Overview
About the Program
Students undertaking the M.Sc. program in Computer Science at Mount Carmel College are trained to explore and acquire an in-depth understanding of the episteme – Computer Science. By putting in a conscious effort to impart knowledge about the field by reputed professors and lecturers, this program is designed to foster a culture wherein students’ talent is amplified with knowledge, technical training and guidance. MSc programme in Computer Science is designed to provide an insight into computing through advanced concepts, principles, strategies and skills supplemented with practical knowledge to effectively develop and work with a range of technologies to build systems and applications that help apply in real-time computing environments. The program combines strong fundamentals, projects, team-oriented activities, and soft skills, leading to a holistic education. This programme takes forward the knowledge gained by the students at the undergraduate level and provides them with an advanced level of learning and understanding on the subjects. Through rigorous evaluation patterns, our students are encouraged to put their skills to use and venture into the field of Computer Science by enhancing their critical thinking abilities and sensibilities. On acquiring knowledge of the qualitative and quantitative techniques as well as gaining an in-depth understanding of the field, Graduates of this degree will be able to demonstrate their skills in Python Programming, Data Mining, Artificial Intelligence etc. The Curricular and Extracurricular activities are designed in a way to ensure that the students receive a holistic understanding through the curriculum.
Head of Department
Dr. S Regina Lourdhu Suganthi
Associate Professor, M.Sc., M.Phil., PGDCA, MS in Software Systems, Ph.D.
Vision
Mission
Objectives:
The main objective of M.Sc. Computer Science is to enhance the skills of computer science enthusiasts in the various thrust areas of the field and provide them with the perfect amalgamation of theory as well as practical knowledge.
Programme Outcomes (PO):
PO1: Able to demonstrate a broad knowledge of Computer Science which includes File Structures, Computer Programming Skills, Computing Skills, Algorithm Design, Theory of Computation, Data Mining, Artificial Intelligence, Information Security
PO2: Demonstrate the ability to recognize, design and implement efficient software solutions to problems, communicate effectively and to work as a team
PO3: Demonstrate the ability to conduct a research or applied Computer Science projects, requiring writing and presentation skills which exemplify their skills in Computer Science
PO4: Write programs utilizing modern software tools, apply programming principles effectively and write procedural code to solve complex problems
PO5: Able to learn and adapt to new technologies and use it effectively for analyzing complex real-world problems and devise computer-based solutions
PO6: Retrieve, use and evaluate relevant professional information, apply research methods, techniques, and problem-solving approaches in the specialization areas
Program Specifications
- GENERAL STRUCTURE
M.Sc. Computer Science is a 2-year program catering to the needs of people interested in the field of computers. The duration of the course is two academic years consisting of four semesters. The first two semesters have four core courses of which three courses are coupled with lab modules and two allied courses. Community Development Programme is mandatory in the second semester to enable the students to be aware of socio-economic impacts. The third semester opens avenues for specialization by offering four elective courses of which three courses are associated with lab modules, one allied course and one open elective. This open elective course encourages students to interact with other disciplines. The fourth semester offers three elective courses and a project.
- PROGRAM REQUIREMENTS
Semester 1:
Four core courses of which three courses are coupled with lab modules PLUS two allied courses.
Semester 2:
Four core courses of which three courses are coupled with lab modules PLUS two allied courses. Community Development Programme is mandatory.
Data Science specific courses are offered in Semester 3 and Semester 4
Semester 3:
Four elective courses of which three courses are associated with lab modules PLUS one allied course, one open elective and an Internship.
Semester 4:
Three elective courses and one major project
Credits:
Each Core or Elective Course – 5 credits each,
Allied Course, Open Elective, Internship – 2 credits each
Elective paper with only theory component – 4 credits
Project – 8 credits.
- TESTING AND EVALUATION
The performance of the student will be assessed throughout the semester. Evaluations will be based on End Semester Examinations and Continuous Internal Assessment (CIA).
