Course Outcome






At the end of course students will be able to –

3 KS01/3IT01/3KE01
Engineering Mathematics-III

◘. Demonstrate the knowledge of differential equations and linear differential equations.
◘. Apply Laplace transform to solve differential equations.
◘. Demonstrate the use of Fourier Transform to connect the time domain and frequency domain.
◘. Demonstrate the basic concepts of probability and statistics.
◘. Apply the knowledge of Complex Analysis.
◘. Apply the knowledge of vector calculus to solve physical problems.

3KS02 Discrete Structure And Graph Theory

◘. Analyze and express logic sentence in terms of predicates, quantifiers, and logical connectives.

◘. Derive the solution for a given problem using deductive logic and prove the solution based on logical inference.

◘. Classify algebraic structure for a given mathematical problem.

◘. Perform combinatorial analysis to solve counting problems.

◘. Develop the given problem as graph net works and solve with techniques of graph theory

3KS03 Object Oriented Programming

◘. Apply Object Oriented approach to design software.
◘. Implement programs using classes and objects.
◘. Specify the forms of inheritance and use them in programs.
◘. Analyze polymorphic behavior of objects.
◘. Design and develop GUI programs.

◘. Develop Applets for web applications

3KS04/3KE04 Data Structures

◘. Apply various linear and nonlinear data structures
◘. Demonstrate operations like insertion, deletion, searching and traversing on various data structures
◘. Examine the usage of various structures in approaching the problem solution.
◘. Choose appropriate data structure for specified problem domain

3KS05 Analog& Digital Electronics

◘. Explain basic concepts of semiconductor devices and its application.

◘. Compare different Number System and basics of conversion of number systems.

◘. Realize different minimization technique to obtain minimized expression.

◘. Design Combinational Circuits.

◘. Design and Develop Sequential Circuits


At the end of course students will be able to –

4KS01 Artificial Intelligence

◘. Explain concepts of Artificial Intelligence and different types of intelligent agents and their architecture.
◘. Formulate problems as state space search problem & efficiently solve them.
◘. Summarize the various searching techniques, constraint satisfaction problem and example problems – game playing techniques.
◘. Apply AI techniques in applications which involve perception, reasoning and learning.
◘. Compare the importance of knowledge, types of knowledge, issues related to knowledge acquisition and representation

4KS02 Data Communication And Networking

◘. Describe data communication Components, Networks, Protocols and various topology based network architecture
◘. Design and Test different encoding and modulating techniques to change digital –to- digital conversion, analog-to-digital conversion, digital to analog conversion, analog to analog conversion,

◘. Explain the various multiplexing methods and evaluate the different error detection & correction techniques.
◘. Illustrate and realize the data link control and data link protocols.
◘. Describe and demonstrate the various Local area networks and the IEEE standards.

4KS03 Operating System

◘. Explain memory management issues like external fragmentation, internal fragmentation.

◘. Illustrate multithreading and its significance.

◘. List various protection and security mechanisms of OS.

◘. Analyze and solve the scheduling algorithms.

◘. Analyze the deadlock situation and resolve it.

◘. Compare various types of operating systems

4KS04 Microprocessor & Assembly Language Programming

◘. Describe microprocessor and its architecture; also understand instruction processing during the fetch-decode-execute cycle.

◘. Design and Test assembly language programs using ◘0◘◘ microprocessor instruction set.

◘. Demonstrate the implementation of standard programming constructs, including control structures and functions, in assembly language.

◘. Illustrate and realize the Interfacing of memory & various I/O devices with microprocessor.

◘. Explain the basic concepts of Internet of Things

4KS05 Theory Of Computation

◘. To construct finite state machines to solve problems in computing.

◘. To write regular expressions for the formal languages.

◘. To construct and apply well defined rules for parsing techniques in compiler

◘. To construct and analyze Push Down, Turing Machine for formal languages

◘. To express the understanding of the Chomsky Hierarchy.

◘. To express the understanding of the decidability and un-decidability problems.


At the end of course students will be able to –

5KS01 Database Management Systems

◘. Model, design and normalize databases for real life applications.

◘. Discuss data models, conceptualize and depict a database system using ER diagram.

◘. Query Database applications using Query Languages like SQL.

◘. Design & develop transaction processing approach for relational databases.

◘. Understand validation framework like integrity constraints, triggers and assertions.

5KS02 Compiler Design

◘. Describe the fundamentals of compiler and various phases of compilers.

◘. Design and implement LL and LR parsers

◘. Solve the various parsing techniques like SLR, CLR, LALR.

◘. Examine the concept of Syntax-Directed Definition and translation.

