M.Sc. (Computer Science)
Sr.No. | Program Outcomes (POs) - A student will be able to |
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PO1: | Adopt relevant methods and procedures for solving problems using computers. |
PO2: | Compare statistical information and use their intelligence and identify with a professional approach. |
PO3: | Use the relevant equipment, technology and software to collect, compare and assess scientific data. |
PO4: | Develop and demonstrate ideas in an innovative manner. |
PO5: | Design and deliver effective presentations and showcase their various IT skills. |
PO6: | Use research-based learning and research methods including design of experiments, analysis and interpretation of data, and synthesis of the information to provide valid conclusions. |
PO7: | Interpret the impact of the professional engineering solutions in societal and environmental contexts, and demonstrate the information of, and need for sustainable development. |
PO8: | Communicate effectively and professionally both in writing and by means of presentations to both specialist and a general audience. |
Sr.No. | Program Specific Outcomes (PSOs) - A student will be able to |
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PS01: | Communicate computer science concepts, designs, and solutions effectively and professionally. |
PS02: | Apply knowledge of computing to produce effective designs and solutions for specific problems. |
PS03: | Use software development tools, software systems, and modern computing platforms. |
Sr.No. | Course Outcomes (COs) - A student will be able to |
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CO1: | Think about programming languages analytically. |
CO2: | Separate syntax from semantics. |
CO3: | Compare programming language designs. |
CO4: | Interpret their strengths and weaknesses. |
CO5: | Infer basic language implementation techniques. |
CO6: | Learn small programs in different programming Languages. |
Sr.No. | Course Outcomes (COs) - A student will be able to |
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CO1: | Analyze the performance of algorithms. |
CO2: | Choose appropriate algorithm design techniques for solving problems |
CO3: | Design algorithms using advance data structures and implement various techniques. |
CO4: | Understand how the choice of data structures and the algorithm design methods impact the performance of programs. |
CO5: | Understand how the choice of data structures and the algorithm design methods impact the performance of programs. |
CO6: | Analyze String matching algorithms. |
Sr.No. | Course Outcomes (COs) - A student will be able to |
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CO1: | Provide an overview of the concept of NoSQL technology. |
CO2: | Provide an insight to the different types of NoSQL databases |
CO3: | Make a choice of what database technologies to use, based on their application needs. |
CO4: | Understand the concept of Aggregation and Schema Migrations. |
CO5: | Understand the concept of Polyglot Persistence. |
CO6: | Describe the use and implementation of Map-Reduce. |
Sr.No. | Course Outcomes (COs) - A student will be able to |
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CO1: | Understand the principles and paradigm of Cloud Computing. |
CO2: | Appreciate the role of Virtualization Technologies. |
CO3: | Design and deploy Cloud Infrastructure |
CO4: | Understand cloud security issues and solutions. |
CO5: | Understand the Disaster Recovery in Clouds. |
CO6: | Manage the resources in Cloud. |
Sr.No. | Course Outcomes (COs) - A student will be able to |
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CO1: | Implement IaaS, PaaS, SaaS |
CO2: | Implement Storage as Service |
CO3: | Understand the working of Google Drive to make spreadsheets and notes. |
CO4: | Implement Cloud Security. |
CO5: | Implement Identity Management. |
CO6: | Implement Cloud Failure Cluster. |
Sr.No. | Course Outcomes (COs) - A student will be able to |
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CO1: | Learn how to combine OOP and Functional Programming. |
CO2: | Understand the principles of functional programming. |
CO3: | Write purely functional programs. |
CO4: | Gain basic proficiency in Scala. |
CO5: | Get to grips with functional programming. |
CO6: | Learn how to install, create database in MongoDB , Neo4j and implementation of different in-built functions in MongoDB, Neo4j. |
Sr.No. | Course Outcomes (COs) - A student will be able to |
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CO1: | Learn how to combine OOP and functional programming. |
CO2: | Understand the principles of functional programming. |
CO3: | Write purely functional programs. |
CO4: | Gain basic proficiency in Scala. |
CO5: | Get to grips with functional programming. |
CO6: | Learn how to install, create database in MongoDB , Neo4j and implementation of different in-built functions in MongoDB, Neo4j. |
Sr.No. | Course Outcomes (COs) - A student will be able to |
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CO1: | Understand the working of wireless and mobile technologies. |
CO2: | Design and develop the android applications. |
CO3: | Design and develop phonegap applications. |
CO4: | Explain the concepts and components of ios. |
CO5: | Explore the various components of android applications |
CO6: | Use various APIs of android and phonegap. |
Sr.No. | Course Outcomes (COs) - A student will be able to |
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CO1: | Develop skills that are required to ensure successful medium and large-scale software projects. |
CO2: | Examine requirements elicitation, project management, verification and validation and management of large software engineering projects. |
CO3: | Perform software verification and validation using inspections, design and execution of the system. |
CO4: | Develop skills to ensure successful medium and large software engineering projects. |
CO5: | Design test cases to help find problems in the requirements or design of an application. |
CO6: | Apply project management techniques for projects to solve real problems. |
Sr.No. | Course Outcomes (COs) - A student will be able to |
