Takshashila Mahavidyalaya Amravati

Course Outcome

Researach Methodology & IPR

1. Study the basic concepts of research and related methodologies.
2. Identify appropriate research problem and good research designing.
3. To develop and implement the techniques of data collection, analysis of data and interpretation.
4. Describe foundational knowledge, learn, adapt and successfully apply analytical and computational approaches on changing societal and technological challenges
5. Learning research tools.
6. To study the IPR, Patent, Copyright, Design patent, and Trademark

Computer Organization System

Learn the concepts of computer organization for several engineering applications.

1. Develop the ability and confidence to use the fundamentals of computer organization as a tool in the engineering of digital systems.
2. Work and identify the different hardware of CPU and performs operation on them.
3. To identify, formulates, and solves hardware and software computer engineering problems using sound computer engineering principle.
4. To impart the knowledge on micro programming
5. To comprehend the concepts of advanced pipelining techniques.

Data Structure

1. Learn the concepts of linear data structures such as arrays, linked lists, stacks and queues.
2. Understand and use the concepts of non-linear data structures such as trees & Graph.
3. Learn and understand various data searching and sorting methods with its complexity.
4. Demonstrate operations such as insertion, deletion, searching and traversing on data structures.
5. Analyses and apply specific sorting and searching methods depending upon factors like type of data, volume of data.
6. Learn & Understand B-tree indexing, hashing, collisions processing and its applications

Database Management Technology

1. Understand and apply the basic concepts and principles of database systems, including their purpose, structure, design, query languages, and relational operations.
2. Demonstrate understanding of data manipulation, retrieval, database management concepts and apply SQL query language effectively.
3. Design efficient and normalized databases using the Entity-Relationship model and will be able to achieve good relational designs and improve database by normalization techniques.
4. Apply knowledge of physical storage systems, data storage structures, and indexing techniques for efficient and effective management of databases.
5. Comprehend and apply the fundamental concepts and techniques related to transactions (ACID property), concurrency control & Protocols, recovery mechanisms, deadlock handling, and recovery algorithms.
6. Understand recent trends in database technology and analyze different database architectures, cloud- based services, No SQL databases, and big data storage systems based on Map Reduce and Hadoop.

Software Testing

1. Design test cases suitable for a software development for different domains.
2. Apply various software testing techniques, such as black-box testing, white-box testing, graybox testing, and regression testing, to identify defects and verify the functionality of software systems.
3. Prepare test planning based on the document.
4. Document test plans and test cases designed.
5. Design test cases that adequately cover different aspects of software functionality, including boundary cases, error handling, and performance scenarios.
6. Apply automated testing tools and frameworks to streamline the testing process and improve efficiency

Computer System Organization Practical

1. Implementation of Computer organisation Programs using Simulators
2. Testing the working of Digital Electronics components and operations.
3. Ability to understand Input –Output Organization
4. To impart the knowledge on micro programming.
5. Implementation of Logic Gates.
6. Able to design electronic circuits.

Lab SQL/DBMS tools, MS Sql, My Sql

1. Install and configure database systems proficiently.
2. Analyze and assess database models and entity relationship models.
3. Design and implement a database schema for a specific problem domain.
4. Acquire thorough understanding of relational database systems.
5. Execute effective data population and querying using SQLDDL, DML, and DCL commands.
6. Develop a back end database for an organization based on case study

N1MCS8-DSE-I(2): lab

1. To study fundamental concepts in software testing, including software testing objectives, process, criteria, strategies, and methods.
2. To discuss various software testing issues and solutions in software unit test; integration, regression, and system testing.
3. To learn how to planning a test project, design test cases and data, conduct testing operations, manage software problems and defects, generate a testing report.
4. To expose the advanced software testing topics, such as object-oriented software testing methods, and component-based software testing issues, challenges, and solutions.
5. To gain software testing experience by applying software testing knowledge and methods to practice-oriented software testing projects.
6. To understand software test automation problems and solutions

Data Structure with OOP LAB

1. Apply the basic concepts of C++/ Java programming in developing the code for various applications.
2. Individually Apply C++/Java programming concepts to design various data structures.
3. Identify and apply a suitable data structure for a given application.
4. Implement various searching techniques 5. Implement various sorting techniques 6. Implement various graph technique.

