M.Sc. (Computer Science)
| Sr.No. | Program Outcomes (POs) |
|---|---|
| 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 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) |
|---|---|
| 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) |
|---|---|
| CO1: | Think about programming languages analytically. |
| CO2: | Separate syntax from semantics. |
| CO3: | Compare programming language designs. |
| CO4: | Interpret their strengths and weaknesses. |
| CO5: | Learn new languages more quickly. |
| CO6: | Infer basic language implementation techniques. |
| CO7: | Learn small programs in different programming Languages. |
| Sr.No. | Course Outcomes (COs) |
|---|---|
| CO1: | Design the algorithms. |
| CO2: | Select the appropriate algorithm by doing necessary analysis of algorithms |
| CO3: | Learn basic Algorithm Analysis techniques and identify the use of asymptotic notation |
| CO4: | Interpret the use of data structures in improving algorithm Performance |
| CO5: | Differentiate classical problem and solutions |
| CO6: | Identify classification of problems |
| CO7: | Provide foundation in algorithm design and analysis |
| CO8: | Describe and design algorithms in the context of space and time complexity. |
| Sr.No. | Course Outcomes (COs) |
|---|---|
| CO1: | Summarize database technologies |
| CO2: | Describe the concept of NoSQL databases |
| CO3: | Design database using MongoDB. |
| CO4: | Implement the information of making a choice of what database technologies to use, based on their application needs. |
| CO5: | Handle large volumes of structured, semi-structured, and unstructured data using database technologies. |
| CO6: | Identify detailed architecture, define objects, load data, query data and performance tune NoSQL databases. |
| Sr.No. | Course Outcomes (COs) |
|---|---|
| CO1: | Explain the principles and paradigm of Cloud Computing. |
| CO2: | Appreciate the role of Virtualization Technologies |
| CO3: | Design and deploy Cloud Infrastructure. |
| CO4: | Predict cloud security issues and solutions. |
| CO5: | Design& develop backup strategies for cloud data based on features. |
| CO6: | Display new ideas and innovations in cloud computing. |
| Sr.No. | Course Outcomes (COs) |
|---|---|
| CO1: | Think about programming languages analytically: |
| CO2: | Separate syntax from semantics |
| CO3: | Compare programming language designs |
| CO4: | Identify their strengths and weaknesses |
| CO5: | Learn new languages more quickly |
| CO6: | Interpret basic language implementation techniques |
| CO7: | Learn small programs in different programming Languages. |
| Sr.No. | Course Outcomes (COs) |
|---|---|
| CO1: | Define different types of routing protocols. |
| CO2: | Illustrate different types of multimedia. |
| CO3: | Recall the concept of networking models, protocols, functionality of each layer. |
| CO4: | Explain methods of user authentication. |
| CO5: | Explain the importance of network security and cryptography and its applications |
| CO6: | Identify different network security protocols and learn them. |
| Sr.No. | Course Outcomes (COs) |
|---|---|
| CO1: | Relate the concepts of distributed database |
| CO2: | Describe what is Distributed DBMS |
| CO3: | Explain various architectures of DDBMS |
| CO4: | Apply various fragmentation techniques given a problem. Demonstrate the basic fundamentals of distributed database |
| CO5: | Illustrate information of architecture, design issues, integrity control, query processing and optimization, transactions, and concurrency control & distributed transaction reliability. |
| CO6: | Identify the steps of query processing. |
| Sr.No. | Course Outcomes (COs) |
|---|---|
| CO1: | Basic Algorithm Analysis techniques and express the use of asymptotic notation |
| CO2: | Discuss different design strategies |
| CO3: | Express the use of data structures in improving algorithm performance. |
| CO4: | Explain classical problem and solutions |
| CO5: | Learn a variety of useful algorithms |
| CO6: | Identify classification of problems. |
| Sr.No. | Course Outcomes (COs) |
|---|---|
| CO1: | Demonstrating the working mechanism and implementation of data communication protocols on Unix operating system. |
| CO2: | Implementation using TCP sockets |
| CO3: | Implementation using UDP sockets. |
| CO4: | Construct Client-Server application program |
| CO5: | Construct Client-Server application program |
| CO6: | Show the use of different socket options. |
| CO7: | Plan to create different kind projects which can make use of TCP and UDP client server technology |
| Sr.No. | Course Outcomes (COs) |
|---|---|
| CO1: | What are the applications of Digital Image Processing How images are formed, sampled, quantized and represented digitally. |
| CO2: | How images are enhanced using Spatial Filtering |
| CO3: | How images are enhanced using Frequency Filtering. |
| CO4: | How images are restored using different filters. |
| CO5: | Role of Morphological Operations in Image Processing. |
| CO6: | Segmentation and how it can be achieved using different methods. |
| CO7: | How object can be described. (Feature Extraction methods) |
| Sr.No. | Course Outcomes (COs) |
|---|---|
| CO1: | Describe the programming interface to the Unix/Linux-system call. |
| CO2: | Demonstrate C program that runs under Unix/Linux. |
| CO3: | Define the insights into functional modules for OS. |
| CO4: | Summarize the concepts underlying in the design and implementation of OS. |
| CO5: | Summarize the concept of system call implementation. |
| CO6: | Design and implementation of Operating Systems. |
| Sr.No. | Course Outcomes (COs) |
|---|---|
| CO1: | Process raw data to make it suitable for various data mining algorithms |
| CO2: | Discover and measure interesting patterns from different kinds of databases. |
| CO3: | Interpret the techniques of clustering, classification, association finding, feature selection and visualization to real world data. |