◘. Assess the concept of Intermediate-Code Generation and run-time environment

◘. Explain the concept code generation and code optimization

5KS03 Computer Architecture & Organization

◘. Discuss basic structure of computer.

◘. Understand the basic operation of CPU.

◘. Compare and select various Memory and I/O devices as per requirement.

◘. Solve the concepts of number representation and their operation.

◘. Explain the concept of parallel processing and pipelining.

5KS04: PE(I)

(i) Cognitive Technologies

◘. Describe the Cognitive computing and principles of cognitive systems.

◘. Identify role of Natural Language Processing in cognitive system.

◘. Outline application of advanced analytics in cognitive computing.

◘. Justify role of Cloud and Distributed Computing in Cognitive Computing.

◘. Assess the process of building a Cognitive Application.

◘. Identify the Emerging Areas and Future Applications of Cognitive Computing.

5KS04: PE(I)

Data Science And Statistics

◘. Demonstrate proficiency with statistical analysis of data.

◘. Build skills in transformation and merging of data for use in analytic tools.

◘. Perform linear and multiple linear regression analysis.

◘. Develop the ability to build and assess data-based models.

◘. Evaluate outcomes and make decisions based on data.

5KS04: PE(I)

Internet Of Things

◘. Understand the basics of IoT

◘. Understand design methodology and platforms involved in IoT

◘. Apply the knowledge to interface various sensors with IoT development

◘. Design and Implement IoT system for real time application

5KS04: PE(I)

Introduction To Cyber Security

◘. Know fundamentals of Cybercrimes and Cyber offenses

◘. Realize the Cyber threats, attacks and Vulnerabilities.

◘. Explore the industry practices and tools.

◘. Comprehend the Access Control and Authentication Process.

◘. Implement Intrusion Detection and Prevention.

5KS05 Open Elect. I

(i) Principles Of Marketing For Engineering

◘. Identify the importance of the digital marketing for marketing success,

◘. Manage customer relationships across all digital channels and build better customer relationships,

◘. Create a digital marketing plan, starting from the SWOT analysis and defining a target group,

◘. Identify digital channels, their advantages and limitations, to perceiving ways of their integration taking into consideration the available budget

5KS05 Open Elect. I

(ii) Fundamentals Of Finance & Accounting

◘. Define bookkeeping and accounting
◘. Explain the general purposes and functions of accounting
◘. Explain the differences between management and financial accounting
◘. Describe the main elements of financial accounting information – assets, liabilities, revenue and expenses
◘. Identify the main financial statements and their purposes.

5KS05 Open Elect. I

(iii) Entrepreneurship

◘. Analyse the business environment in order to identify business opportunities,
◘. Identify the elements of success of entrepreneurial ventures,
◘. Evaluate the effectiveness of different entrepreneurial strategies,
◘. Specify the basic performance indicators of entrepreneurial activity,
◘. Explain the importance of marketing and management in small businesses venture,
◘. Interpret their own business plan


At the end of course students will be able to –

6KS01 Security Policy & Governance

◘. List and discuss the key characteristics of Information Security, Leadership and Management
◘. Differentiate between Law and Ethics
◘. Describe why ethical codes of conduct are important to Information Security
◘. Discuss the importance, benefits and desired outcomes of Information Security Governance ◘. Discuss the process of developing, implementing and maintaining various types of Information Security Policies.
◘. Define Risk Management and its role in the organization.

6KS02 Design And Analysis Of Algorithms

◘. Carry out the analysis of various Algorithms for mainly Time complexity.
◘. Apply design principles and concepts to algorithm design.
◘. Understand different algorithmic design strategies.
◘. Analyze the efficiency of algorithms using time complexity.
◘. Apply the standard sorting algorithms.

6KS04: PE(II)

Natural Language Processing

On completion of the course, student will be able to–
◘. Understand how to tag a given text with basic Language features
◘. Design an innovative application using NLP components
◘. Implement a rule-based system to tackle morphology/syntax of a language
◘. Design a tag set to be used for statistical processing for real-time applications
◘. Compare and contrast the use of different statistical approaches for different types of NLP applications.

6KS04: PE(II)

Big Data Analytics

◘. Work with big data tools and its analysis techniques.

◘. Analyze data by utilizing clustering and classification algorithms.

◘. Learn and apply different algorithms and recommendation systems for large volumes of data.

◘. Perform analytics on data streams.

◘. Learn NoSQL databases and management.

6KS04: PE(II)

Sensors And Actuators

◘. Fabricate some of those sensors

◘. Simulate sensors and characterize before fabricating it

◘. Design application with sensors and actuators for real world

6KS04: PE(II)


◘. Classify the symmetric encryption techniques

◘. Illustrate various public key cryptographic techniques

◘. Evaluate the authentication and hash algorithms.

