*in the first semester, a pre-PhD student hasto take three courses fromthe list of courses offeredby the department based on the expertise of the available faculty members. Also, the above list maybeupdatedfromtimetotimesubjectto theapprovaloftheBoardofStudiesoftheFaculty.
**onlyfornon-SAUstudents
Course Structure
PREAMBLE
The proposed M.Sc. (Computer Science) programme (two years), M.Tech. (Computer Science) programme (two years), and integrated M.Sc. + M.Tech. (Computer Science) programme (three years) have been designed to keep pace with the rapid developments in field of Computer Science and to cater the requirements of the SARRAC countries as well as the aspirations of students. The integrated programme is flexible with multiple entry and exit options for the students, as shown in Figure 1, to cater diverse academic structures across the SAARC countries. The proposed integrated M.Sc. + M.Tech. (Computer Science) programme is one of the unique curricula offered by some of the universities in the SAARC region. The salient features of the aforesaid programmes are outlined below:
The students with three years of bachelor’s degree are eligible to apply either for two years M.Sc. (Computer Science) programme or three years integrated M.Sc. + M.Tech. (Computer Science) programme.
The students with four years bachelor’s degree are eligible to apply for two years M.Tech. (Computer Science) programme.
The students entering into the integrated programme will have an option to exit the programme with M.Sc. (Computer Science) degree after two years; or, they can opt to continue with one more year and exit with integrated M.Sc.+ M.Tech. (Computer Science) degree.
At most 5 students of M.Sc. (Computer Science) programme satisfying minimum CGPA criteria decided by the department will be offered an option to switch to integrated M.Sc.+M.Tech. (Computer Science) programme in the beginning of second year.
The students may complete the programme without any specialization, or they can opt any of the two specializations viz. Artificial Intelligence & Machine Learning and Advanced Networks & Systems. For specialization, besides studying the specialized courses, the students will have to do their projects/dissertations in the area of specialization.
Admission to M.Tech. programme is either through merit list based on GATE (conducted by IITs) scores or merit list based on marks in SAU entrance examination.
Admission to M.Sc. programme and integrated M.Sc. + M.Tech. programme is through SAU entrance examination. There is a common application form for M.Sc. and integrated M.Sc. + M.Tech. programmes. The students can provide their preferences for both the programmes in the application form. There is the same question paper in the entrance examination for both the programmes. Separate merit lists will be prepared for both programmes based on the students preferences and the marks obtained in SAU entrance examination. In case a seat becomes vacant after withdrawal of admission by a student, the next student will be automatically switched from one programme to another based on the preference given by student in the application form and marks in the entrance examination, and/or next student from the waiting list will be offered admission.
The grade requirement for promotion to next semester as well as for the award of the degree, repetition of a course, extra semester to clear backlog etc. are as per university regulations/byelaws.
SUMMARY OF THE PROGRAMMES
Name of the programme
Duration
Number of seats
M. Sc. (Computer Science)
2 years (4 semesters)
20
M. Tech. (Computer Science)
2 years (4 semesters)
30
Integrated M.Sc. + M.Tech. (Computer Science)
3 years (6 semesters)
20
The entry and exit schemes of the proposed programmes are summarized in Figure 1.
MINIMUM ELIGIBILITY CRITERIA
In order to be eligible for admission to these programmes, an applicant must satisfy following criterion:
M.Sc. (Computer Science) Programme
A 3 or 4-year Bachelor’s degree in Computer Science or a relevant area* with mathematics as a subject either at the Bachelor’s level or at the 10+2 (12th class) level from an institution recognised by the government of any of the SAARC countries with a minimum of 55% marks in the aggregate or an equivalent grade. Candidates who have a 2-year Bachelor’s degree and have cleared the first year of the Master’s programme are also eligible.
M.Tech. (Computer Science) Programme
A 4-year B.Tech./B.E./BSc. (Engg.)/BS degree in Computer Science and Engineering or a relevant area* from an institution recognised by the government of any of the SAARC countries with a minimum of 55% marks in the aggregate or an equivalent grade.
OR
A Master’s degree in Computer Science/ Computer Applications/ Mathematics/ Operational Research/ Statistics/ Electronics/ Information Technology/ Physics an institution recognised by the government of any of the SAARC countries with a minimum of 55% marks in the aggregate or an equivalent grade level.