I Evaluation Procedure for core/ elective courses with practicals/ tutorials :
- Continuous Internal Assessment for theory (CIA) : 30 Marks
|
Two tests |
20 |
|
Assignments / Projects / Presentations |
10 |
|
Total |
30 |
- End Semester Examination for theory (ESE): 70 Marks
- Continuous Internal Assessment for Practical’s/ Tutorials (CIA): 15 Marks
|
Pre-final test |
10 |
|
Assignments / Projects / Presentations / Records |
5 |
|
Total |
15 |
- End Semester Examination for Practical’s/ Tutorials (ESE): 35 Marks
- Students should secure a paper minimum of 40% each in end semester theory and in theory total (CIA + ESE), End Semester practical examination and in practical total (CIA + ESE) and an aggregate of 50%
II Evaluation Procedure for core/elective courses without practical’s / tutorials :
- Continuous Internal Assessment for theory (CIA): 30 Marks
- End Semester Examination for theory (ESE): 70 Marks
III Evaluation Procedure for Allied Courses:
- Continuous Internal Assessment for theory (CIA): 15 Marks
- End Semester Examination for theory (ESE): 35 Marks
- Students should secure a paper minimum of 40% each in end semester theory and in theory total (CIA + ESE).
IV Evaluation for Practical Examination
Practical Examination Question Paper Pattern for 50 marks
Part – A: Three questions from the lab list of the subject to be given by the examiner and two questions will be answered and executed by the students of their choice.
Part – B: The mini project done by the student has to be demonstrated. An add-on module has to be given.
Scheme of Evaluation:
|
Part A |
|
|
Writing two Programs |
10 Marks |
|
Execution of Two programs |
20 Marks |
|
Viva-Voce |
05 Marks |
|
Part B |
|
|
Demo |
10 Marks |
|
Add- on |
05 Marks |
|
Total |
50 Marks |
Practical Examination Question Paper Pattern for 35 marks
Part – A: Three Questions from the lab list of the subject to be given by the examiner and two questions will be answered and executed by the students of their choice.
Scheme of Evaluation:
|
Part A |
|
|
Writing two Programs |
10 Marks |
|
Execution of Two programs |
20 Marks |
|
Viva-Voce |
05 Marks |
|
Total |
35 Marks |
V Evaluation Procedure for Project:
IV Semester Project:
- Continuous Internal Assessment (CIA) : 50 Marks
|
Review - I |
20 |
|
Review - II |
20 |
|
Guide Evaluation of work progress |
10 |
|
Total |
50 |
- End Semester Examination (ESE): 150 Marks
- Students should secure a paper minimum of 40% in end semester examination and in total (CIA+ ESE).
Syllabus
|
I SEMESTER |
|||||||
|
Sl. No. |
Course Code |
Name of the Course |
LTP |
Credits |
CIA Marks |
ESE |
Total |
|
Marks |
|||||||
|
1 |
MCS1FSCCC-01 |
File Structures |
4:0:2 |
5 |
30+15 |
70+35 |
150 |
|
2 |
MCS1TCCC-02 |
Theory of Computation |
4:2:0 |
5 |
30+15 |
70+35 |
150 |
|
3 |
MCS1ADBMSCC-03 |
Advanced DBMS |
4:0:2 |
5 |
30+15 |
70+35 |
150 |
|
4 |
MCS1AJPCC-04 |
Advanced Java Programming |
3:0:4 |
5 |
30+15 |
70+35 |
150 |
|
5 |
MCS1PPAC-01 |
Python Programming |
0:0:4 |
2 |
15 |
35 |
50 |
|
6 |
MCS1TCSAC-02 |
Technical and Communication Skills |
2:0:0 |
2 |
15 |
35 |
50 |
|
Total |
|
24 |
|
|
700 |
||
|
II SEMESTER |
|||||||
|
Sl. No. |
Course Code |
Name of the Course |
LTP |
Credits |
CIA Marks |
ESE |
Total |
|
Marks |
|||||||
|
1 |
MCS2DMTCC-05 |
Data Mining Techniques |
4:0:2 |
5 |
30+15 |
70+35 |
150 |
|
2 |
MCS2AICC-06 |
Artificial Intelligence |
4:2:0 |
5 |
30+15 |
70+35 |
150 |
|
3 |
MCS2AACC-07 |
Advanced Algorithms |
4:0:2 |
5 |
30+15 |
70+35 |
150 |
|
4 |
MCS2WTCC-08 |
Web Technology |
3:0:4 |
5 |
30+15 |
70+35 |
150 |
|
5 |
MCS2MADAC-03 |
Mobile Application Development |
0:0:4 |
2 |
15 |
35 |
50 |
|
6 |
MCS2RMAC-04 |
Research Methodology |
2:0:0 |
2 |
15 |
35 |
50 |
|
7 |
MCS2CDP |
Community Development Programme |
|
2 |
|
50 |
50 |
|
|
Total |
|
26 |
|
|
750 |
|
|
III SEMESTER |
|||||||
|
Sl. No. |
Course Code |
Name of the Course |
LTP |
Credits |
CIA Marks |
ESE |
