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1 Semester - 2023 - Batch | Course Code |
Course |
Type |
Hours Per Week |
Credits |
Marks |
MCA131N | MATHEMATICAL FOUNDATION FOR COMPUTER SCIENCE | Core Courses | 2 | 2 | 50 |
MCA132N | PROBLEM SOLVING USING C | Core Courses | 3 | 2 | 50 |
MCA133N | RESEARCH METHODOLOGY | Skill Enhancement Courses | 3 | 2 | 50 |
MCA134N | COMPUTER ORGANIZATION AND DESIGN | Core Courses | 4 | 3 | 100 |
MCA135N | ADVANCED DATABASE TECHNOLOGIES | Core Courses | 3 | 4 | 100 |
MCA171N | PYTHON PROGRAMMING | Core Courses | 5 | 5 | 150 |
MCA172N | WEB STACK DEVELOPMENT | Core Courses | 7 | 4 | 150 |
2 Semester - 2023 - Batch | Course Code |
Course |
Type |
Hours Per Week |
Credits |
Marks |
MCA231N | SOFTWARE ENGINEERING | Core Courses | 3 | 2 | 50 |
MCA232N | APPLIED STATISTICS USING R | Core Courses | 4 | 3 | 100 |
MCA233N | OPERATING SYSTEMS | Core Courses | 4 | 3 | 100 |
MCA251N | SOFTWARE PROJECT DEVELOPMENT LAB -PHASE I | Core Courses | 3 | 1 | 50 |
MCA271N | DATA STRUCTURES AND ALGORITHMS | Core Courses | 8 | 4 | 150 |
MCA272N | PROGRAMMING USING JAVA | Core Courses | 8 | 4 | 150 |
3 Semester - 2023 - Batch | Course Code |
Course |
Type |
Hours Per Week |
Credits |
Marks |
MCA331N | DATA COMMUNICATION AND CRYPTOGRAPHY | Core Courses | 4 | 3 | 100 |
MCA332N | DATA MINING | Core Courses | 4 | 3 | 100 |
MCA333AN | ACCOUNTING AND FINANCE MANAGEMENT | Discipline Specific Elective Courses | 6 | 2 | 100 |
MCA351N | SOFTWARE PROJECT DEVELOPMENT LAB-PHASE II | Core Courses | 3 | 1 | 50 |
MCA371N | MOBILE APPLICATION DEVELOPMENT | Core Courses | 8 | 5 | 150 |
MCA372AN | ADVANCED PYTHON PROGRAMMING | Discipline Specific Elective Courses | 7 | 5 | 150 |
4 Semester - 2022 - Batch | Course Code |
Course |
Type |
Hours Per Week |
Credits |
Marks |
MCA441BN | DATA ENGINEERING AND KNOWLEDGE REPRESENTATION | Discipline Specific Elective Courses | 4 | 3 | 100 |
MCA471N | MOBILE APPLICATIONS | Core Courses | 7 | 4 | 150 |
MCA472N | MACHINE LEARNING | Core Courses | 7 | 4 | 150 |
MCA473BN | NATURAL LANGUAGE PROCESSING | Discipline Specific Elective Courses | 8 | 4 | 150 |
MCA481N | SEMINAR | Skill Enhancement Courses | 3 | 2 | 50 |
5 Semester - 2022 - Batch | Course Code |
Course |
Type |
Hours Per Week |
Credits |
Marks |
MCA571N | CLOUD COMPUTING | Major Core Courses-I | 8 | 4 | 150 |
MCA581N | SPECIALIZATION PROJECT | Major Core Courses-I | 5 | 4 | 100 |
6 Semester - 2022 - Batch | Course Code |
Course |
Type |
Hours Per Week |
Credits |
Marks |
MCA681N | INDUSTRY PROJECT | Core Courses | 16 | 12 | 300 |
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Department Overview: | |
Department of Computer Science of CHRIST (Deemed to be University) strives to shape outstanding computer professionals with ethical and human values to reshape nation’s destiny. The training imparted aims to prepare young minds for the challenging opportunities in the IT industry with a global awareness rooted in the Indian soil, nourished and supported by experts in the field. | |
Mission Statement: | |
VISION The Department of Computational Sciences endeavours to imbibe the vision of the University “Excellence and Service”. The department is committed to this philosophy which pervades every aspect and functioning of the department. MISSION “To develop a computational scientist with ethical and human values”. To accomplish our mission, the department encourages students to apply their acquired knowledge and skills towards professional achievements in their career. The department also moulds the students to be socially responsible and ethically sound. | |
Introduction to Program: | |
Master of Computer Applications is a Two year post graduate programme spread over six Trimesters. This programme strives to shape the students into outstanding computer professionals for the challenging opportunities in IT industry. It enables students to evolve from the stereo type thinking to better achievers and prepares them to scale the global standards. Curriculum incorporates the state of the art areas of IT industry to provide opportunity for extended study in an area of specialization. Programme Objective | |
Program Objective: | |
Programme Outcome/Programme Learning Goals/Programme Learning Outcome: PO1: 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.PO2: 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. PO3: 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. PO4: 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. PO5: 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. PO6: Professional Ethics: Understand and commit to professional ethics and cyber regulations, responsibilities, and norms of professional computing practices. PO7: Life-long learning: Recognise the need, and have the ability, to engage in independent learning for continual development as a computing professional. PO8: Project management and finance: Demonstrate knowledge and understanding of the computing 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. PO9: 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. PO10: 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. PO11: Individual and Team Work: Function effectively as an individual and as a member or leader in diverse teams and in multidisciplinary environments. PO12: 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. | |
Assesment Pattern | |
CIA : 50% ESE : 50% | |
Examination And Assesments | |
The Department of Computational Sciences at CHRIST (Deemed to be University) Delhi- NCR has created a niche in the realm of higher education in India through its programmes. Currently, the Department offers a wide array of undergraduate courses with multiple specializations in the disciplines of Computer Science, Statistics & Mathematics. A dedicated research block with all the latest research facilities boosts the morale of the faculty and research scholars alike. This is an ideal place for students with a research blend of mind to explore his/her passion. Apart from academics, students are moulded holistically through various co-curricular and extracurricular activities. To promote the holistic development of the students and to sustain the academic creativity and inventiveness of the faculty the department engages in numerous workshops, seminars, industrial interfaces, faculty development programmes and many such endeavours. It is equipped with a highly committed team of instructors having versatile experience in teaching and research. The department also provides opportunities to work on collaborative projects with industry and international universities. |