A 3 or 4-year Bachelor’s degree in Computer Science or a relevant area* with mathematics as a subject either at the Bachelor’s level or at the 10+2 (12th class) level from an institution recognised by the government of any of the SAARC countries with a minimum of 55% marks in the aggregate or an equivalent grade. Candidates who have a 2-year Bachelor’s degree and have cleared the first year of the Master’s programme are also eligible.
*Indicative List of Relevant Areas:
Computer Science and Engineering
Computer Engineering
Computer Applications
Information Technology
Any other Science/Engineering areas having at least one-fifth Computer Science courses
SPECIALIZATION
With an objective to address the emerging global technological challenges, the programmes offer options to students to acquire skills and excellence in the following specific areas:
Artificial Intelligence & Machine Learning
Advanced Networks & Systems
The students can either choose to get the respective degree without specialization or with specialization.
The students admitted in the M.Tech. (Computer Science) programme are required to submit their choice of degree with specialization or degree without specialization before the beginning of the first semester. In case a student opts for degree with specialization, then he/she also needs to select one of the above-mentioned areas of specialization before the beginning of the first semester.
The students admitted in the M.Sc. (Computer Science) and integrated M.Sc. + M.Tech. (Computer Science) programme are required to submit their choice of degree with specialization or degree without specialization before the beginning of the third semester. In case a student opts for a degree with specialization, then he/she also needs to select one of the above-mentioned areas of specialization before the beginning of third semester.
CATEGORIZATION OF COURSES
The following categories of courses will be taught in the Master’s programmes:
Hard Core (HC) Courses: These are core courses that will be compulsorily studied by the students as a core requirement to complete the requirements of the respective degree.
Soft Core (SC) Courses: These are electives courses related to the discipline or specialization in the programme and hence are mandatory for qualifying the eligibility for the specialization.
Specialized Elective (SE) Courses: These are optional courses offered in the areas of specialization.
General Elective (GE) Courses: These are optional courses that can be chosen by students who do not opt for any specialization. A SC or SE course can also be GE.
Open Elective (OE) Courses: These are the relevant optional courses that can be chosen from the other departments in the university.
PROGRAMME STRUCTURES
The programme structures along with credit distribution of courses are summarized in Tables 1 to 5.
Specialization in Artificial Intelligence & Machine Learning
SC
Fundamentals of Artificial Intelligence
SC 501
3-1-0
4
SC
Fundamentals of Machine Learning
SC 502
3-0-2
4
SE**
Specialized Elective 1
–
–
4
SE**
Specialized Elective 2
–
–
4
Specialization in Advanced Networks and Systems
SC
Wireless and Mobile Networks
SC 503
3-1-0
4
SC
Advanced Internet Protocols
SC 504
3-1-0
4
SE**
Specialized Elective 1
–
–
4
SE**
Specialized Elective 2
–
–
4
Non- specialization
GE***
General Elective 1
–
–
4
GE***
General Elective 2
–
–
4
GE***
General Elective 3
–
–
4
GE***
General Elective 4
–
–
4
4th
Project****
–
–
20
Total
82
Note: * The credit will not be included in the CGPA.
**The SE courses are to be chosen from the specialization buckets as shown in Table 2. These courses will be floated by the department as per the availability of faculties.
***The SC courses will be GE courses for students not opting for specialization.
****The project can be done in industry or under the supervision of faculty of the department.
The students choosing specialization must take SE courses from the buckets given in Table 2. All SC and SE courses will be GE courses for students opting for degree without specialization. The course codes and credits of SE and GE courses are shown in Table 2.
