markov chains - Transition probabilities - Limiting distributions. Transition Diagram.

Markovian models – M/M/1, M/M/C, finite and infinite capacity - M/M/∞ queues - Finite source model - M/G/1 queue (steady state solutions only) – Pollaczek – Khintchine formula – Special cases. Single and Multiple Server System.

T2. Medhi J., “Stochastic Processes”, 3^rd Edition,New Age Publishers, New Delhi, 2009. 

T3. Veerarajan, “Probability, Statistics and Random process”, Third Edition, Tata McGraw Hill, New Delhi,  2009.

R2. Taha, H. A., “Operations Research-An Introduction”, Eighth Edition, Pearson Education Edition Asia, Delhi, 2015.

R3. Gross, D. and Harris, C.M., “Fundamentals of Queuing theory”, John Wiley and Sons, Third Edition, New York, 2008.

·         End Semester Examination(ESE)      : 50% (50 marks out of 100 marks)

Components of the CIA

CIA I   :  Subject Assignments / Online Tests                      : 10 marks

CIA II  :   Mid Semester Examination (Theory)                    : 25 marks                  

CIA III            : Quiz/Seminar/Case Studies/Project/

              Innovative Assignments/presentations/publications       : 10 marks

Attendance                                                                             : 05 marks

            Total                                                                                       : 50 marks

Mid Semester Examination (MSE) : Theory Papers:

• The MSE is conducted for 50 marks of 2 hours duration.
• Question paper pattern; Five out of Six questions have to be answered. Each  question carries 10 marks

End Semester Examination (ESE):

The ESE is conducted for 100 marks of 3 hours duration.

The syllabus for the theory papers are divided into FIVE units and each unit carries equal weightage in terms of marks distribution.

Question paper pattern is as follows.

Two full questions with either or choice will be drawn from each unit. Each question carries 20 marks. There could be a maximum of three sub divisions in a question. The emphasis on the questions is to test the objectiveness, analytical skill and application skill of the concept, from a question bank which reviewed and updated every year

The criteria for drawing the questions from the Question Bank are as follows

50 % - Medium Level questions

25 % - Simple level questions

25 % - Complex level questions

To understand the concepts of data communications.

To study the functions of different layers. To introduce IEEE standards employed in computer networking.

To make the students to get familiarized with different protocols and network components.

To build foundation of Networks in Algorithms and its analysis, Software Engineering Models and Theory of Automata.

Components – Direction of Data flow – networks – Components and Categories – types of Connections – Topologies –Protocols and Standards – ISO / OSI model – Transmission Media – Coaxial Cable – Fiber Optics – Line Coding – Modems – RS232 Interfacing sequences.

Error – detection and correction – Parity – LRC – CRC – Hamming code – low Control and Error control - stop and wait – go back-N ARQ – selective repeat ARQ- sliding window – HDLC. - LAN - Ethernet IEEE 802.3 - IEEE 802.4 - IEEE 802.5 - IEEE 802.11 – FDDI - SONET – Bridges.

Internetworks – Packet Switching and Datagram approach – IP addressing methods – Subnetting – Routing – Distance Vector Routing – Link State Routing – Routers.

Duties of transport layer – Multiplexing – Demultiplexing – Sockets – User Datagram Protocol (UDP) – Transmission Control Protocol (TCP) – Congestion Control – Quality of services (QOS) – Integrated Services.

Domain Name Space (DNS) – SMTP – FTP – HTTP - WWW – Security – Cryptography-Case study.

R2: Larry L. Peterson, Bruce S. Davie, Computer Networks: A Systems Approach Edition: 6th Edition, MK-Morgan Kaufmann/Elsevier-2021. ISBN: 978-0-12-818200-0.

R3: Andrew S. Tanenbaum, Nick Feamster, David J. Wetherall, Computer Networks: 6th Edition, Pearson, 2021, ISBN 9780136764052.

End Semester Examination 30%

Course objectives:

This course provides a strong foundation of fundamental concepts in Artificial Intelligence. To provide a basic exposition to the goals and methods and to enable the student to apply these techniques in applications which involve perception, reasoning and learning.

History - Applications – Components of AI - Intelligent Agents - Characteristics of Intelligent Agents - Agents and Environments - Good behavior – The nature of environments – structure of agents - Problem Solving - problem solving agents – Example problems– Searching for solutions.

Classical Search: Uniformed Search strategies - BFS - DFS- Bidirectional Search-Informed Heuristics Search Strategies -Heuristic function - Greedy - best -first search-A* Algorithm. local search algorithms and optimization problems –Hill-climbing Search, Simulated annealing, Local beam Search, Genetic algorithm -Searching with partial observations - Online Search Agents and Unknown Environment.

Games – Optimal decisions in games –Min-Max algorithm- Alpha – Beta Pruning – imperfect real-time decision –Stochastic Games. 

Constraint Satisfaction Problem (CSP): Definition - Constraint propogation - Backtracking search - Local Search -The Structure of problems.

Logic - Propositional logic - First order logic – Syntax and semantics for first order logic – Using first order logic – Knowledge engineering in first order logic. 