Total |
|
Marks |
|||||||
|
1 |
MCS3SDSEC-01 |
Statistics for Data Science |
4:2:0 |
5 |
30+15 |
70+35 |
150 |
|
2 |
MCS3MLEC-02 |
Machine Learning |
3:0:4 |
5 |
30+15 |
70+35 |
150 |
|
3 |
MCS3CCDEC-03 |
Cloud Computing for Data Science |
4:0:2 |
5 |
30+15 |
70+35 |
150 |
|
4 |
MCS3BDAEC-04 |
Big Data Analytics |
4:0:2 |
5 |
30+15 |
70+35 |
150 |
|
5 |
MCS3DVTAC-05 |
Data Visualization Techniques |
2:0:0 |
2 |
15 |
35 |
50 |
|
6 |
OE |
Open elective |
2:0:0 |
2 |
15 |
35 |
50 |
|
7 |
|
Internship Report |
|
2 |
|
50 |
50 |
|
8 |
Total |
31 |
26 |
|
|
750 |
|
|
IV SEMESTER |
|||||||
|
Sl. No. |
Course Code |
Name of the Course |
LTP |
Credits |
CIA Marks |
ESE |
Total Marks |
|
1 |
MCS4AMLEC-05 |
Advanced Machine Learning |
3:0:4 |
5 |
30+15 |
70+35 |
150 |
|
2 |
MCS4OTEC-06 |
Optimization Techniques |
4:2:0 |
5 |
30+15 |
70+35 |
150 |
|
3 |
MCS4IOTEC-07 |
Internet of Things |
4:0:0 |
4 |
30 |
70 |
100 |
|
4 |
PR-01 |
Project / Viva Voce |
12 |
8 |
50 |
150 |
200 |
|
22 |
600 |
||||||
|
Total (Semester I to IV) |
98 |
2800 |
|||||
Career Prospects
Upon the successful completion of M.Sc. Computer Science program, one can find lucrative career opportunities in Software and Computer Hardware related industry. An M.Sc. Computer Science degree mostly helps in acquiring a job position in the IT sector. The IT and ITeS sector has been one of the top employment sectors in India in the past and continues to do so. Current trends show that the sector will increase to grow at a good rate annually. With an expansion in the sector, the employment opportunities are also expected to increase. This estimates a good career prospect for M.Sc. Computer Science graduate.
The college has an active placement cell which:
- Provides Campus Recruitment Training to hone their skills of both aptitude tests and interview
- Arranges prominent companies in the city to conduct interviews in the college
Highlights
- Guest Lectures on various technical and non-technical topics are conducted every week to upgrade their Technical, Social and interpersonal skills
- Orientation Programme is conducted for freshers enumerating all the rules and regulations of the college and thus educating them about the Campus culture
- Overview
-
Overview
About the Program
Students undertaking the M.Sc. program in Computer Science at Mount Carmel College are trained to explore and acquire an in-depth understanding of the episteme – Computer Science. By putting in a conscious effort to impart knowledge about the field by reputed professors and lecturers, this program is designed to foster a culture wherein students’ talent is amplified with knowledge, technical training and guidance. MSc programme in Computer Science is designed to provide an insight into computing through advanced concepts, principles, strategies and skills supplemented with practical knowledge to effectively develop and work with a range of technologies to build systems and applications that help apply in real-time computing environments. The program combines strong fundamentals, projects, team-oriented activities, and soft skills, leading to a holistic education. This programme takes forward the knowledge gained by the students at the undergraduate level and provides them with an advanced level of learning and understanding on the subjects. Through rigorous evaluation patterns, our students are encouraged to put their skills to use and venture into the field of Computer Science by enhancing their critical thinking abilities and sensibilities. On acquiring knowledge of the qualitative and quantitative techniques as well as gaining an in-depth understanding of the field, Graduates of this degree will be able to demonstrate their skills in Python Programming, Data Mining, Artificial Intelligence etc. The Curricular and Extracurricular activities are designed in a way to ensure that the students receive a holistic understanding through the curriculum.