TABLE 2: LIST OF SE AND GE COURSES
Course Type
Course Title
Course Code
L-T-P
Credits
Specialization in Artificial Intelligence & Machine Learning
SE
Natural Language Processing
SE 501
3-1-0
4
SE
Evolutionary Algorithms
SE 502
3-0-2
4
SE
Information Retrieval
SE 503
3-1-0
4
SE
Reinforcement Learning
SE 504
3-0-2
4
SE
Big Data Analytics
SE 505
3-0-2
4
SE
Social Media Analytics
SE 506
3-1-0
4
SE
Network Science
SE 507
3-1-0
4
SE
AI and ML Techniques for Cyber Security
SE 508
3-1-0
4
SE
Computational Intelligence
SE 509
3-0-2
4
Specialization in Advanced Networks & Systems
SE
Optical Networks
SE 521
3-1-0
4
SE
Linear Programming for Computer Networks
SE 522
3-1-0
4
SE
Internet of Things
SE 523
3-1-0
4
SE
Cloud Computing
SE 524
3-1-0
4
SE
Software Defined Networking
SE 525
3-1-0
4
SE
Cryptography and Network Security
SE 526
3-1-0
4
SE
Blockchain Technology
SE 527
3-1-0
4
SE
Performance Modeling of Computer Networks
SE 528
3-1-0
4
Courses for Non-specialization
GE
Distributed Machine Learning
GE 531
3-1-0
4
GE
Embedded Systems Design
GE 532
3-1-0
4
SE
Fuzzy Modelling
GE 533
3-1-0
4
GE
Real-Time Systems
GE 534
3-1-0
4
GE
Mobile Computing
GE 535
3-1-0
4
GE
Queueing Theory with Applications
GE 536
3-1-0
4
GE
Soft Computing
GE 537
3-1-0
4
Remark: The SE courses will be GE courses for students not opting for specialization. Besides above-listed courses, new SE or GE courses may be offered after approval by the BoS.
Specialization in Artificial Intelligence & Machine Learning
SC
Fundamentals of Artificial Intelligence
SC 501
3-1-0
4
SC
Fundamentals of Machine Learning
SC 502
3-0-2
4
Specialization in Advanced Networks & Systems
SC
Wireless and Mobile Networks
SC 503
3-1-0
4
SC
Advanced Internet Protocols
SC 504
3-1-0
4
Non- specialization
GE*
General Elective 1
–
–
4
GE*
General Elective 2
–
–
4
2nd
HC
Advanced Computer Architecture
HC 504
3-1-0
4
HC
Introduction to South Asia
–
2-0-0
2
OE**
Academic Reading and Writing
–
2-0-0
2
Specialization in Artificial Intelligence & Machine Learning
SC
Computational Intelligence
SC 505
3-0-2
4
SC
Deep Learning
SC 506
3-0-2
4
SE***
Soft Elective 1
–
–
4
SE***
Soft Elective 2
–
–
4
Specialization in Advanced Networks & Systems
SC
Performance Modeling of Computer Networks
SC 507
3-1-0
4
SC
Distributed Systems
SC 508
3-1-0
4
SE***
Specialized Elective 1
–
–
4
SE***
Specialized Elective 2
–
–
4
Non-specialization
GE*
General Elective 3
–
–
4
GE*
General Elective 4
–
–
4
GE*
General Elective 5
–
–
4
GE*
General Elective 6
–
–
4
Second
3rd
–
Dissertation (Part-I)
–
–
16
4th
–
Dissertation (Part-II)
–
–
24
Total
82
Note: * The SC courses will be GE courses for students not opting for specialization.
** The credit will not be included in the CGPA.
***The SE courses are to be chosen from the specialization buckets as shown in Table 5. These courses will be floated by the department as per the availability of faculties.
Specialization in Artificial Intelligence & Machine Learning
SC
Fundamentals of Artificial Intelligence
SC 501
3-1-0
4
SC
Fundamentals of Machine Learning
SC 502
3-0-2
4
Specialization in Advanced Networks & Systems
SC
Wireless and Mobile Networking
SC 503
3-1-0
4
SC
Advanced Internet Protocols
SC 504
3-1-0
4
Non- specialization
GE*
General Elective 1
–
–
4
GE*
General Elective 2
–
–
4
4th
HC
Advanced Computer Architecture
HC 504
3-1-0
4
HC
Introduction to South Asia
–
2-0-0
2
OE**
Academic Reading and Writing
–
2-0-0
2
Specialization in Artificial Intelligence & Machine Learning
SC
Computational Intelligence
SC 505
3-0-2
4
SC
Deep Learning
SC 506
3-0-2
4
SE***
Specialized Elective 1
–
–
4
SE***
Specialized Elective 2
–
–
4
Specialization in Advanced Networks & Systems
SC
Performance Modeling of Computer Networks
SC 507
3-1-0
4
SC
Distributed Systems
SC 508
3-1-0
4
SE***
Specialized Elective 1
–
–
4
SE***
Specialized Elective 2
–
–
4
Non-specialization
GE*
General Elective 3
–
–
4
GE*
General Elective 4
–
–
4
GE*
General Elective 5
–
–
4
GE*
General Elective 6
–
–
4
Third
5th
–
Dissertation (Part I)
–
–
16
6th
–
Dissertation (Part II)
–
–
24
Total
122
Note:
* The SC courses will be GE courses for students not opting for specialization.