Inference in First order logic – propositional versus first order logic – unification and lifting – forward chaining – backward chaining - Resolution - Knowledge representation - Ontological Engineering - Categories and objects.

Learning from Examples : Forms of Learning - Supervised learning - Learning Decision Trees - Regression and classification with linear models, Artificial Neural Network. 

Knowledge in Learning : Logical formulation of learning – Explanation based learning – Learning using relevant information – Inductive logic programming. Statistical learning- Learning with complete data - Learning with hidden variable.

T1. Stuart Russell and Peter Norvig, “Artificial Intelligence – A Modern Approach”, 4th Edition, Pearson Education, 2020.

T2. Elaine Rich; Kevin Knight; Shivashankar B Nair, “Artificial Intelligence”, 3rd Edition, Tata McGraw-Hill, 2019.

T3. Francois Chollet “Deep Learning with Python”, 1st Edition Manning Publication, 2018.

R1. Jeff Heaton, "Artificial Intelligence for Humans, Volume 1: Fundamental Algorithms",1st edition, CreateSpace Independent Publishing Platform, 2013

R2. George F. Luger, " Artificial Intelligence: Structures and Strategies for Complex Problem Solving", 6th Edition, Pearson Education,2021

R3.Kevin Warwick, " Artificial Intelligence: The Basics", Routledge, 2011.

End Sem Examination- 50%

To introduce basic concepts of algorithms; To introduce mathematical aspects and analysis of algorithms; To introduce sorting and searching algorithms; To introduce various algorithmic techniques; To introduce algorithm design methods.

Introduction, Notion of Algorithm, Fundamentals of Algorithmic Solving, Important Problem Types, Fundamentals of the Analysis Framework, Mathematical Analysis  of Non-recursive Algorithm, Mathematical Analysis of Recursive Algorithm and examples, Empirical Analysis of Algorithms and Algorithm Visualization.

Brute Force and Exhaustive Search: Selection Sort, Bubble Sort, Sequential Search and Brute-force string matching, Travelling Salesman Problem, Knapsack Problem, Assignment Problem. 

Decrease and Conquer: Insertion Sort and Topological Sorting and Fake Coin Problem, Russian Peasant Multiplication, Josephus Problem

Divide and conquer: Merge sort, Quick Sort, Binary Tree Traversals and Related Properties and Multiplication of Large Integers and Strassen’s Matrix Multiplication.

Transform and Conquer: Presorting, Notion of Heap and Heapsort, Horner’s Rule and Binary Exponentiation.

Space and Time Trade - Offs: Sorting by Counting, Horspool’s and Boyer - Moore Algorithm for String Matching, Hashing.

Dynamic Programming: Knapsack Problem, Warshall’s and Floyd’s Algorithm. 

Greedy Techniques: Prim’s Algorithm, Kruskal’s Algorithm, Dijkstra’s Algorithm.

Limitations of Algorithm Power: Decision Trees, P, NP and NP Complete Problems, Challenges in Numerical Algorithms.

Backtracking: n-Queen’s Problem, Hamiltonian Circuit problem and Subset-Sum problem.

Branch and Bound: Assignment problem, Knapsack problem and Traveling salesman problem.

• The students will gain a strong foundation on concept of Computer Graphics.
• The students will learn the various Input and Output graphics devices.
• The students will understand the techniques of 2D and 3D transformations.
• The students will study OpenGL in Java and JOGL and how to create graphics object with JOGL

A survey of Computer Graphics, Video Display Devices, Raster-Scan Systems, Graphics Workstation and Viewing Systems, Input Devices, Hard-Copy Devices, Graphics Networks, Graphics on the Internet.

Line Drawing Algorithms, DDA Algorithms, Bresenham's Line Algorithm, CircleGenerating Algorithms, Midpoint Circle Algorithms, Ellipse Algorithms, Basic TwoDimensional Transformations, Matrix Representation, Three-Dimensional Translation, Three-Dimensional Rotation, Three-Dimensional Scaling, Other Three-Dimensional Transformations - Reflection and Shears.

Java Graphics in 2D, Two-Dimensional Graphics in Java, Transformations and Modeling, Basics of OpenGL and JOGL, Basic OpenGL 2D Programs, Into the Third Dimension, Drawing in 3D, Normal and Textures

Geometry, Vectors, Matrices and Homogeneous Coordinates, Primitives, Polygonal Meshes, Drawing Primitives, Viewing and Projections, Perspective Projection, Orthographic Projection, The Viewing Transform, A Simple Avatar, Viewer Nodes in Scene Graphics

Light and Material, Vision and Color, OpenGL Materials, OpenGL Lighting, Lights and Materials in Scenes, Case Study: Textures, Texture targets, Mipmaps and Filtering, Texture Transformations, Creating Texture with OpenGL, Loading Data into Texture, Texture Coordinate Generation, Texture Objects.

•  Continuous Internal Assessment (CIA) : 50% (50 marks out of 100 marks)
•  End Semester Examination (ESE): 50% (50 marks out of 100 marks)

Explain tools for developing applications in Web programming; Describe scripting languages –Java Script; Under case study: Exposure to a web platform.