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CO1: | Explain the ideas of soft computational techniques based on human experience. |
CO2: | Design, analyze and perform experiments on real life problems using various Neural Learning Algorithms. |
CO3: | Conceptualize fuzzy logic and its implementation for various real world applications. |
CO4: | Apply the process of approximate reasoning using Neuro- Fuzzy Modelling. |
CO5: | Provide the mathematical background to carry out optimization using genetic algorithms. |
CO6: | Explain the students about Artificial Neural Networks and various categories of ANN. |
Sr.No. | Course Outcomes (COs) - A student will be able to |
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CO1: | Apply fuzzy logic and reasoning to handle different properties and algorithms of Fuzzy Logic. |
CO2: | Apply neural networks Activation Functions, Perceptron Learning Algorithm and Hebb’s Rule. |
CO3: | Implementation of neural networks for Feed Forward and Back propagation. |
CO4: | Construct Neural Network for solving linearly separable problem using Perceptron Model. |
CO5: | Implementation of Neural Network to develop supervised learning algorithms. |
CO6: | Apply genetic algorithm to study and analyze genetic life cycle. |
Sr.No. | Course Outcomes (COs) - A student will be able to |
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CO1: | Understand the components of android applications. |
CO2: | Design and develop the android applications. |
CO3: | Design and develop the phonegap and IOS applications. |
CO4: | Implement UNIX/Linux Commands. |
CO5: | Demonstrate the use of various system calls. |
CO6: | Implement and catch the signals. |
Sr.No. | Course Outcomes (COs) - A student will be able to |
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CO1: | Recognize major Software Architectural styles, Designs and Frameworks to create reusable and flexible software applications and systems. |
CO2: | Recognize the characteristics of patterns that make it useful to solve real-world problems. |
CO3: | Apply Software Architectural styles, Design Pattern and Frameworks to create reusable and flexible software applications and systems. |
CO4: | Perform software verification and validation using inspections, design and execution of system. |
CO5: | Perform case study to take a framework and find patterns in the frames. |
CO6: | Design java applications using design pattern techniques. |
Sr.No. | Course Outcomes (COs) - A student will be able to |
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CO1: | Recognize the characteristics of machine learning that make it useful to real-world problems. |
CO2: | Process available data using python libraries and predict outcomes using machine learning algorithms to solve given problems. |
CO3: | Estimate machine learning models efficiency using suitable metrics. |
CO4: | Explore the various algorithms of machine learning. |
CO5: | Design application using machine learning techniques. |
CO6: | Understand the role of machine learning engineer |
Sr.No. | Course Outcomes (COs) - A student will be able to |
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CO1: | Learn advanced technology which is used widely in Industry as a part of full stack developer. |
CO2: | Ppowerful way to develop the web application in Python. |
CO3: | Understand asynchronous programming using NodeJS. |
CO4: | Build and deploy a robust Django Web App. |
CO5: | Integrate with Restful web services using ExpressJS Framework. |
CO6: | Build and HTTP server using the core modules in NODEJS. |
CO7: | Interface to a MongoDB database and a web service. |
Sr.No. | Course Outcomes (COs) - A student will be able to |
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CO1: | Recognize the characteristics, applications of big data. |
CO2: | Discuss the emerging database landscape. |
CO3: | Differentiate various applications architecture for Big data analysis. |
CO4: | Understand components of Hadoop Ecosystem. |
CO5: | Understand how to perform real time analytics. |
CO6: | Study Big Data Analytics Methodology. |
Sr.No. | Course Outcomes (COs) - A student will be able to |
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CO1: | Recognize the characteristics, applications of big data that make it useful to real-world problems. |
CO2: | Process available data using big data tools hadoop file system and predict outcomes to solve given problems. |
CO3: | Study various case studies using big data tools/commands and analyse it. |
CO4: | Design various case studies using big data tools/commands. |
CO5: | Create a single node cluster Hadoop configuration. |
CO6: | Study and design various case studies using big data tools/commands and analyse it. |
Sr.No. | Course Outcomes (COs) - A student will be able to |
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CO1: | Use libraries like Numpy, Pandas and Scikit Learn efficiently for machine learning. |
CO2: | Visualise the data using libraries like Matplotlib and Seaborn. |
CO3: | Apply suitable algorithm and metrics to evaluate the machine learning model. |
CO4: | Use specific frameworks as per applications need. |
CO5: | Design java applications using design pattern techniques. |
CO6: | Recognize the characteristics of patterns for a given problem. |
Sr.No. | Course Outcomes (COs) - A student will be able to |
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CO1: | Understand different software engineering concepts particularly software development life cycle i.e planning, analyzing , designing ,implementation and testing of a software project and work accordingly. |
CO2: | Understand different programming language concepts in depth, particularly Java, Net, Machine Learning, Deep Learning etc. |
CO3: | Work as a team and learn to co-ordinate and communicate effectively with team members and get the work done. |
CO4: | Learn to focus on getting a working project done on time so that it will be delivered to customer without delay. |
CO5: | Understand different software tools and techniques to implement project which are used in IT industry. |
CO6: | Learn to have hand on training to work on actual environment to implement software project. |