MCA131N - MATHEMATICAL FOUNDATION FOR COMPUTER SCIENCE (2023 Batch) | |
Total Teaching Hours for Semester:30 |
No of Lecture Hours/Week:2 |
Max Marks:50 |
Credits:2 |
Course Objectives/Course Description |
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Course Objectives This course aims to provide fundamental knowledge of mathematical foundations for Computer Science. |
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Learning Outcome |
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CO1: Understand the concepts of Discrete theory, relations and functions used in Computer Science CO2: Understand the Propositional Logic, and Algebraic structure concepts used in
Computer science
CO3: Understand and Apply Finite State Automata and Turing Machines with
Computer related problems.
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Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern | |
MCA132N - PROBLEM SOLVING USING C (2023 Batch) | |
Total Teaching Hours for Semester:30 |
No of Lecture Hours/Week:3 |
Max Marks:50 |
Credits:2 |
Course Objectives/Course Description |
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To provide extensive knowledge of C programming language to the students. It helps in developing the ability to solve computational problems through programs. Lab component is included to give hands-on experience to the students. |
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Learning Outcome |
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CO1: Understand different features of C language CO2: Analyse real life problem statements to enhance problem solving skills CO3: Apply the features of C language to develop applications targeting to the industry
needs. |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern | |
MCA133N - RESEARCH METHODOLOGY (2023 Batch) | |
Total Teaching Hours for Semester:30 |
No of Lecture Hours/Week:3 |
Max Marks:50 |
Credits:2 |
Course Objectives/Course Description |
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This course starts with an introduction to the basic concepts in research and leads through the various methodologies involved in the research process. It focuses on finding out the research gap from the literature and encourages lateral, strategic, and creative thinking. This course also introduces computer technology and basic statistics required for conducting research and reporting the research outcomes scientifically, with emphasis on research ethics. |
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Learning Outcome |
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CO1: Understand the essence of research and the necessity of defining a research problem. CO2: Apply research methods and methodologies including research design, data collection, data analysis, and interpretation. CO3: Create scientific reports according to specified standards. |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern | |
MCA134N - COMPUTER ORGANIZATION AND DESIGN (2023 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:4 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
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This course begins with an introduction to organizational Basic building block diagram of a digital computer system. As the course progresses each major block ranging from Processor to I/O will be discussed in their full architectural detail. The course talks primarily about Computer Organization and Architecture issues, Architecture of a typical Processor, Memory Organization, I/O devices and their interface and System Bus organization etc. |
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Learning Outcome |
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CO1: Understand and analyze computer architecture and organization, computer arithmetic, and CPU design CO2: Compare the design issues in terms of speed, technology, cost and performance. CO3: Identify the performance of various classes of Memories, build large memories using small memories for better performance and analyze arithmetic for ALU implementation |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern | |
MCA135N - ADVANCED DATABASE TECHNOLOGIES (2023 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:4 |
Course Objectives/Course Description |
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To provide a strong foundation for database design and application development and understand the underlying core database concepts and emerging technologies. |
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Learning Outcome |
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CO1: Understand the basic concepts of database systems, transactions, and related database facilities like concurrency control, data object locking, and protocols. CO2: Analyze the database requirements and develop the logical design of the database. CO3: Develop NoSQL database applications using storing, accessing, and querying. |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern | |
MCA171N - PYTHON PROGRAMMING (2023 Batch) | |
Total Teaching Hours for Semester:75 |
No of Lecture Hours/Week:5 |
Max Marks:150 |
Credits:5 |
Course Objectives/Course Description |
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This course covers programming paradigms brought in by Python with a focus on Regular Expressions, List and Dictionaries. It explores the various modules and libraries to cover the landscape of Python programming. |
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Learning Outcome |