 HTML5:

Introduction to HTML5 basic tags, Forms, Multimedia (video, audio) markup and APIs, Canvas, Data Storage, Drag & Drop, Messaging & Workers CSS3:

Understanding basic CSS Syntax and Styles, Understanding Display, Position, and Document Flow, Changing and styling fonts, Adding transitions and animations, Introduction to usage of bootstrap and sass.

Java Script: Introduction, Java script function’s, methods and objects, Decisions and loops, Document Object, Model (DOM), JavaScript Events, Ajax and JSON, API, error handling and debugging, Filtering and Form enhancement, Introduction to Dynamic Web Programming, Implementing jQuery and JavaScript in Web Pages, Building Richly Interactive Web Pages with jQuery, Introducing jQuery UI, Getting started and building Web applications with angular JS.

React js: Introduction, JSX in Depth, Data Flow and Life Cycle Events, Composite and Dynamic Components and Forms, Mixins and the DOM, React on the Server, React Addons, Performance of React Apps, React Router and Data Models, Animation, React Tools, Flux, Redux and React.

 Introduction to Server-Side Development with PHP, What is Server-Side Development, A Web Server’s Responsibilities, Quick Tour of PHP, Program Control, Functions, PHP Arrays and Super globals, Arrays, $_GET and $_POST Super global Arrays, $_SERVER Array, $_Files Array, Reading/Writing Files, PHP Classes and Objects, Object-Oriented Overview, Classes and Objects in PHP, Object Oriented Design, Error Handling and Validation, What are Errors and Exceptions?, PHP Error Reporting, PHP Error and Exception Handling, connectivity to database and processing the form.

The Node Module System, The Node Programming Model, Events and Timers, The Command Line Interface, The File System, Streams, Binary Data, Executing Code, Network Programming, HTTP.

Node JS Database Connectivity, MVC Framework and Architecture, Web Hosting and Content Management System, Usage of Amazon storage for web application.

1.      Bruce Lawson, Remy Sharp, “Introducing HTML 5”, Pearson Education, 2011.

2.      Ian Lunn, “CSS3 Foundations”, Wiley Publishers, 2012.

3.      Jon Duckett, “JavaScript and JQuery: Interactive Front-End Web Development”, Wiley Publishers: 2014.

4.      Sams, “Teach Yourself AngularJS, JavaScript, and jQuery All in One”, Pearson Education ,2015.

5.      Vipul A M, Prathomesh Sonpatki, “React JS by Example-Building Modern Web Application with React”, Packt Publishing,2019.

6.      Colin J. Ihrig, “Pro Node.js for Developers”, APRESS, 2013.

7.   Randy Connolly, Ricardo Hoar, "Fundamentals of Web Development”, 1 stEdition, Pearson Education India. (ISBN:978-9332575271)

1.      Matt West, “HTML5 Foundations”, Wiley Publishers: 2012.

2.      Training Guide Programming in HTML5 with JavaScript and CSS3 (MCSD) (Microsoft Press Training Guide), 2013.

3.      Elizabeth Castro, Bruce Hyslop, “HTML and CSS: Visual QuickStart Guide” 8^th edition, 2013.

4.      Robin Nixon, “Learning PHP, MySQL &JavaScript with jQuery, CSS and HTML5”, 4 thEdition, O’Reilly Publications, 2015. (ISBN:978-9352130153) 2) Luke Welling, Laura Thomson, “PHP and MySQL Web Development”, 5th Edition, Pearson Education, 2016. (ISBN:978-9332582736)

5.      Nicholas C Zakas, “Professional JavaScript for Web Developers”, 3rd Edition, Wrox/Wiley India, 2012. (ISBN:978-8126535088) 4) David Sawyer Mcfarland, “JavaScript & jQuery: The Missing Manual”, 1st Edition, O’Reilly/Shroff Publishers & Distributors Pvt Ltd, 2014 (ISBN:978- 9351108078)

6.       Zak Ruvalcaba Anne Boehm, “Murach's HTML5 and CSS3”, 3rdEdition, Murachs/Shroff Publishers & Distributors Pvt Ltd, 2016. (ISBN:978-9352133246)

Continuous Internal Assessment (CIA) for Theory papers: 50% (50 marks out of 100 marks)

End Semester Examination (ESE): 50% (50 marks out of 100 marks)

Course objectives:

To understand the principles of encryption algorithms; conventional and public key cryptography.

To have a detailed knowledge about authentication, hash functions and Network & application-level security

mechanisms.

OSI Security Architecture, Classical Encryption techniques, Cipher Principles, DES, Crypto analysis of DES, AES, Block Cipher Design Principles and Modes of Operation, Triple DES, Placement of Encryption Function, Traffic Confidentiality.

Introduction to Number theory, Deffie Hellman Key Exchange, Key Management, Elliptic curve Cryptography, Confidentiality using Symmetric Encryption, Public Key Cryptography and RSA.

Authentication Requirements, Authentication Functions, Message Authentication Codes, Hash Functions, MD5, SHA, RIPEMD and HMAC Standards

Authentication Applications: Kerberos – X.509 Authentication Service – Electronic Mail Security – PGP – S/MIME - IP Security – Web Security.