** The credit will not be included in the CGPA.
***The SE courses are to be chosen from the specialization buckets as shown in Table 5. These courses will be floated by the department as per the availability of faculties.
The students choosing specialization must take SE courses from the buckets given in Table 5. All SC and SE courses will be GE courses for students opting for degree without specialization. The course codes and credits of SE and GE courses are shown in Table 5.
TABLE 5: SE AND GE COURSES
Course Type
Course Title
Course Code
L-T-P
Credits
Specialization in Artificial Intelligence & Machine Learning
SE
Natural Language Processing
SE 501
3-1-0
4
SE
Evolutionary Algorithms
SE 502
3-0-2
4
SE
Information Retrieval
SE 503
3-1-0
4
SE
Reinforcement Learning
SE 504
3-0-2
4
SE
Big Data Analytics
SE 505
3-0-2
4
SE
Social Media Analytics
SE 506
3-1-0
4
SE
Network Science
SE 507
3-1-0
4
SE
AI and ML Techniques for Cyber Security
SE 508
3-1-0
4
SE
Advanced Machine Learning
SE 510
3-0-2
4
Specialization in Advanced Network & Systems
SE
Optical Networks
SE 521
3-1-0
4
SE
Linear Programming for Computer Networks
SE 522
3-1-0
4
SE
Internet of Things
SE 523
3-1-0
4
SE
Cloud Computing
SE 524
3-1-0
4
SE
Software Defined Networking
SE 525
3-1-0
4
SE
Cryptography and Network Security
SE 526
3-1-0
4
SE
Blockchain Technology
SE 527
3-1-0
4
Courses for Non-specialization
GE
Distributed Machine Learning
GE 531
3-1-0
4
GE
Embedded Systems Design
GE 532
3-1-0
4
GE
Fuzzy Modelling
GS 533
3-1-0
4
GE
Real-Time Systems
GE 534
3-1-0
4
GE
Mobile Computing
GE 535
3-1-0
4
GE
Queueing Theory with Applications
GE 536
3-1-0
4
GE
Soft Computing
GE 537
3-0-2
4
Remark: The SE courses will be GE courses for students not opting for specialization. Besides above-listed courses, new SE or GE courses may be offered after approval of the BoS.
Course Structure
COURSE STRUCTURE* FOR 5-YEAR B.TECH – M.TECH (CSE) DEGREE
(*Subject to further re-organization/updation/revision based on experts’ feedback)
PREAMBLE
With an objective to prepare learned and skilled professionals for SAARC countries having strong conceptual and practical background, a dual degree B.Tech – M.Tech (Computer Science and Engineering) programme of five years duration is offered. The salient features of the programme are:
The programme is unique in SAARC countries except India. It saves one year of student is obtaining M.Tech degree.
The programme provides an exit option to students with B.Tech (Computer Science and Engineering) degree after successful completion of 4th year. The students has to submit the choice to exit the programme at the end of sixth semester.
The total number of seats in the programme is 30.
The grade requirement for promotion to next semester as well as for the award of the degree, repetition of a course, extra semester to clear backlog etc. are as per university regulations/byelaws.
The University follows a unique up-to-date curriculum with the aim of equipping students with strong analytical and technical skills as well as thorough knowledge of and expertise in the latest state-of-the art techniques in Computer Science as well as in the interdisciplinary disciplines so that they can work competently in diverse areas including industry, teaching and research and development. Besides having a good mix of theoretical and lab-oriented computer science courses together with a reasonable amount of training/learning in the interdisciplinary domains, the Dual Degree B.Tech.-M.Tech (Computer Science and Engineering) programme has a project component which also provides an opportunity to students to work on research problems under the close supervision of faculty members so that they are equipped to work in leading industries, international R&D institutions or pursue a career in top-ranking academia towards higher education and research.