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CO1: Understand and apply Python Data structures . CO2: Demonstrate Object Oriented Concepts in Python. CO3: Apply NumPy and Pandas for solving real time problems. CO4: Design GUI window with database operations. |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern | |
MCA172N - WEB STACK DEVELOPMENT (2023 Batch) | |
Total Teaching Hours for Semester:90 |
No of Lecture Hours/Week:7 |
Max Marks:150 |
Credits:4 |
Course Objectives/Course Description |
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On completion of this course, a student will be familiar with full stack and able to develop a web application using advanced technologies and cultivate good web programming style and discipline by solving the real-world scenarios. |
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Learning Outcome |
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CO1: Apply JavaScript, HTML5 and CSS3 effectively to create interactive and dynamic websites.
CO2: Design websites using appropriate security principles, focusing specifically on the vulnerabilities inherent in common web implementations
CO3: Create modern web applications using MERN
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Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern | |
MCA231N - SOFTWARE ENGINEERING (2023 Batch) | |
Total Teaching Hours for Semester:30 |
No of Lecture Hours/Week:3 |
Max Marks:50 |
Credits:2 |
Course Objectives/Course Description |
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The Course provides solid fundamental knowledge of software engineering concepts to the students and it prepares them to develop the skills necessary to handle software projects. It also enables the students to apply software engineering principles to develop quality software applications. |
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Learning Outcome |
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CO1: Understand the importance of the stages in the software life cycle and the various
process models. CO2: Design software by applying the software engineering principles. CO3: Develop the quality software using efficient project management. |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern | |
MCA232N - APPLIED STATISTICS USING R (2023 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:4 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
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This course covers the concept of applied statistics, probability and R tool in computational perspective. It explore the practical experience of statistics and probability using R programming. |
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Learning Outcome |
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CO1: Understand the applied statistics and probability concepts from a computational
perspective. CO2: Creating knowledge on statistics and probability to learn courses like machine
learning and deep learning. CO3: Creating knowledge on statistics and probability to learn courses like machine
learning and deep learning. |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern | |
MCA233N - OPERATING SYSTEMS (2023 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:4 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
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To understand and appreciate the different functions of Operating Systems |
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Learning Outcome |
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CO1: Comprehend the fundamentals concepts and building blocks of Operating
Systems CO2: Understand the concepts of processes, threads, files, inter-process communication
and memory management CO3: Appreciate the concepts of processes, threads, files, inter-process communication
and memory management |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern | |
MCA251N - SOFTWARE PROJECT DEVELOPMENT LAB -PHASE I (2023 Batch) | |
Total Teaching Hours for Semester:30 |
No of Lecture Hours/Week:3 |
Max Marks:50 |
Credits:1 |
Course Objectives/Course Description |
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1. To have hands on experience in developing a software project by using various software engineering principles and methods in each of the phases of software development. 2. Ability to translate end-user requirements into system and software requirements 3. Able to identify and formulate research problem, conduct critical research review based on the domain Description Each student will be encouraged to develop a project based on the societal and institutional needs. At the end of the Course the students will be submitting design document / literature review document in the IEEE format. |
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Learning Outcome |
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CO1: To understand the concepts of Software Engineering CO2: To Identify the problem in the specified area and Analyze the problem, identify
the different modules to solve the problems CO3: To Analyze the research gap and propose the novel methodology for given
problem |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern | |
MCA271N - DATA STRUCTURES AND ALGORITHMS (2023 Batch) | |
Total Teaching Hours for Semester:90 |
No of Lecture Hours/Week:8 |
Max Marks:150 |
Credits:4 |
Course Objectives/Course Description |
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To provide extensive knowledge of data structures and algorithms using C language to the students. It helps in developing the ability to solve computational problems through programs. Lab component is included to give hands-on experience to the students. It includes linked lists, stacks, queues, trees, heaps, hash tables, and graphs. |
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Learning Outcome |
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CO1: Design code involving applications arrays, structures, Pointer, stacks, queues, trees, and
