Department Of Master of Computer Applications
The PEOs are reviewed periodically based on feedback of the programme’s various stakeholders. For this purpose, there should be in place a process to identify and document relationships with stakeholders (including students) and their needs, which have to be adequately addressed when reviewing the programme curriculum and processes. Justification shall be provided as to how the composition of programme curriculum contributes towards attainment of the PEOs defined for the programme. Also, it is expected to expound how the administrative system helps the programme in ensuring the attainment of the PEOs. There should be enough evidence and documentation to show the achievement of the PEOs set by the institution with the help of the assessment (indicate tools and how they are used) and evaluation process that have been developed. Also, show that this continuous process leads to the revision or refinement of the PEOs. The institute shall provide the required information for assessment, evaluation and review methods to evaluate the attainment of the PEOs as per the format given in the SAR. If the institute wishes to provide additional information, it will include that information in a suitable format wherever necessary.
Programme Outcomes
Graduates Attributes (GAs) form a set of individually assessable outcomes that are the components indicative of the graduate’s potential to acquire competence to practice at the appropriate level. The GAs are examples of the attributes expected of a graduate from an accredited programme. The computing professional Graduate Attributes of the NBA are as following:
1.Computational Knowledge:
Apply knowledge of computing fundamentals, computing specialisation, mathematics, and domain knowledge appropriate for the computing specialisation to the abstraction and conceptualisation of computing models from defined problems and requirements.
2.Problem Analysis:
Identify, formulate, research literature, and solve complex computing problems reaching substantiated conclusions using fundamental principles of mathematics, computing sciences, and relevant domain disciplines.
3.Design /Development of Solutions:
Design and evaluate solutions for complex computing problems, and design and evaluate systems, components, or processes that meet specified needs with appropriate consideration for public health and safety, cultural, societal, and environmental considerations.
4,Conduct investigations of complex Computing problems:
Use research-based knowledge and research methods including design of experiments, analysis and interpretation of data, and synthesis of the information to provide valid conclusions.
5.Modern Tool Usage:
Create, select, adapt and apply appropriate techniques, resources, and modern computing tools to complex computing activities, with an understanding of the limitations.
6.Professionl Ethics:
Understand and commit to professional ethics and cyber regulations, responsibilities, and norms of professional computing practices.
7.Life-long Learning:
Recognise the need, and have the ability, to engage in independent learning for continual development as a computing professional.
8.Project management and finance:
Demonstrate knowledge and understanding of t h e c o m p u t i n g and management principles and apply these to one’s own work, as a member and leader in a team, to manage projects and in multidisciplinary environments.
9.Communication Efficacy:
Communicate effectively with the computing community, and with society at large, about complex computing activities by being able to comprehend and write effective reports, design documentation, make effective presentations, and give and understand clear instructions.
10.Societal and Environmental Concern:
Understand and assess societal, environmental, health, safety, legal, and cultural issues within local and global contexts, and the consequential responsibilities relevant to professional computing practices.
11.Individual and Team Work:
Function effectively as an individual and as a member or leader in diverse teams and in multidisciplinary environments.
12.Innovation and Entrepreneurship
Identify a timely opportunity and using innovation to pursue that opportunity to create value and wealth for the betterment of the individual and society at large.
The POs formulated for an MCA programme by the institute must be consistent with the NBA’s Graduate Attributes of computing professionals. The POs must foster t h e attainment of the PEOs.
The programme shall indicate the process involved in defining and redefining the POs. It shall also provide how and where the POs are published and disseminated. It should also describe the process that periodically documents and demonstrates that the POs are based on the needs of the stakeholders of the programme. The extent to which and how the POs are aligned with the Graduate Attributes of computing professionals prescribed by the NBA shall be provided. The correlation between the POs and the PEOs is to be provided as per the format given in the SAR in order to establish the contribution of the POs towards the attainment of the PEOs.
PROGRAM SPECIFIC OUTCOMES (PSOs) :
PSO 1. Able to select suitable data models, appropriate architecture, and platform to implement a system with good performance.
PSO 2. Able to design and integrate various system based components to provide user interactive solutions for various challenges.
PSO 3. Able to develop applications for real time environments using existing and upcoming Technologies.
Regulation 2021 (2 Years)
PROGRAMME EDUCATIONAL OBJECTIVES (PEOs)
PEO 1: Apply their computing skills to analyse, design and develop innovative software products to meet the industry needs and excel as software professionals.
PEO 2: Pursue lifelong learning and do research in the computing field based on solid technical foundations.
PEO 3: Communicate and function effectively in teams in multidisciplinary fields within the global, societal and environmental context.
PEO 4: Exhibit professional integrity, ethics and an understanding of responsibility to contribute technical solutions for the sustainable development of society.
PROGRAM OUTCOMES (POS):
PO 1: An ability to independently carry out research/investigation and development work to solve practical problems
PO 2: An ability to write and present a substantial technical report/document
PO 3: Students should be able to demonstrate a degree of mastery over the area as per the specialization of the program. The mastery should be at a level higher than the requirements in the appropriate bachelor program
PO 4: Able to select suitable data models, appropriate architecture, and platform to implement a system with good performance.