MINIMUM ELIGIBILITY CRITERIA
A student must have passed the Class 12 or Higher Secondary or any equivalent qualifying examination in Science stream (having Mathematics and Physics/Chemistry as mandatory subjects) with a minimum of 65% marks in aggregate based on education board recognized by any of the SAARC nations.
SELECTION PROCESS
The following admission process is adopted:
Route 1: Merit list based on JEE Main (conducted by IITs) scores.
Route 2: Merit list based on entrance examination conducted by SAU.
Semester-I
S.No.
Code
CourseTitle
ContactPeriodsperWeek
Credit
L
T
P
Total
1
CSE 101
Computational Thinking
3
0
4
7
5
2
MT 101
Advanced Calculus
3
1
0
4
4
3
PH 101
Engineering Physics
3
0
4
7
5
4
EN 101
English-I
3
1
0
3
4
5
HS 101
Introduction to South Asia
2
0
0
2
2
Total
14
2
8
23
20
Semester-II
S.No.
Code
CourseTitle
ContactPeriodsperWeek
Credit
L
T
P
Total
1
CSE 102
Data Structures
3
0
4
7
5
2
CSE 103
Digital Logic Design
3
0
4
7
5
3
MT 102
Linear Algebra and Optimization
3
1
0
4
4
4
EN 102
English-II (Language Lab)
2
0
0
2
2
5
HS 102
HSS-I
3
1
0
4
4
Total
14
2
8
24
20
Semester-III
S.No.
Code
CourseTitle
ContactPeriodsperWeek
Credit
L
T
P
Total
1
CSE 201
Object Oriented Programming
3
0
4
7
5
2
CSE 202
Computer Architecture
3
0
4
7
5
3
MT 201
Introduction to Probability Theory
3
1
0
4
4
4
MT 202
Discrete Mathematics
3
1
0
4
4
5
HS 201
HSS-II
3
1
0
4
4
Total
15
3
8
26
22
Semester-IV
S.No.
Code
CourseTitle
ContactPeriodsperWeek
Credit
L
T
P
Total
1
CSE 203
Operating Systems
3
0
4
7
5
2
CSE 204
Design and Analysis of Algorithms
3
1
2
6
5
3
CSE 205
Introduction to Artificial Intelligence
3
0
2
5
4
4
MT 203
Fundamentals of Data Science and Statistics
3
1
0
4
4
5
HS 202
HSS-III
3
1
0
4
4
Total
15
3
8
26
22
Semester-V
S.No.
Code
CourseTitle
ContactPeriodsperWeek
Credit
L
T
P
Total
1
CSE 301
Computer Networks
3
0
4
7
5
2
CSE 302
Machine Learning
3
1
2
6
5
3
CSE 303
Database Management Systems
3
0
4
7
5
4
CSE 304
Software Engineering
3
1
0
4
4
5
HS 301
HSS-IV
3
1
0
4
4
Total
15
3
10
28
23
Semester-VI
S.No.
Code
CourseTitle
ContactPeriodsperWeek
Credit
L
T
P
Total
1
CSE 305
Distributed Systems
3
1
2
6
5
2
CSE 306
Project (Application Development)
1
0
6
7
4
3
CSE XXXX
Departmental Elective I
4
4
CSE XXXX
Departmental Elective II
4
5
OE XXXX
Open Elective I
4
Total
21
Semester-VII
S.No.
Code
CourseTitle
ContactPeriodsperWeek
Credit
L
T
P
Total
1
CSE 401
Advanced Algorithm
3
1
2
6
5
2
CSE 402
Advanced Computer Networks
3
1
2
6
5
3
CSE XXXX
Departmental Elective III
4
4
CSE XXXX
Departmental Elective IV
4
5
OE XXXX
Mini Project
4
Total
22
Semester-VIII
S.No.
Code
CourseTitle
ContactPeriodsperWeek
Credit
L
T
P
Total
1
CSE 403
Theory of Computation
3
1
0
4
4
2
CSE XXXX
Departmental Elective V
4
3
CSE XXXX
Departmental Elective VI
4
4
OE XXXX
Open Elective III
4
5
CSE 422
M.Tech Thesis
4
Total
20
Semester-IX
S.No.