graphs CO2: Understand various techniques for searching, sorting, and hashing CO3: Implement an appropriate data structure to solve real world problems |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern | |
MCA272N - PROGRAMMING USING JAVA (2023 Batch) | |
Total Teaching Hours for Semester:90 |
No of Lecture Hours/Week:8 |
Max Marks:150 |
Credits:4 |
Course Objectives/Course Description |
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This course will help the learner to gain sound knowledge in object-oriented principles, GUI application design with database, and enterprise application design with Servlets. |
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Learning Outcome |
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CO1: Understanding and applying the principles of object-oriented programming in the
construction of robust, maintainable programs. CO2: Analyze the various societal and environmental problems critically to develop
solutions using the features of programming language. CO3: Develop sustainable and innovative solutions for real-time problems. |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern | |
MCA331N - DATA COMMUNICATION AND CRYPTOGRAPHY (2023 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:4 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
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This course aims to set the foundation for computer networks and introduce the cryptographic approaches. The course covers the communication process between devices with a standard set of protocols based on the Internet model (TCP/IP). The last two units present the cryptographic approaches used for network security. |
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Learning Outcome |
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CO1: Follow Network Architecture and its functionality.
CO2: Evaluate network protocols for data transmission in various types of networks.
CO3: Explain the working principle of Algorithms in Cryptography.
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Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern | |
MCA332N - DATA MINING (2023 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:4 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
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This course helps to preprocess and analyze data, choose relevant models and algorithms for respective applications and to develop research interest towards advances in data mining. |
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Learning Outcome |
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CO1: Understand different types of data to be mined and different preprocessing techniques.
CO2: Categorize the scenario for applying different data mining techniques.
CO3: Evaluate different models used for classification and clustering.
CO4: Focus towards research and innovation.
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Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern | |
MCA333AN - ACCOUNTING AND FINANCE MANAGEMENT (2023 Batch) | |
Total Teaching Hours for Semester:30 |
No of Lecture Hours/Week:6 |
Max Marks:100 |
Credits:2 |
Course Objectives/Course Description |
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The course covers a wide range of topics, including financial reporting, financial analysis, budgeting, internal control, and financial decision-making. The course begins by introducing students to the fundamental principles of accounting and the preparation and interpretation of financial statements. |
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Learning Outcome |
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CO1: Students should develop a solid understanding of basic accounting principles, concepts, and terminology. CO2: Students should be able to apply accounting principles to record, analyze, and report financial transactions of individuals, businesses, or organizations. |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern | |
MCA351N - SOFTWARE PROJECT DEVELOPMENT LAB-PHASE II (2023 Batch) | |
Total Teaching Hours for Semester:30 |
No of Lecture Hours/Week:3 |
Max Marks:50 |
Credits:1 |
Course Objectives/Course Description |
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Learning Outcome |
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CO1: To develop the software project based on requirements
CO2: To solve the research issues using novel methodology
CO3: Able to develop real time projects / present Paper, publish research articles and Patents |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern | |
MCA371N - MOBILE APPLICATION DEVELOPMENT (2023 Batch) | |
Total Teaching Hours for Semester:90 |
No of Lecture Hours/Week:8 |
Max Marks:150 |
Credits:5 |
Course Objectives/Course Description |
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This course will enable students to learn to setup Android Application development environment, create user friendly User Interfaces, handle multiple activity, persistent application development, handle data in cloud, test and deploy the App in the market. |
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Learning Outcome |
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CO1: Understand the basic concepts of Mobile application development
CO2: Design and develop user interfaces for the Android platforms
CO3: Apply Kotlin programming concepts to Android application development
CO4: Deploy mobile app with material design principles.
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Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern | |
MCA372AN - ADVANCED PYTHON PROGRAMMING (2023 Batch) | |
Total Teaching Hours for Semester:75 |
No of Lecture Hours/Week:7 |
Max Marks:150 |
Credits:5 |
Course Objectives/Course Description |
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This course inculcates the theoretical and practical approaches which focus on advanced programming concepts in Python. This course explores data analysis, text analysis, gaming, and web development using python.