Head of Department
Dr. S Regina Lourdhu Suganthi
Associate Professor, M.Sc., M.Phil., PGDCA, MS in Software Systems, Ph.D.Vision
Mission
Objectives:
The main objective of M.Sc. Computer Science is to enhance the skills of computer science enthusiasts in the various thrust areas of the field and provide them with the perfect amalgamation of theory as well as practical knowledge.
Programme Outcomes (PO):
PO1: Able to demonstrate a broad knowledge of Computer Science which includes File Structures, Computer Programming Skills, Computing Skills, Algorithm Design, Theory of Computation, Data Mining, Artificial Intelligence, Information Security
PO2: Demonstrate the ability to recognize, design and implement efficient software solutions to problems, communicate effectively and to work as a team
PO3: Demonstrate the ability to conduct a research or applied Computer Science projects, requiring writing and presentation skills which exemplify their skills in Computer Science
PO4: Write programs utilizing modern software tools, apply programming principles effectively and write procedural code to solve complex problems
PO5: Able to learn and adapt to new technologies and use it effectively for analyzing complex real-world problems and devise computer-based solutions
PO6: Retrieve, use and evaluate relevant professional information, apply research methods, techniques, and problem-solving approaches in the specialization areas
- Program Specifications
-
Program Specifications
- GENERAL STRUCTURE
M.Sc. Computer Science is a 2-year program catering to the needs of people interested in the field of computers. The duration of the course is two academic years consisting of four semesters. The first two semesters have four core courses of which three courses are coupled with lab modules and two allied courses. Community Development Programme is mandatory in the second semester to enable the students to be aware of socio-economic impacts. The third semester opens avenues for specialization by offering four elective courses of which three courses are associated with lab modules, one allied course and one open elective. This open elective course encourages students to interact with other disciplines. The fourth semester offers three elective courses and a project.
- PROGRAM REQUIREMENTS
Semester 1:
Four core courses of which three courses are coupled with lab modules PLUS two allied courses.
Semester 2:
Four core courses of which three courses are coupled with lab modules PLUS two allied courses. Community Development Programme is mandatory.
Data Science specific courses are offered in Semester 3 and Semester 4
Semester 3:
Four elective courses of which three courses are associated with lab modules PLUS one allied course, one open elective and an Internship.
Semester 4:
Three elective courses and one major project
Credits:
Each Core or Elective Course – 5 credits each,
Allied Course, Open Elective, Internship – 2 credits each
Elective paper with only theory component – 4 credits
Project – 8 credits.
- TESTING AND EVALUATION
The performance of the student will be assessed throughout the semester. Evaluations will be based on End Semester Examinations and Continuous Internal Assessment (CIA).
I Evaluation Procedure for core/ elective courses with practicals/ tutorials :
- Continuous Internal Assessment for theory (CIA) : 30 Marks
Two tests
20
Assignments / Projects / Presentations
10
Total
30
- End Semester Examination for theory (ESE): 70 Marks
- Continuous Internal Assessment for Practical’s/ Tutorials (CIA): 15 Marks
Pre-final test
10
Assignments / Projects / Presentations / Records
5
Total
15
- End Semester Examination for Practical’s/ Tutorials (ESE): 35 Marks
- Students should secure a paper minimum of 40% each in end semester theory and in theory total (CIA + ESE), End Semester practical examination and in practical total (CIA + ESE) and an aggregate of 50%
II Evaluation Procedure for core/elective courses without practical’s / tutorials :
- Continuous Internal Assessment for theory (CIA): 30 Marks
- End Semester Examination for theory (ESE): 70 Marks
III Evaluation Procedure for Allied Courses:
- Continuous Internal Assessment for theory (CIA): 15 Marks
- End Semester Examination for theory (ESE): 35 Marks
- Students should secure a paper minimum of 40% each in end semester theory and in theory total (CIA + ESE).
IV Evaluation for Practical Examination
Practical Examination Question Paper Pattern for 50 marks
Part – A: Three questions from the lab list of the subject to be given by the examiner and two questions will be answered and executed by the students of their choice.
Part – B: The mini project done by the student has to be demonstrated. An add-on module has to be given.
Scheme of Evaluation:
Part A
Writing two Programs
10 Marks
Execution of Two programs
20 Marks
Viva-Voce
05 Marks
Part B
Demo
10 Marks
Add- on
05 Marks
Total
50 Marks
Practical Examination Question Paper Pattern for 35 marks
Part – A: Three Questions from the lab list of the subject to be given by the examiner and two questions will be answered and executed by the students of their choice.