Code
CourseTitle
ContactPeriodsperWeek
Credit
L
T
P
Total
4
CSE XXXX
Departmental Elective VII
4
5
CSE 421
M.Tech Thesis
16
Total
20
Semester-X
S.No.
Code
CourseTitle
ContactPeriodsperWeek
Credit
L
T
P
Total
5
CSE 422
M.Tech Thesis
20
Total
20
SEMESETER-WISE CREDITS
Semester
Credits
Semester I
20
Semester II
20
Semester III
22
Semester IV
22
Semester V
23
Semester VI
21
Semester VII
22
Semester VIII
20
Semester IX
20
Semester X
20
210
LIST OF DEPARTMENTAL ELECTIVES
S.No.
Code
CourseTitle
ContactPeriodsperWeek
Credit
L
T
P
Total
Level I
1
CSE L101
Theory of Computation
3
1
0
4
4
2
CSE L102
Compiler Design
3
1
0
4
4
3
CSE L103
Data Mining
3
2
5
4
4
CSE L104
Computer Graphics
3
0
2
5
4
5
CSE L105
Pattern Recognition
3
0
2
5
4
6
CSE L106
Natural Language Processing
3
0
2
5
4
7
CSE L107
Information Retrieval
3
0
2
5
4
8
CSE L108
Big Data Analytics
3
0
2
5
4
9
CSE L109
Social Media Analytics
3
0
2
5
4
10
CSE L110
Network Science
3
0
2
5
4
11
CSE L111
Internet of Things and Embedded
Systems
3
0
2
5
4
12
CSE L112
Cloud Computing
3
0
2
5
4
13
CSE L113
Software Defined Networking
3
0
2
5
4
14
CSE L114
Blockchain Technology
3
0
2
5
4
15
CSE L115
Real-Time Systems
3
0
2
5
4
16
CSE L116
Mobile Computing
3
0
2
5
4
17
CSE L117
Soft Computing
3
0
2
5
4
18
CSE L118
Computational Intelligence
3
0
2
5
4
19
CSE L119
Cryptography and Network Security
3
0
2
5
4
20
CSE L120
Graph Algoriths
3
1
0
4
4
21
CSE L121
Wireless Networks
3
0
2
5
4
LevelII
22
CSE L201
Advanced Computer Architecture
3
0
2
5
4
23
CSE L202
Advanced Algorithms
3
1
0
4
4
24
CSE L203
Evolutionary Algorithms
3
0
2
5
4
25
CSE L204
AI and ML Techniques for Cyber
Security
3
0
2
5
4
26
CSE L205
Fuzzy Modelling
3
0
2
5
4
27
CSE L206
Deep Learning
3
0
2
5
4
28
CSE L207
Advanced Machine Learning
3
0
2
5
4
29
CSE L208
Reinforcement Learning
3
0
2
5
4
30
CSE L209
Advanced Computer Networks
3
0
2
5
4
31
CSE L210
Performance Modeling of Computer
Systems
3
1
0
4
4
32
CSE L211
Advanced Optimization Techniques
3
1
0
4
4
33
CSE L212
Game Theory
3
1
0
4
4
34
CSE L213
Computer Vision
3
0
2
5
4
35
CSE L214
Multiprocessor Systems and High-
Performance Computing
3
0
2
5
4
36
CSE L215
Optical Networks
3
0
2
5
4
37
CSE L216
Generative AI
3
0
2
5
4
38
CSE L217
Explainable AI
3
0
2
5
4
Notations
HSS: Humanities and Social Sciences.
Open electives (OE): These are the elective courses which a student can opt from other departments/faculties of the university (excluding the courses offered in HSS bucket), which will broaden the knowledge of the students beyond the discipline of Computer Science
Departmentalelective(DE): These are elective courses offered by the department.
L: Lecture | T: Tutorial | P: Practical
Course Structure
PREAMBLE
With an objective to prepare learned and skilled professionals for SAARC countries having strong conceptual and practical backgrounds, B.Tech (Computer Science and Engineering) programme of four years duration is offered. The total number of seats in the programme is 90. The grade requirement for promotion to next semester as well as for the award of the degree, repetition of a course, extra semester to clear backlog etc. are as per university regulations/byelaws.