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Learning Outcome |
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CO1: Create different visualizations using Python
CO2: Design websites using Python IDE frameworks
CO3: Apply Python for Image Processing and Text analysis
CO4: Develop Games using modern tools
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Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern | |
MCA441BN - DATA ENGINEERING AND KNOWLEDGE REPRESENTATION (2022 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:4 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
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To provide a foundational knowledge of data engineering and knowledge representation. To store, retrieve, analyze and design data for various applications. To represent different sorts of knowledge, such as uncertain or incomplete knowledge. |
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Learning Outcome |
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CO1: To store and retrieve data effectively CO2: To analyse the data from different sources CO3: To analyse and design knowledge based systems |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern | |
MCA471N - MOBILE APPLICATIONS (2022 Batch) | |
Total Teaching Hours for Semester:75 |
No of Lecture Hours/Week:7 |
Max Marks:150 |
Credits:4 |
Course Objectives/Course Description |
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This course will enable students to learn to setup Android Application development environment, create user friendly User Interfaces, handle multiple activity, persistent application development, handle data in cloud, test and deploy the App in the market. |
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Learning Outcome |
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CO1: Understand the basic concepts of Mobile application development CO2: Design and develop user interfaces for the Android platforms CO3: Apply Java programming concepts to Android application development CO4: Demonstrate advanced Java programming competency by developing a maintainable and efficient cloud based mobile application |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern | |
MCA472N - MACHINE LEARNING (2022 Batch) | |
Total Teaching Hours for Semester:75 |
No of Lecture Hours/Week:7 |
Max Marks:150 |
Credits:4 |
Course Objectives/Course Description |
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The objective of this course is to provide introduction to the principles and design of machine learning algorithms. The course is aimed at providing foundations for conceptual aspects of machine learning algorithms along with their applications to solve real world problems. |
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Learning Outcome |
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CO1: Understand basic principles of machine learning techniques CO2: Evaluate machine learning problems and their solutions CO3: Apply machine learning algorithms to solve real world problems |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern | |
MCA473BN - NATURAL LANGUAGE PROCESSING (2022 Batch) | |
Total Teaching Hours for Semester:90 |
No of Lecture Hours/Week:8 |
Max Marks:150 |
Credits:4 |
Course Objectives/Course Description |
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This course is to make students familiar with the concepts of the study of human language from a computational perspective. It covers syntactic, semantic and discourse processing models, emphasizing machine learning concepts. |
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Learning Outcome |
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CO1: To understand various approaches on syntax and semantics in NLP CO2: To apply various methods to discourse, generation, dialogue and summarization using NLP. CO3: To analyze various methodologies used in Machine Translation, machine learning techniques used in NLP including unsupervised models and to analyze real time applications |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern | |
MCA481N - SEMINAR (2022 Batch) | |
Total Teaching Hours for Semester:30 |
No of Lecture Hours/Week:3 |
Max Marks:50 |
Credits:2 |
Course Objectives/Course Description |
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The course is designed to enhance the soft skills and technical understanding of the students. |
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Learning Outcome |
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CO1: Understand new and latest trends in Information Technology CO2: Demonstrate the professional presentation abilities CO3: Apply the acquired knowledge in their research |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern | |
MCA571N - CLOUD COMPUTING (2022 Batch) | |
Total Teaching Hours for Semester:90 |
No of Lecture Hours/Week:8 |
Max Marks:150 |
Credits:4 |
Course Objectives/Course Description |
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This course gives an overview of the field of Cloud computing and an in-depth study into its enabling technologies and main building blocks. Students will gain hands-on experience solving relevant problems through projects that will utilize existing public cloud tools. The students will develop the skills needed to become a practitioner or carry out projects in this domain. |
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Learning Outcome |
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CO1: Interpret the types and service models of any given cloud platform. CO2: Analyse the core issues in line with the security, privacy, and interoperability in cloud
platform. CO3: Assess the comparative advantages and disadvantages of Virtualization technology. CO4: Create a cloud environment using open source software tools. |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern | |
MCA581N - SPECIALIZATION PROJECT (2022 Batch) | |
Total Teaching Hours for Semester:60 |
No of Lecture Hours/Week:5 |
Max Marks:100 |
Credits:4 |
Course Objectives/Course Description |
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To work on a project were student are specialized in. |
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Learning Outcome |
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CO1: NA |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern | |
MCA681N - INDUSTRY PROJECT (2022 Batch) | |
Total Teaching Hours for Semester:30 |
No of Lecture Hours/Week:16 |
Max Marks:300 |
Credits:12 |
Course Objectives/Course Description |
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It is a full time project to be taken up either in the industry or in an R&D organization |
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Learning Outcome |
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CO1: NA |
Text Books And Reference Books: | |
Essential Reading / Recommended Reading | |
Evaluation Pattern |