PO 5: Able to design and integrate various system based components to provide user interactive solutions for various challenges.
PO 6: Able to develop applications for real time environments using existing and upcoming technologies.
SEMESTER – I
C101 – APPLIED PROBABILITY AND STATISTICS FOR COMPUTER SCIENCE ENGINEERS (MA4151)
| C101.1 | apply the concepts of Linear Algebra to solve practical problems. |
| C101.2 | use the ideas of probability and random variables in solving engineering problems. |
| C101.3 | be familiar with some of the commonly encountered two dimension random variables and be equipped for a possible extension to multivariate analysis. |
| C101.4 | use statistical tests in testing hypothesis on data. |
| C101.5 | develop critical thinking based on empirical evidence and the scientific approach to knowledge development. |
C102 – ADVANCED DATA STRUCTURES AND ALGORITHMS(MC4101)
| C102.1 | Design data structures and algorithms to solve computing problems. |
| C102.2 | Choose and implement efficient data structures and apply them to solve problems. |
| C102.3 | Design algorithms using graph structure and various string-matching algorithms to solve real-life problems. |
| C102.4 | Design one’s own algorithm for an unknown problem. |
| C102.5 | Apply suitable design strategy for problem solving. |
C103 – OBJECT ORIENTED SOFTWARE ENGINEERING(MC4102)
| C103.1 | Design object oriented software using appropriate process models. |
| C103.2 | Differentiate software processes under waterfall and agile methodology. |
| C103.3 | Design and Develop UML diagrams for software projects. |
| C103.4 | Apply Design Patterns for a software process. |
| C103.5 | Categorize testing methods and compare different testing tools for software processes. |
| C103.6 | Analyze object oriented metrics and quality for software engineering processes. |
C104 – PYTHON PROGRAMMING(MC4103)
| C104.1 | Develop algorithmic solutions to simple computational problems |
| C104.2 | Represent compound data using Python lists, tuples and dictionaries. |
| C104.3 | Read and write data from/to files in Python Programs |
| C104.4 | Structure simple Python programs using libraries, modules etc. |
| C104.5 | Structure a program by bundling related properties and behaviors into individual objects. |
C105 – FUNDAMENTALS OF ACCOUNTING(MC4104)
| C105.1 | Able to understand the basic concepts of Accounting standards. |
| C105.2 | Able to understand the process of maintaining Accounts in an organization |
| C105.3 | Helps to understand and calculating the financial position of an organization |
| C105.4 | Helps to understand Financial Management concepts and its components |
| C105.5 | It helps to understand the importance of BRS and generation of various financial reports |
C106 – ADVANCED DATA STRUCTURES AND ALGORITHMS LABORATORY(MC4111)
| C106.1 | Design and implement basic and advanced data structures extensively |
| C106.2 | Design algorithms using graph structures |
| C106.3 | Design and develop efficient algorithms with minimum complexity using design techniques |
| C106.4 | Develop programs using various algorithms. |
| C106.5 | Choose appropriate data structures and algorithms, understand the ADT/libraries, and use it to design algorithms for a specific problem |
C107 – PYTHON PROGRAMMING LABORATORY(MC4112)
| C107.1 | Apply the Python language syntax including control statements, loops and functions to solve a wide variety of problems in mathematics and science. |
| C107.2 | Use the core data structures like lists, dictionaries, tuples and sets in Python to store, process and sort the data |
| C107.3 | Create files and perform read and write operations |
| C107.4 | Illustrate the application of python libraries |
| C107.5 | Handle exceptions and create classes and objects for any real time applications |
C108 – COMMUNICATION SKILLS ENHANCEMENT – I(MC4113)
| C108.1 | Listen and comprehend lectures in English |
| C108.2 | Articulate well and give presentations clearly |
| C108.3 | Participate in Group Discussions successfully |
| C108.4 | Communicate effectively in formal and informal writing |
| C108.5 | Write proficient essays and emails |
SEMESTER – II
C109 – FULL STACK WEB DEVELOPMENT(MC4201)
| C109.1 | Write client side scripting HTML, CSS and JS. |
| C109.2 | Implement and architect the server side of the web application. |
| C109.3 | Implement Web Application using NodeJS. |
| C109.4 | Architect NoSQL databases with MongoDB. |
| C109.5 | Implement a full-stack Single Page Application using React, NodeJS and MongoDB and deploy on Cloud. |
C110 – ADVANCED DATABASE TECHNOLOGY(MC4202)
| C110.1 | Design a distributed database system and execute distributed queries. |
| C110.2 | Manage Spatial and Temporal Database systems and implement it in corresponding applications. |
| C110.3 | Use NoSQL database systems and manipulate the data associated with it. |
| C110.4 | Design XML database systems and validate with XML schema. |