The University follows a unique up-to-date curriculum with the aim of equipping students with strong analytical and technical skills as well as thorough knowledge of and expertise in the latest state-of-the art techniques in Computer Science and Engineering as well as in the interdisciplinary disciplines so that they can work competently in diverse areas including industry, teaching and research and development. Besides having a good mix of theoretical and lab-oriented computer science courses together with a reasonable amount of training/learning in the interdisciplinary domains, the B.Tech (Computer Science and Engineering) programme has a project component which also provides an opportunity to students to work on practical problems.
MINIMUM ELIGIBILITY CRITERIA
A student must have passed the Class 12 or Higher Secondary or any equivalent qualifying examination in Science stream (having Mathematics and Physics/Chemistry as mandatory subjects) with a minimum of 65% marks in aggregate based on education board recognized by any of the SAARC nations.
SELECTION PROCESS
The following admission process is adopted:
Route 1: Merit list based on JEE Main (conducted by IITs) scores.
Route 2: Merit list based on entrance examination conducted by SAU.
COURSE STRUCTURE* FOR 4-YEAR B.TECH (CSE) DEGREE
*Subject to further re-organization/updation/revision based on experts’ feedback
Semester-I
S.No.
Code
CourseTitle
ContactPeriodsperWeek
Credit
L
T
P
Total
1
CSE 101
Computational Thinking
3
0
4
7
5
2
MT 101
Advanced Calculus
3
1
0
4
4
3
PH 101
Engineering Physics
3
0
4
7
5
4
EN 101
English-I
3
1
0
3
4
5
HS 101
Introduction to South Asia
2
0
0
2
2
Total
14
2
8
23
20
Semester-II
S.No.
Code
CourseTitle
ContactPeriodsperWeek
Credit
L
T
P
Total
1
CSE 102
Data Structures
3
0
4
7
5
2
CSE 103
Digital Logic Design
3
0
4
7
5
3
MT 102
Linear Algebra and Optimization
3
1
0
4
4
4
EN 102
English-II (Language Lab)
2
0
0
2
2
5
HS 102
HSS-I
3
1
0
4
4
Total
14
2
8
24
20
Semester-III
S.No.
Code
CourseTitle
ContactPeriodsperWeek
Credit
L
T
P
Total
1
CSE 201
Object Oriented Programming
3
0
4
7
5
2
CSE 202
Computer Architecture
3
0
4
7
5
3
MT 201
Introduction to Probability Theory
3
1
0
4
4
4
MT 202
Discrete Mathematics
3
1
0
4
4
5
HS 201
HSS-II
3
1
0
4
4
Total
15
3
8
26
22
Semester-IV
S.No.
Code
CourseTitle
ContactPeriodsperWeek
Credit
L
T
P
Total
1
CSE 203
Operating Systems
3
0
4
7
5
2
CSE 204
Design and Analysis of Algorithms
3
1
2
6
5
3
CSE 205
Introduction to Artificial Intelligence
3
0
2
5
4
4
MT 203
Fundamentals of Data Science and
3
1
0
4
4
5
HS 202
HSS-III
3
1
0
4
4
Total
15
3
8
26
22
Semester-V
S.No.
Code
CourseTitle
ContactPeriodsperWeek
Credit
L
T
P
Total
1
CSE 301
Computer Networks
3
0
4
7
5
2
CSE 302
Machine Learning
3
1
2
6
5
3
CSE 303
Database Management Systems
3
0
4
7
5
4
CSE 304
Software Engineering
3
1
0
4
4
5
HS 301
HSS-IV
3
1
0
4
4
Total
15
3
10
28
23
Semester-VI
S.No.
Code
CourseTitle
ContactPeriodsperWeek
Credit
L
T
P
Total
1
CSE 305
Distributed Systems
3
1
2
6
5
2
CSE 306
Project (Application Development)
1
0
6
7
4
3
CSE XXXX
Departmental Elective I
4
4
CSE XXXX
Departmental Elective II
4
5
OE XXXX
Open Elective I
4
Total
21
Semester-VII
S.No.
Code
CourseTitle
ContactPeriodsperWeek
Credit
L
T
P
Total
1
CSE XXXX
Departmental Elective III
4
2
CSE XXXX
Departmental Elective IV
4
3
OE XXXX
Open Elective II
4
4
OE XXXX
Open Elective III
4
5
CSE 421
Mini Project
0
0
8
8
4
Total
20
Semester-VIII
S.No.