| CO4: | Design a data mart or data warehouse for any organization. |
| CO5: | Asses raw input data and preprocess it to provide suitable input for range of data mining algorithms. |
| CO6: | Extract association rules and classification model |
| CO7: | Identify the similar objects using clustering techniques. |
| Sr.No. | Course Outcomes (COs) |
|---|---|
| CO1: | Gained information of DOT Net framework |
| CO2: | Learned C# language features for development of Web and Stand Alone Application |
| CO3: | Implementing Web Services using DOTNET framework |
| CO4: | Apply validations to ASP and C# pages |
| CO5: | use different controls of c# and ASP.Net |
| CO6: | Develop different kinds of web application |
| CO7: | Host different kind of web application on the internet. |
| Sr.No. | Course Outcomes (COs) |
|---|---|
| CO1: | Define What is AI?and Early work in AI, AI and related fields and AI problems and Techniques |
| CO2: | Solve AI problems |
| CO3: | Express the Representations and Mappings, Approaches to Knowledge representation, Knowledge representation method,- Propositional Logic,, Predicate logic, Representing Simple facts in Logic, Representing Instances and Isa relationships,- Computable Functions and Predicates, Resolution, Forward and backward chaining |
| CO4: | Write a Script and design a frame for given problem |
| CO5: | EstimateMinimax Search Procedures, Adding alpha-beta cutoffs |
| CO6: | Get the information about what is learning and types of learning. |
| Sr.No. | Course Outcomes (COs) |
|---|---|
| CO1: | Demonstrate the skill to ensure successful medium and large scale projects |
| CO2: | Relate requirement elicitation, project management, verification and validation of software engineering projects with real life projects |
| CO3: | Select and use project management techniques for process modeling, planning,estimation,risk management, process and product metrics for successful quality project |
| CO4: | Apply project management concepts and techniques to an IT project. |
| CO5: | Identify issues that could lead to IT project success or failure. |
| CO6: | Explain project management in terms of the software development process. |
| CO7: | Describe the responsibilities of IT project managers. |
| CO8: | Apply project management concepts through working in a group as team leader or active team member on an IT project. |
| Sr.No. | Course Outcomes (COs) |
|---|---|
| CO1: | Explain the concepts of android. |
| CO2: | Explain the principles and theories of mobile computing technologies. |
| CO3: | Describe infrastructures and technologies of mobile computing technologies. |
| CO4: | List applications in different domains that mobile computing offers to the public, employees, and businesses. |
| CO5: | Describe the possible future of mobile computing technologies and applications. |
| CO6: | Effectively communicate course work through written and oral presentation |
| Sr.No. | Course Outcomes (COs) |
|---|---|
| CO1: | Explain the concepts of how an intelligent system work and its brief development process. |
| CO2: | Solve fuzzy set problems by recognizing fuzzy rules, approximate reasoning, fuzzy inference systems, and fuzzy logic |
| CO3: | Explain the theory and concepts of neural networks |
| CO4: | Use Soft computing techniques the solve character recognition, pattern classification, regression and similar problems. |
| CO5: | List the facts and outline the different process carried out in fuzzy logic, ANN and Genetic Algorithms. |
| CO6: | Outline facts to optimization. identify process/procedures to handle real world problems using soft computing. |
| Sr.No. | Course Outcomes (COs) |
|---|---|
| CO1: | Identify, define and justify the scope of the proposed problem |
| CO2: | Gather and analyze system requirements |
| CO3: | Propose an optimized solution among the existing solutions |
| CO4: | Practice software analysis and design techniques |
| CO5: | Develop a functional application based on the software design |
| CO6: | Apply coding, debugging and testing tools to enhance the quality of the software |
| CO7: | Construct new software system based on the theory and practice gained through this exercise |
| CO8: | Prepare the proper documentation of software projects following the standard guidelines |
| CO9: | Learn technical report and oral presentation skills |
| Sr.No. | Course Outcomes (COs) |
|---|---|
| CO1: | Discuss the basics of lambda calculus and combinator, how they are used to implement functional programming languages. |
| CO2: | Summarise the main features of reduction strategies |
| CO3: | Problem Solving using Python Programming |
| CO4: | Programming Capabilities using Python Programing |
| CO5: | Construct reduce code using functional features of Python Programming |
| CO6: | Construct Object Oriented Programming features using Python Programming. |
| Sr.No. | Course Outcomes (COs) |
|---|---|
| CO1: | Explain the role of BI in enterprise performance management and decision support. |
| CO2: | Describe the applications of data mining and intelligent systems in managerial work. |
| CO3: | Distinguish between data warehousing and online analytical processing (OLAP) concepts, including dimensional modeling, star and snowflake schemas, attribute hierarchies, metrics, and cubes. |
| CO4: | Reframe data analysis and reporting using available BI software. |
| CO5: | Explain the foundations, definitions, and capabilities of DSS, data analytics and BI. |
| CO6: | List the definitions, concepts, and architectures of data warehousing. |
| CO7: | Demonstrate the impact of business reporting, information visualization, and dashboards. |
| CO8: | Explain data mining, neural networks, support vector machines, text analytics, text mining, sentiment analysis, web mining, web analytics, social analytics, social network analysis |