PG Curriculum - Computer Science and Engineering - Saveetha (Autonomous) Engineering College

VISION

To uniquely position the department and to establish synergistic relationship across the entire spectrum of disciplines involved with computing by our faculty contributing to Computer Science and devoting themselves to take the maximal advantage of modern Computer Science to solve a wide range of complex, scientific, technological and social problems.

MISSION

To pursue our vision by striving for excellence in creating, applying, and imparting knowledge in Computer Science and Engineering.
To pursue comprehensive educational system, research in collaboration with industry and government and to disseminate knowledge through scholarly publications.
To provide service through professional societies to the community, the state, and the nation.

I. PROGRAMME EDUCATIONAL OBJECTIVES (PEOs)

Graduates, within four years of graduation, should demonstrate peer- recognized expertise together with the ability to articulate that expertise and use it for contemporary problem solving in the analysis, design, and evaluation of computer and software systems, including system integration and implementation.
Graduates, within four years of graduation, should demonstrate engagement in the engineering profession, locally and globally, by contributing to the ethical, competent, and creative practice of engineering or other professional careers.
Graduates, within four years of graduation, should demonstrate sustained learning and adapting to a constantly changing field through graduate work, professional development, and self-study.
Graduates, within four years of graduation, should demonstrate leadership and initiative to ethically advance professional and organizational goals, facilitate the achievements of others, and obtain substantive results.
Graduates, within four years of graduation, should demonstrate a commitment to teamwork while working with others of diverse cultural and interdisciplinary backgrounds.

II. PROGRAM OUTCOMES (POs)

An ability to independently carry out research /investigation and development work to solve practical problems
An ability to write and present a substantial technical report/document
3. Students should be able to demonstrate a degree of mastery over the area as per the specialization of the program. The mastery should be at a level higher than the requirements in the appropriate bachelor program

Flexible choice based credit system

The learner can select the course he is interested to study during a semester. The course can be opted by the learner, with the prerequisite courses completed by the learner. For courses which do not have prerequisite, the learner can study the course in any semester, whenever its offered.

The learner should have earned the credits in each category namely HS, BS, ES, PC, PE, OE, MC to become eligible for the award of the degree.

III. CHOICE BASED CREDIT SYSTEM CURRICULUM SEMESTER I

S.No.	Course Code	Course Title	Category	Contact Periods	L	T	P	C
THEORY
1.	19MMA04	Applied Probability and Statistics	FC	4	4	0	0	4
2.	19MCS01	Advanced Data Structures and Algorithms	PC	4	4	0	0	4
3.	19MCS02	Advanced Computer Architecture	PC	3	3	0	0	3
4.	19MCS03	Operating System Internals	PC	3	3	0	0	3
5.	19MCS04	Advanced Software Engineering	PC	3	3	0	0	3
6.	19MCS05	Machine Learning Techniques	PC	3	3	0	0	3
PRACTICALS
7.	19MCS06	Data Structures Laboratory	PC	4	0	0	4	2
TOTAL				24	20	0	4	22

SEMESTER II

S.No.	Course Code	Course Title	Category	Contact Periods	L	T	P	C
THEORY
1.	19MCS07	Network Design and Technologies	PC	3	3	0	0	3
2.	19MCS08	Security Practices	PC	3	3	0	0	3
3.	19MCS09	Internet of Things	PC	3	3	0	0	3
4.	19MCS10	Big Data Analytics	PC	3	3	0	0	3
5.		Professional Elective –I	PE	3	3	0	0	3
6.		Professional Elective –II	PE	3	3	0	0	3
PRACTICALS
7.	19MCS11	Data Analytics Laboratory	PC	4	0	0	4	2
8.	19MCS12	Term Paper Writing and Seminar	EEC	2	0	0	2	1
TOTAL				24	18	0	6	21

SEMESTER III

S.No	Course Code	Course Title	Category	Contact Periods	L	T	P	C
THEORY
1.		Professional Elective –III	PE	3	3	0	0	3
2.		Professional Elective –IV	PE	3	3	0	0	3
3.		Professional Elective –V	PE	3	3	0	0	3
PRACTICALS
4.	19MCS13	Project Work Phase – I	EEC	12	0	0	12	6
TOTAL				21	9	0	12	15

SEMESTER IV

S.No	Course Code		Course Title	Category	Contact Periods	L	T	P	C
PRACTICALS
1.	19MCS14	Project Work Phase – II		EEC	24	0	0	24	12
TOTAL					24	0	0	24	12