◘. Discuss authentication applications

◘. Summarize the intrusion detection and its solutions to overcome the attacks.

◘. Understand basic concepts of system level security

6KS05 Open Elect. II

Computational Biology

◘. Understand what types of biological questions can be investigated using computers, and what limitations computational methods impose on the understanding of biology.

◘. Describe the properties of DNA, RNA, and proteins, the relationships among these molecules.

◘. Analyze how to convert a biological question into a computational problem that can be solved using computers.

◘. Explain general approaches for solving computational problems, and will be able to apply these approaches to new problems you encounter.

◘. Understand how implement the algorithms by writing computer programs.

6KS05 Open Elect. II

Cyber Laws & Ethics

◘. Understand Cyber Space, Cyber Crime, Information Technology,Internet& Services.

◘. List and discuss various forms of Cyber Crimes

◘. Explain Computer and Cyber Crimes

◘. Understand Cyber Crime at Global and Indian Perspective.

◘. Describe the ways of precaution and prevention of Cyber Crime as well as Human Rights.

6KS05 Open Elect. II

Intellectual Property Rights

◘. Demonstrate a breadth of knowledge in Intellectual property.

◘. Assess fundamental aspects of Intellectual Property Rights.

◘. Discuss Patents, Searching, filling and drafting of Patents

◘. Discuss the basic principles of geographical indication, industrial designs, and copyright.

◘. Explain of Trade Mark and Trade Secret.

◘. Investigate current trends in IPR and Government initiatives in fostering IPR.


At the end of course students will be able to –

7KS01 / 7KE01 Social Sciences And Engineering Economics

◘. An ability to understand the importance of social science and economics in professional life.

◘. An ability to utilize high-level interpersonal skills to negotiate with stakeholders and maintain cordial relationships with them reflecting the professional ethics and responsibilities.

◘. Understanding of professional responsibility with socioeconomic constraints and norms

◘. An ability to understand the need of society and design the system to fulfill it with deep analysis.

◘. An ability to understand the social science and engage in a lifelong learning process performing better in the group as well as individually.

7KS02 Computer Graphics

◘. Describe the basic concepts of Computer Graphics.

◘. Demonstrate various algorithms for basic graphics primitives.

◘. Apply 2-D geometric transformations on graphical objects.

◘. Use various Clipping algorithms on graphical objects

◘. Explore 2-D geometric transformations, curve representation techniques and projections methods

◘. Explain visible surface detection techniques and Animation

7KS03 Cloud Computing

◘. Describe the fundamental concept, architecture and applications of Cloud Computing.

◘. Discuss the problems related to cloud deployment model.

◘. Examine the concept of virtualization.

◘. Identify the role of network connectivity in the cloud.

◘. Assess different Cloud service providers.

◘. Inspect the security issues in cloud service models.

7KS04: PE(III)


◘. Describe basic concept of robotics.

◘. Explain Components of a Robot System & Mechanical Systems

◘. Illustrate Control of Actuators in Robotic Mechanisms

◘. Compare and contrast Robotic Sensory Devices

◘. Recommend Robotics Hardware & Software Considerations in Computer Vision

◘. Design Robotic system by taking real time considerations.

7KS04: PE(III)

Data Warehouse And Mining

◘. Explain the basics of data mining techniques.

◘. Identify the similarity and dissimilarity between the data sets.

◘. Apply Data Preprocessing to techniques.

◘. Describe Data Warehouse fundamentals, Data Mining Principles.

◘. Illustrate Multidimensional Data Analysis in Cube Space

◘. Assess Mining Frequent Patterns, Associations, and Correlations

7KS04: PE(III)

Embedded System

◘. Describe the basics of embedded systems and structural core units as well as memory organization for embedded system.

◘. Explain components of embedded system, characteristics and quality attributes of embedded systems.

◘. Discuss role of ◘0◘◘ microcontroller and its architecture in design of embedded systems

◘. Examine the different Addressing modes and Instruction Set of 5032 microcontrollers.

◘. Use knowledge of C programming to do embedded programming.

◘. Assess the Real-Time Operating System concepts with VxWorks RTOS.

7KS04: PE(III)

Digital Forensics

◘. Describe Digital Forensics and its related preparation

◘. Outline Data Acquisition tools

◘. Use knowledgeto improve crime investigations.