Scheme of Evaluation:
Part A
Writing two Programs
10 Marks
Execution of Two programs
20 Marks
Viva-Voce
05 Marks
Total
35 Marks
V Evaluation Procedure for Project:
IV Semester Project:
- Continuous Internal Assessment (CIA) : 50 Marks
Review - I
20
Review - II
20
Guide Evaluation of work progress
10
Total
50
- End Semester Examination (ESE): 150 Marks
- Students should secure a paper minimum of 40% in end semester examination and in total (CIA+ ESE).
- Syllabus
-
Syllabus
I SEMESTER
Sl. No.
Course Code
Name of the Course
LTP
Credits
CIA Marks
ESE
Total
Marks
1
MCS1FSCCC-01
File Structures
4:0:2
5
30+15
70+35
150
2
MCS1TCCC-02
Theory of Computation
4:2:0
5
30+15
70+35
150
3
MCS1ADBMSCC-03
Advanced DBMS
4:0:2
5
30+15
70+35
150
4
MCS1AJPCC-04
Advanced Java Programming
3:0:4
5
30+15
70+35
150
5
MCS1PPAC-01
Python Programming
0:0:4
2
15
35
50
6
MCS1TCSAC-02
Technical and Communication Skills
2:0:0
2
15
35
50
Total
24
700
II SEMESTER
Sl. No.
Course Code
Name of the Course
LTP
Credits
CIA Marks
ESE
Total
Marks
1
MCS2DMTCC-05
Data Mining Techniques
4:0:2
5
30+15
70+35
150
2
MCS2AICC-06
Artificial Intelligence
4:2:0
5
30+15
70+35
150
3
MCS2AACC-07
Advanced Algorithms
4:0:2
5
30+15
70+35
150
4
MCS2WTCC-08
Web Technology
3:0:4
5
30+15
70+35
150
5
MCS2MADAC-03
Mobile Application Development
0:0:4
2
15
35
50
6
MCS2RMAC-04
Research Methodology
2:0:0
2
15
35
50
7
MCS2CDP
Community Development Programme
2
50
50
Total
26
750
III SEMESTER
Sl. No.
Course Code
Name of the Course
LTP
Credits
CIA Marks
ESE
Total
Marks
1
MCS3SDSEC-01
Statistics for Data Science
4:2:0
5
30+15
70+35
150
2
MCS3MLEC-02
Machine Learning
3:0:4
5
30+15
70+35
150
3
MCS3CCDEC-03
Cloud Computing for Data Science
4:0:2
5
30+15
70+35
150
4
MCS3BDAEC-04
Big Data Analytics
4:0:2
5
30+15
70+35
150
5
MCS3DVTAC-05
Data Visualization Techniques
2:0:0
2
15
35
50
6
OE
Open elective
2:0:0
2
15
35
50
7
Internship Report
2
50
50
8
Total
31
26
750
IV SEMESTER
Sl. No.
Course Code
Name of the Course
LTP
Credits
CIA Marks
ESE
Total
Marks
1
MCS4AMLEC-05
Advanced Machine Learning
3:0:4
5
30+15
70+35
150
2
MCS4OTEC-06
Optimization Techniques
4:2:0
5
30+15
70+35
150
3
MCS4IOTEC-07
Internet of Things
4:0:0
4
30
70
100
4
PR-01
Project / Viva Voce
12
8
50
150
200
22
600
Total (Semester I to IV)
98
2800
- Career Prospects
-
Career Prospects
Upon the successful completion of M.Sc. Computer Science program, one can find lucrative career opportunities in Software and Computer Hardware related industry. An M.Sc. Computer Science degree mostly helps in acquiring a job position in the IT sector. The IT and ITeS sector has been one of the top employment sectors in India in the past and continues to do so. Current trends show that the sector will increase to grow at a good rate annually. With an expansion in the sector, the employment opportunities are also expected to increase. This estimates a good career prospect for M.Sc. Computer Science graduate.
The college has an active placement cell which:
- Provides Campus Recruitment Training to hone their skills of both aptitude tests and interview
- Arranges prominent companies in the city to conduct interviews in the college
- Highlights
-
Highlights
- Guest Lectures on various technical and non-technical topics are conducted every week to upgrade their Technical, Social and interpersonal skills
- Orientation Programme is conducted for freshers enumerating all the rules and regulations of the college and thus educating them about the Campus culture