Operating System

1. To make aware of different types of Operating System and their services.
2. Know basic components of an operating system.
3. Comprehend how an operating system virtualises CPU and memory.
4. Discuss various scheduling and swapping policies.
5. Explain how a simple file system organizes data in the hard disk.
6. Get to know how an operating system protects the computer system

Graphic Application Programming

1. Able to understand the mathematical modelling of graphical objects to be drawn/used in different kind of applications.
2. Learn and understand the concepts of computer graphics, including viewing, projection, perspective, modelling and transformation in2 D&3D.
3. Learn and understand the algorithms to generate line segments, polygon and its transformations, windowing and clipping.
4. Demonstrate operations such as various Transformation and Projection.
5. Demonstrate various algorithms for scan conversion and filling of basic objects and their comparative analysis.
6. Get the knowledge of display control, 3D geometry, primitives and conversions, algorithms for hidden surfaces and lines, concepts of shading and curves.

Computer Network & Wireless Technology

After successful completion of the course, the students would be able to

1. Understand the basics of data communication and computer networking
2. Compare and describe the structure and working of various reference models for networking
3. Infer the process of communication in client server model
4. Develop knowledge about design of various protocols used in communication
5. Anticipate various anomalies that may occur during network communication
6. Build knowledge about wireless technology

Data Mining and Data Warehouse

Upon completion of this course successfully, students would be able to

1. Use basic concepts and techniques of Data Mining
2. Develop skills of using recent data mining software for solving practical problems.
3. Develop experience of doing in dependent study and research.
4. Study the methodology of engineering legacy databases for data warehousing and data mining to derive business rules for decision support systems.
5. Develop and apply critical thinking, problem-solving, and decision- making skills.

Artifical Intelligences& Machine Learning

On completion of this course, students would be able to:

1. Analyze artificial intelligence (AI) techniques and describe their principles.
2. Examine and demonstrate the important role that search algorithms play in problem-solving, inference, perception, knowledge representation, and learning.
3. Use the concepts of logic and knowledge representation to solve challenges in the real world.
4. Recognize the features of machine learning that allow it to be used in solving a real-world problem.
5. Implement the various supervised learning techniques for tree-based and support vector machine models.
6. Use several linear approaches for classification and regression, then optimize them using various regularization strategies.

Network Security

1. Study the introduction about security over the network.
2. Learn the cryptographic algorithm.
3. Learn and understand the types of authentication application and protocol.
4. Learn the Protocol used to provide authenticity to the client and data.
5. Understand the concept of network security and prevention from intruders.
6. Learn and understand Types of viruses.

Distributed Computing

1. Learn the fundamental concepts of distributed computing systems.
2. Learn the concepts of message passing in distributed systems with inter Process Communication.
3. Learn and understand Remote Procedure Call-RPC
4. Learn and understand the concept of Synchronization
5. Learn and understand Deadlock in distributed computing systems

Desgin & algorthim

1. Analyze the running time proved the correctness basic algorithms.
2. Design efficient algorithms for computational problems using divide and conquer
3. Design optimal solutions using greedy algorithm.
4. Able to apply searching and traversing efficiently
5. Prove the hardness of NP hard problems using simple reduction.
6. Do performance analysis of simple approximation algorithm

Web Computing

1. Describe the basic concept PHP, Server-Side Scripting Language.
2. Design applications using Arrays and Function.
3. Understand OOP concepts for application development.
4. Implement the knowledge of PHP-Database handling.
5. Develop PHP framework for effective design of web application.
6. Implement JavaScript to develop dynamic web pages.