TOTAL NO. OF CREDITS: 70

V. CATEGORIZATION OF COURSES

A. FOUNDATION COURSES (FC)

S.No.	Course Code	Course Title	Contact Hours Per Week			Credits	Prerequisite
			L	T	P
1.	19MMA04	Applied Probability and Statistics	4	0	0	4	NIL

B. PROFESSIONAL CORE (PC)

S.No.	Course Code	Course Title	Contact Hours Per Week			Credits	Prerequisite
S.No.	Course Code	Course Title	L	T	P	Credits	Prerequisite
1.	19MCS01	Advanced Data Structures and Algorithms	4	0	0	4	NIL
2.	19MCS02	Advanced Computer Architecture	3	0	0	3	NIL
3.	19MCS03	Operating System Internals	3	0	0	3	NIL
4.	19MCS04	Advanced Software Engineering	3	0	0	3	NIL
5.	19MCS05	Machine Learning Techniques	3	0	0	3	NIL
6.	19MCS06	Data Structures Laboratory	0	0	4	2	NIL
7.	19MCS07	Network Design and Technologies	3	0	0	3	NIL
8.	19MCS08	Security Practices	3	0	0	3	NIL
9.	19MCS09	Internet of Things	3	0	0	3	NIL
10.	19MCS10	Big Data Analytics	3	0	0	3	NIL
11.	19MCS11	Data Analytics Laboratory	0	0	4	2	NIL

C. EMPLOYABILITY ENHANCEMENT COURSE (EEC)

S.No.	Course Code	Course Title	Contact Hours Per Week			Credits	Prerequisite
S.No.	Course Code	Course Title	L	T	P	Credits	Prerequisite
1.	19MCS12	Term Paper and Seminar	0	0	2	1	NIL
2.	19MCS13	Project Work Phase – I	0	0	12	6	NIL
3.	19MCS14	Project Work Phase – II	0	0	24	12	NIL

D. PROFESSIONAL ELECTIVE COURSES (PE)

S.No.	Course Code	Course Title	Contact Hours Per Week			Credits	Prerequisite
S.No.	Course Code	Course Title	L	T	P	Credits	Prerequisite
1.	19MCS15	Advanced Databases	3	0	0	3	NIL
2.	19MCS16	Principles of Programming Languages	3	0	0	3	NIL
3.	19MCS17	Image Processing and Analysis	3	0	0	3	NIL
4.	19MCS18	Web Engineering	3	0	0	3	NIL
5.	19MCS19	Cloud Computing Technologies	3	0	0	3	NIL
6.	19MCS20	Real Time Systems	3	0	0	3	NIL
7.	19MCS21	Mobile and Pervasive Computing	3	0	0	3	NIL
8.	19MCS22	Parallel Programming Paradigms	3	0	0	3	NIL
9.	19MCS23	Information Retrieval Techniques	3	0	0	3	NIL
10.	19MCS24	Software Architectures and Design	3	0	0	3	NIL
11.	19MCS25	Performance Analysis of Computer Systems	3	0	0	3	NIL
12.	19MCS26	Language Technologies	3	0	0	3	NIL
13.	19MCS27	Computer Vision	3	0	0	3	NIL
14.	19MCN21	Speech Processing and Synthesis	3	0	0	3	NIL
15.	19MCS29	Software Quality Assurance and Testing	3	0	0	3	NIL
16.	19MCS30	Formal models of software systems	3	0	0	3	NIL
17.	19MCS31	Embedded Software Development	3	0	0	3	NIL
18.	19MCS32	Social Network Analysis	3	0	0	3	NIL
19.	19MCS33	Bio-inspired Computing	3	0	0	3	NIL
20.	19MCS34	Compiler Optimization Techniques	3	0	0	3	NIL
21.	19MCS35	Data Visualization Techniques	3	0	0	3	NIL
22.	19MCS36	Reconfigurable Computing	3	0	0	3	NIL
23.	19MCS37	Mobile Application Development	3	0	0	3	NIL
24.	19MCS38	Bio Informatics	3	0	0	3	NIL
25.	19MCS39	Information Storage Management	3	0	0	3	NIL
26.	19MCS40	Agile Methodologies	3	0	0	3	NIL

27.	19MCS41	Distributed Systems	3	3	NIL
28.	19MCS42	Knowledge Engineering	3	3	NIL
29.	19MCS43	Operations Research	3	3	NIL
30.	19MCS44	Research Methodologies	3	3	NIL
31.	19MMA05	Linear Algebra and Number Theory	3	3	NIL

CREDIT SUMMARY

Category	Credits	Credit%
Foundation Courses	4	5.7
Professional Core Courses	32	45.7
Professional Elective Courses	15	21.4
Employability Enhancement Courses	19	27.14
Total	70	100