M.Sc. (Computer Science)
M.Sc. Computer Science
About Programme
M.Sc. in Computer Science is a two-year post-graduate programme with the objective to develop human resources with core competence in various thrust areas of Computer Science. It will provide students with opportunities to develop and hone core competency in the field of computer science and encourage them to make a mark in the much sought-after IT industry. The Syllabus of this Course creates a unique identity for M.Sc. in Comp Science distinct from similar degrees in other related subjects, focuses on core Computer Science subjects, incorporate advanced and most recent trends, Identify and nurture research temper among students, Offer provision for internship with industry and Focus, as far as possible, only on open-source software.
Programme Outcome
Ø Comprehension of technical information from multimedia presentations (BTL: 1,2)
Ø Learn to grasp theoretical concepts and use modern tools and techniques (BSL: 3, 4)
Ø Incorporate productivity measurement and project planning tools for periodical self-assessment (BTL: 5)
Ø Develop and demonstrate leadership skills by taking advantage of assorted learning opportunities (BTL: 6)
Programme Sepcific Outcome
Ø Knowledge of the core subjects within computer science; Aptitude to employ computational skills so as to provide solutions to real-world problems; Up to date with technological trends (BTL: 1, 2, 3)
Ø Capability to join a team of IT solution providers, lead projects or launch start-ups; Ability to explore opportunities in research and academia (BTL: 4, 5, 6)
Ø Equipped with the required soft skills for professional development; Motivation for independent and life-long learning in computer science and allied fields (BTL: 1 to 6)
Eligibility
B.Sc. (Computer Science, IT, Mathematics, Physics, Statistics) / BCS / B.E. (Computer / IT)
Intake & Seats Reservation
Ø Intake: 200 Students.
Ø Reservation in Seats: Other University – 6 (3%)
Mumbai University – 194 (97%)
[GEN- 74 (38%); SC- 25 (13%); ST- 13 (7%);
DT (A)- 6 (3%); NT (B)- 5 (2.5%);
NT (C)- 7 (3.5%); NT(D)- 4 (2%); OBC- 37 (19%);
SBC- 4 (2%); EWS-19 (10%)]
Admission Process
Ø Admission will be made on purely merit basis.
Ø Documents along with application form:
(1) Application Fees Rs. 100.00
(2) FY, SY, TY Degree Marksheets
(3) Caste Certificate, if any
Ø Documents along with admission form:
(1) SSC, HSC, FY, SY, TY Degree Marksheets
(2) SSC School Leaving Certificate
(3) Aadhar Card
(4) Caste Certificate & Caste Validity, if any
Subjects and Evaluation
|
Paper Code |
Paper Name |
Credits |
Total Marks |
External (UA) |
Internal (CA) |
|||
|
Max Marks |
Min Marks |
Max Marks |
Min Marks |
Max Marks |
Min Marks |
|||
|
Semester-I |
|
|||||||
|
PSCS101 |
Algorithm for Optimization |
4 |
100 |
40 |
60 |
24 |
40 |
16 |
|
PSCS102 |
Software Defining Networking |
4 |
100 |
40 |
60 |
24 |
40 |
16 |
|
PSCS103 |
Applied Signal and Image Processing |
4 |
100 |
40 |
60 |
24 |
40 |
16 |
|
PSCS104 |
Advanced Database Techniques |
4 |
100 |
40 |
60 |
24 |
40 |
16 |
|
PSCSP101 |
Practical: Algorithm for Optimization |
2 |
50 |
20 |
50 |
20 |
- |
- |
|
PSCSP102 |
Practical: Software Defining Networking |
2 |
50 |
20 |
50 |
20 |
- |
- |
|
PSCSP103 |
Practical: Applied Signal & Image Processing |
2 |
50 |
20 |
50 |
20 |
- |
- |
|
PSCSP104 |
Practical: Advanced Database Techniques |
2 |
50 |
20 |
50 |
20 |
- |
- |
|
Total |
=SUM(ABOVE) 24 |
=SUM(ABOVE) 600 |
- |
=SUM(ABOVE) 440 |
- |
=SUM(ABOVE) 160 |
- |
|
|
Semester-II |
|
|||||||
|
PSCS201 |
Applied Machine and Deep Learning |
4 |
100 |
40 |
60 |
24 |
40 |
16 |
|
PSCS202 |
Natural Language Processing |
4 |
100 |
40 |
60 |
24 |
40 |
16 |
|
PSCS203 |
Web Mining |
4 |
100 |
40 |
60 |
24 |
40 |
16 |
|
PSCS204 |
Embedded and IoT Technology |
4 |
100 |
40 |
60 |
24 |
40 |
16 |
|
PSCSP201 |
Practical: Applied Machine & Deep Learning |
2 |
50 |
20 |
50 |
20 |
- |
- |
|
PSCSP202 |
Practical: Natural Language Processing |
2 |
50 |
20 |
50 |
20 |
- |
- |
|
PSCSP203 |
Practical: Web Mining |
2 |
50 |
20 |
50 |
20 |
- |
- |
|
PSCSP204 |
Practical: Embedded and IoT Technology |
2 |
50 |
20 |
50 |
20 |
- |
- |
|
Total |
=SUM(ABOVE) 24 |
=SUM(ABOVE) 600 |
- |
=SUM(ABOVE) 440 |
- |
=SUM(ABOVE) 160 |
- |
|
.