◘. Examine Digital Forensic and its validation

◘. Assess role of email and social media in investigations

◘. Discuss Cloud Forensics

7KS05: P.E.- (IV)

Block Chain Fundamentals

◘. Describe Crypto currency as application of block chain technology

◘. Examine Basic Cryptographic primitives used in Block chain

◘. Illustrate Consensus in a Blockchain

◘. Discuss empirical study oofbitcoin the mining

◘. Compare and contrast Ethereum and Bitcoin

◘. Use concepts of Block chain technology that are commonly used across multiple industries to solve large scale problems

7KS05: P.E.- (IV)

Image Processing

◘. Explain fundamental steps in Image Processing

◘. Compare different methods for image transform with its properties

◘. Illustrate Image Enhancement in spatial domain

◘. Examine Image Enhancement in Frequency Domain

◘. Apply various methods for segmenting image and identifying image components

◘. Investigate morphological operations to improve the quality of image.

7KS05: P.E.- (IV)

Optimization Techniques

◘. Describe statement of an optimization problem

◘. Examine linear programming procedures to solve optimization problems.

◘. Compare different nonlinear programming methods of optimization

◘. Discuss Geometric Programming with different constraint

◘. Identify the appropriate optimization technique for the given problem

◘. Synthesize algorithms to solve real time optimization problems.


At the end of course students will be able to –

8KS01 Object Oriented Analysis And Design

◘. Describe Object Oriented principles, for performing object-oriented analysis and design.

◘. Explain the basic concepts of UML, Software Development Processes and Design pattern.

◘. Illustrate requirements for developing software.

◘. Create initial domain model & system sequence diagram for use case scenario.

◘. Design static and dynamic objects for modeling.

◘. Construct UML and Design Patterns for developing object-oriented software.

8KS02 Professional Ethics And Management

◘. Relate ethical and non-ethical situations

◘. Outline ethics in the society & environment

◘. Examine the moral judgment & correlate the concepts in addressing the ethical dilemmas

◘. Identify risk and safety measures in various engineering fields

◘. Justify ethical issues related to engineering responsibilities and rights

◘. Synthesize cognitive skills in solving social problems

8KS03: P.E.- (V)

Virtual And Augmented Reality

◘. Describe Virtual reality & its applications.

◘. Discuss virtual reality world and types.

◘. Examine geometry of virtual world and the physiology of human vision

◘. Investigate Visual Perception, Motion and Tracking

◘. Inspect Physics of Sound and the Physiology of Human Hearing.

◘. Explain Augmented reality & examples based on Augmented reality

8KS03: P.E.- (V)

Machine Learning And AI

◘. Describe Machine learning and its types.

◘. Discuss Bayesian Decision Theory and Parametric Methods

◘. Illustrate Multivariate and Dimensionality Reduction methods.

◘. Categorize Non-Parametric methods

◘. Justify discrimination techniques in Machine learning

◘. Synthesize Neural network using Multilayer Perceptron

8KS03: P.E.- (V)

Wireless Sensor Networks

◘. Describe Network of Wireless Sensor Nodes

◘. Explain Node Architecture and Physical Layer.

◘. Discuss Medium Access Control and its related properties.

◘. Analyze the protocols and algorithms used at different network protocollayers in sensor systems.

◘. Compare different power management techniques and clocks and the Synchronization problems.

◘. Explain time synchronization and its problems.

8KS03: P.E.- (V)

System & Software Security

◘. Relate malicious and non-malicious attacks.

◘. Outline web common vulnerabilities, attack mechanisms and methods against computer and information systems.

◘. Apply relevant methods for security modeling and analysis of Operating System.

◘. Investigate a secure network by monitoring and analyzing the nature of attacks.

◘. Explain cryptography, intrusion detection and firewall system

◘. Implement different security solutions at various levels such as operating systems, databases and clouds

8KS04: P.E.- (VI)

Distributed Ledger Technology

§ To develop an understanding of the requirements for electronic payment systems

§ To understand key cryptographic constructs, economic incentive mechanisms and distributed algorithms underpinning crypto currencies such as Bitcoin and Ethereum

§ To develop a basic facility with programming smart contracts on one crypto currency platform

8KS04: P.E.- (VI)

Multimedia Computing

◘. Describe technical aspect of Multimedia Computing.

◘. Compare various file formats for audio, video and text media.

◘. Examine lossless data compression techniques in real time.

◘. Illustrate lossy data compression techniques in real time scenario

◘. Investigate video compression technique ◘. Construct various networking protocols for multimedia applications.

8KS04: P.E.- (VI)

Modelling& Simulation

◘. Describe System models & system modelling.

◘. Explain continuous system methods of obtaining solutions.

◘. Illustrate the need of simulation and mathematical modeling

◘. Examine simulation of Queuing System and PERT network.

◘. Inspect experimentation of Simulation.

◘. List different special purpose languages use for continuous and discrete systems