AL & ML Practical

1. Apply various AI search algorithms (uninformed, informed, heuristic, constraint satisfaction,)
2. Understand the fundamentals of knowledge representation, inference.
3. Understand the fundamentals of theorem proving using AI and ML tools.
4. Demonstrate working knowledge of reasoning in the presence of incomplete and/or uncertain information

Clouding Computing

On completion of this course, students would be able to:

1. Describe the basic concept of Cloud Computing and Its Models.
2. Analyze the application and virtualization infrastructures for cloud computing.
3. Exhibit in-depth understanding of key cloud-based services.
4. Understand the necessity of management activity at cloud environment.
5. Study different cloud deployment tools. 6. Understand various security aspects related to cloud

Big Data

On completion of this course, students would be able to:

1. Identify current scenarios of big data and provide various facets of big data.
2. Illustrate different types of big data technologies.
3. Familiar with the big data technology framework and file systems.
4. Describe the components of Map Reduce &it’s working.
5. Understand the use of Apache Spark in Distributed processing System
6. Apply NoSQL to store big data and real time web application

Cyber Security

On completion of this course, students would be able to:

1. Analyses and evaluate the importance of personal data & its privacy & security.
2. Recognize the importance of firewall in cyber-attacks from unauthorized access in network.
3. Increase awareness about Cyber-attack vectors and safety against Cyber-frauds
4. Take measures for self -Cyber protection as well as societal Cyber- Protection.
5. Analyses and evaluate existing legal framework and laws on Cyber security
6. Analyses and evaluate the digital payment system security and remedial measures against digital payment frauds

Block Chain Technology

On completion of this course, students would be able to:

1. Describe the basic concept of Block chain and Distributed Ledger Technology.
2. Interpret the knowledge of the Bit coin network, nodes, keys, wallets and transactions.
3. Implement smart contracts in Ethereum using different development frameworks.
4. Develop applications in permissioned Hyperledger Fabric network.
5. Understand different Crypto assets and Crypto currencies.
6. Analyses the use of Blockchain in different use cases and with AI, IoT and Cyber Security using case studies.

Android Programming Skills

On completion of this course, students would be able to:

1. Develop Android apps with proficiency in Java, UI design, and user interaction.
2. Implement core Android components, including Activities, Fragments, Services, Broadcast Receivers, and Content Providers.
3. Manage data storage and retrieval using SQLite, Shared Preferences, and file-based techniques.
4. Integrate networking capabilities to handle HTTP requests, JSON/XML data, and RESTful APIs.
5. Utilize multimedia features and device sensors for audio, video, camera, and location-based services

Software Testing

On completion of this course, students would be able to:

1. Design test cases suitable for a software development for different domains.
2. Apply various software testing techniques, such as black-box testing, white-box testing, gray-box testing, and regression testing, to identify defects and verify the functionality of software systems.
3. Prepare test planning based on the document.
4. Document test plans and test cases designed.

Operating System Algorithm LAB

1. Able to learn various CPU scheduling algorithms.
2. Able to learn memory management techniques.
3. Able to learn disk scheduling algorithms.
4. Able to learn memory allocation algorithms.
5. Able to learn the various page replacement algorithms.

Graphics Application Programming LAB

1. Apply the basic concepts of C programming in developing the code for various Graphics applications.
2. Individually Apply C programming concepts to do the Program in Computer Graphics.
3. Identify and apply a suitable transformation for a given application.

Lab VI- Lab Based on DSE II (1)/ DSE II (2)/ DSE II (3) N2MCS7 -DSE II (3) - Data Mining Data Warehousing

1. Understand and implement classical models and algorithms in data warehouses and data mining 2. Characterize the kinds of patterns that can be discovered by association rule mining, classification and clustering.
2. Master data mining techniques in various applications like social, scientific and environmental context.
3. Develop skill in selecting the appropriate data mining algorithm for solving practical problems.