Syllabus

MCA

MCA Syllabus

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Course Outcomes

1. Knowledge Computing Use expertise of computing fundamentals, mathematics, and domain knowledge suitable to figure out solutions for the complex problems.
2. Problem analysis Classify, articulate, review and analyze research and computing problems to reach valid conclusions using computing sciences, mathematics and relevant domain fields.
3. Design/development of solutions Design solutions to complex problems and plan system requirements or processes which meet the specific needs of the clients for the public health and safety, and the cultural, societal, and environmental considerations.
4. Conduct investigations of complex problems Apply research oriented methods to analyze, interpret and to do the design of experiments on the information to arrive at effective conclusions.
5. Modern tool usage Build, select, and apply suitable techniques, resources and modern computing IT tools including prediction, analysis and modeling to computing systems.
6. Research Ability Facility to independently carry out research / investigations, identify problems and develop solutions to solve practical problems.
7. Innovation and Entrepreneurship Recognize and identify an opportunity for using innovation to pursue that opportunity to create value for the benefit of the individual and society at large.
8. Ethics Apply ethical principles and commit to professional ethics and responsibilities and norms of the professional computing practice.
9. Individual and team work Function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings.
10. Communication Communicate effectively on complex system building activities with the stake holders and with society at large, such as, being able to comprehend and write effective reports and design documentation, make effective presentations, and give and receive clear instructions.
11. Project management and finance Demonstrate knowledge and understanding of the 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.
12. Life-long learning Recognize the need for, and have the preparation and ability to engage in independent and life-long learning in the broadest context of technological change.

PROGRAM SPECIFIC OBJECTIVES (PSO)

PSO 1: Enable the students to select suitable data model, appropriate architecture, platform to implement a system with good performance.

PSO 2: Enable the students to design and integrate various system based components to provide user interactive solutions for various challenges.

Mapping Of Programme Educational Objectives with Programme Outcomes And Programme Specific Objectives

Programme Educational Objectives	Programme Outcomes												PSO
	1	2	3	4	5	6	7	8	9	10	11	12	1	2
1	√	√	√	√	√	√	√				√		√
2		√	√		√	√	√	√	√		√	√		√
3	√			√			√			√	√		√	√

S.A. ENGINEERING COLLEGE, CHENNAI - 77

AN AUTONOMOUS INSTITUTION

REGULATION – 2020A

CHOICE BASED CREDIT SYSTEM

MASTER OF COMPUTER APPLICATIONS

SEMESTER I

SL. NO.	COURSE CODE	COURSE TITLE	CATEGORY	CONTACT HOURS				C
				L	T	P	Total
1	MC 2101A	Python Programming	FC	3	0	0	3	3
2	MC 2102A	Advanced Data Structures and Algorithms	PC	3	0	0	3	3
3	MC 2103A	Advanced Database Technology	PC	3	0	0	3	3
4	MC 2104A	Object Oriented Software Engineering	PC	3	0	0	3	3
5	MA 2105A	Matrices, Probability and Statistics	PC	5	3	2	0	4
6	MC 2106A	Research Methodology and Intellectual Property Rights	FC	2	2	0	0	2
7	MC 2111A	Advanced Database Technology Laboratory	PC	4	0	0	4	2
8	MC 2112A	Advanced Data Structures and Python Programming Laboratory	PC	4	0	0	4	2
9	MC 2113A	Communication Skills Enhancement	EEC	2	0	0	2	1
TOTAL				29	17	2	10	23

SEMESTER II

SL. NO.	COURSE CODE	COURSE TITLE	CATEGORY	CONTACT HOURS				C
				L	T	P	Total
1	MC 2201A	Internet Programming	PC	3	0	0	3	3
2	MC 2202A	Cloud Computing Technologies	PC	3	0	0	3	3
3	MC 2203A	Artificial Intelligence and Machine Learning	PC	3	0	0	3	3
4	MC 2204A	Mobile Application Development	PC	3	0	0	3	3
5	MC 2205A	Cyber Security	PC	3	0	0	3	3
6	MC 200XA	Elective I: Software Project Management, Agile Methodologies, E Learning, Accounting and Financial Management for Application	PE	3	3	0	0	3
7	MC 2211A	Internet Programming Laboratory	PC	4	0	0	4	2
8	MC 2212A	Artificial Intelligence and Machine Learning Laboratory	PC	4	0	0	4	2
9	MC 2214A	Technical Seminar and Report Writing	PC	2	0	0	2	1
TOTAL				28	18	0	10	23

SEMESTER III

SL. NO.	COURSE CODE	COURSE TITLE	CATEGORY	CONTACT HOURS				C
				L	T	P	Total
1	MC 2301A	Data Science	PC	3	3	0	0	3
2	MC 2302A	Embedded Systems and Internet of Things	PC	3	3	0	0	3
3	MC 2303A	Software Testing and Quality Assurance	PC	3	3	0	0	3
4	MC 200XB	Elective II: Compiler Optimization Techniques, C# and .NET Programming, Wireless Networking, Web Design, Big Data Analytics	PE	3	3	0	0	3
5	MC 200XC	Elective III: Social Network Analytics, Bio Inspired Computing, Information Retrieval Techniques, Software Architecture, Data Mining and Data Warehousing Techniques	PE	3	3	0	0	3
6	MC 200XD	Elective IV: Data Visualization Techniques, Resource Management Techniques, Professional Ethics, Organizational Behavior, Business Data Analytics	PE	3	3	0	0	3
7	MC 200XE	Elective V: Cryptocurrency and Blockchain Technologies, Advances in Networking, Soft Computing, Deep Learning, Network Programming and Security	PE	3	3	0	0	3
8	MC 2311A	Data Science Laboratory	PC	4	0	0	4	2
9	MC 2312A	Internet of Things Laboratory	PC	4	0	0	4	2
10	MC 2313A	Mini Project	EEC	4	0	0	4	2
TOTAL				29	21	0	8	27

SEMESTER IV

SL. NO.	COURSE CODE	COURSE TITLE	CATEGORY	CONTACT HOURS				C
				L	T	P	Total
1	MC 2401A	Project Work	EEC	24	0	0	24	12
TOTAL				24	0	0	24	12

TOTAL CREDITS: 85