| C110.5 | Apply knowledge of information retrieval concepts on web databases. |
C111 – CLOUD COMPUTING TECHNOLOGIES(MC4203)
| C111.1 | Use Distributed systems in Cloud Environment. |
| C111.2 | Articulate the main concepts, key technologies, strengths and limitations of Cloud computing. |
| C111.3 | Identify the Architecture, Infrastructure and delivery models of Cloud computing. |
| C111.4 | Install, choose and use the appropriate current technology for the implementation of Cloud. |
| C111.5 | Adopt Microservices and DevOps in Cloud environments. |
C112 – MOBILE APPLICATION DEVELOPMENT(MC4204)
| C112.1 | Understand the basics of mobile application development frameworks and tools. |
| C112.2 | Develop a UI for mobile applications. |
| C112.3 | Design mobile applications that manage memory dynamically. |
| C112.4 | Build applications based on mobile OS like Android, iOs. |
| C112.5 | Build location based services. |
C113-CYBER SECURITY(MC4205)
| C113.1 | Develop a set of risk and security requirements to ensure that there are no gaps in an organization’s security practices. |
| C113.2 | Achieve management, operational and technical means for effective cyber security. |
| C113.3 | Audit and monitor the performance of cyber security controls. |
| C113.4 | Spot gaps in the system and devise improvements. |
| C113.5 | Identify and report vulnerabilities in the system |
C114 – ADVANCED DATABASE TECHNOLOGY LABORATORY(MC4211)
| C114.1 | Design and implement advanced databases. |
| C114.2 | Use big data frameworks and tools |
| C114.3 | Formulate complex queries using SQL. |
| C114.4 | Create an XML document and perform Xquery |
| C114.5 | Query processing in Mobile databases using open source tools. |
C115 – FULL STACK WEB DEVELOPMENT LABORATORY(MC4212)
| C115.1 | To implement and deploy the client side of the web application |
| C115.2 | To develop and deploy server side applications using NodeJS. |
| C115.3 | To use Express framework in web development |
| C115.4 | To implement and architect database systems in both NoSQL and SQL environments. |
| C115.5 | To develop a full stack single page application using React, NodeJS, and a Database and deploy using containers. |
C116 – COMMUNICATION SKILLS ENHANCEMENT – II(MC4213)
| C116.1 | Students will be able to make presentations and participate in Group discussions withconfidence. |
| C116.2 | Students will be able to perform well in the interviews. |
| C116.3 | Students will make effective presentations. |
SEMESTER – III
C201 – MACHINE LEARNING(MC4301)
| C201.1 | Understand about Data Preprocessing, Dimensionality reduction |
| C201.2 | Apply proper model for the given problem and use feature engineering techniques |
| C201.3 | Make use of Probability Technique to solve the given problem. |
| C201.4 | Analyze the working model and features of Decision tree |
| C201.5 | choose and apply appropriate algorithm to learn and classify the data |
C202 – INTERNET OF THINGS(MC4302)
| C202.1 | Define the infrastructure for supporting IoT deployments |
| C202.2 | Understand the usage of IoT protocols for communication between various IoT devices |
| C202.3 | Design portable IoT using Arduino/Raspberry Pi /equivalent boards. |
| C202.4 | Understand the basic concepts of security and governance as applied to IoT |
| C202.5 | Analyze and illustrate applications of IoT in real time scenarios |
C203 – MACHINE LEARNING LABORATORY(MC4311)
| C203.1 |
apply data preprocessing technique and explore the structure of data to prepare for predictive modeling |
| C203.2 | understand how to select and train a model and measure the performance. |
| C203.3 | apply feature selection techniques in Machine Learning |
| C203.4 | construct Bayesian Network for appropriate problem |
| C203.5 | learn about parametric and non-parametric machine Learning algorithms and implementto practical situations |
C204 – INTERNET OF THINGS LABORATORY(MC4312)
| C204.1 | To understand the various IoT protocols |
| C204.2 | Test and experiment different sensors for application development |
| C204.3 | To develop applications using Arduino/Raspberry Pi/ Equivalent boards. |
| C204.4 | To develop applications that would read the sensor data and post it in Cloud |
| C204.5 | Develop IOT applications with different platforms and frameworks. |
2021
SEMESTER – III
PO – CO MAPPING – MACHINE LEARNING(MC4301)
| PO1 | PO2 | PO3 | PO4 | PO5 | PO6 | |
| C201.1 | 3 | 2 | 2 | 1 | – | 1 |
| C201.2 | 3 | 2 | 2 | 1 | – | 1 |
| C201.3 | 3 | 2 | 2 | 1 | – | 1 |
| C201.4 | 3 | 2 | 2 | 1 | – | 1 |
| C201.5 | 3 | 2 | 2 | 1 | – | 1 |
| Avg | 3 | 2 | 2 | 1 | – | 1 |
PO-CO MAPPING – MACHINE LEARNING(MC4301)
2021
SEMESTER-III
CO – PEO MAPPING – MACHINE LEARNING(MC4301)
| PEO1 | PEO2 | PEO3 | PEO4 | |
| C201.1 | 3 | 3 | 2 | 1 |
| C201.2 | 3 | 2 | 1 | 1 |
| C201.3 | 3 | 2 | 2 | 1 |
| C201.4 | 3 | 2 | 2 | 1 |
| C201.5 | 3 | 1 | 2 | 1 |
| Avg | 3 | 2 | 1.8 | 1 |
CO- PEO Mapping – MACHINE LEARNING(MC4301)