Code
CourseTitle
ContactPeriodsperWeek
Credit
L
T
P
Total
1
CSE XXXX
Open Elective IV*
3
2
CSE XXXX
Open Elective V*
3
3
CSE 422
BTP/Internship
14
Total
20
*A student may take the open electives from online or other institutes in the eighth semester recommended by the department. Additional credits may also be allocated in VI and VII semesters based on a minimum CGPA criteria.
Semester-Wise Credits
Semester
Credits
Semester I
20
Semester II
20
Semester III
22
Semester IV
22
Semester V
23
Semester VI
21
Semester VII
20
Semester VIII
20
168
LIST OF DEPARTMENTAL ELECTIVES
S.No.
Code
CourseTitle
ContactPeriodsperWeek
Credit
L
T
P
Total
Level I
1
CSE L101
Theory of Computation
3
1
0
4
4
2
CSE L102
Compiler Design
3
1
0
4
4
3
CSE L103
Data Mining
3
2
5
4
4
CSE L104
Computer Graphics
3
0
2
5
4
5
CSE L105
Pattern Recognition
3
0
2
5
4
6
CSE L106
Natural Language Processing
3
0
2
5
4
7
CSE L107
Information Retrieval
3
0
2
5
4
8
CSE L108
Big Data Analytics
3
0
2
5
4
9
CSE L109
Social Media Analytics
3
0
2
5
4
10
CSE L110
Network Science
3
0
2
5
4
11
CSE L111
Internet of Things and Embedded
Systems
3
0
2
5
4
12
CSE L112
Cloud Computing
3
0
2
5
4
13
CSE L113
Software Defined Networking
3
0
2
5
4
14
CSE L114
Blockchain Technology
3
0
2
5
4
15
CSE L115
Real-Time Systems
3
0
2
5
4
16
CSE L116
Mobile Computing
3
0
2
5
4
17
CSE L117
Soft Computing
3
0
2
5
4
18
CSE L118
Computational Intelligence
3
0
2
5
4
19
CSE L119
Cryptography and Network Security
3
0
2
5
4
20
CSE L120
Graph Algoriths
3
1
0
4
4
21
CSE L121
Wireless Networks
3
0
2
5
4
Level II
22
CSE L201
Advanced Computer Architecture
3
0
2
5
4
23
CSE L202
Advanced Algorithms
3
1
0
4
4
24
CSE L203
Evolutionary Algorithms
3
0
2
5
4
25
CSE L204
AI and ML Techniques for Cyber
Security
3
0
2
5
4
26
CSE L205
Fuzzy Modelling
3
0
2
5
4
27
CSE L206
Deep Learning
3
0
2
5
4
28
CSE L207
Advanced Machine Learning
3
0
2
5
4
29
CSE L208
Reinforcement Learning
3
0
2
5
4
30
CSE L209
Advanced Computer Networks
3
0
2
5
4
31
CSE L210
Performance Modeling of Computer
Systems
3
1
0
4
4
32
CSE L211
Advanced Optimization Techniques
3
1
0
4
4
33
CSE L212
Game Theory
3
1
0
4
4
34
CSE L213
Computer Vision
3
0
2
5
4
35
CSE L214
Multiprocessor Systems and High-
Performance Computing
3
0
2
5
4
36
CSE L215
Optical Networks
3
0
2
5
4
37
CSE L216
Generative AI
3
0
2
5
4
38
CSE L217
Explainable AI
3
0
2
5
4
Notation
HSS: Humanities and Social Sciences.
Departmental electives: These are elective courses offered by the department.
L: Lecture | T: Tutorial | P: Practical
Course Structure
PhD (Applied Mathematics)
S. No.
Course No.
Course
Credits
1ST SEMESTER
1
AM 501
Advanced Analysis
2
2
AM 502
Advanced Numerical Optimization Techniques
2
3
AM 503
Advanced Numerical Techniques for Differential Equations
2
4
AM 504
Advanced Mathematical Modeling
2
5
AM 505
Parallel Iterative Methods for Partial Differential Equations
2
6
AM506
Operator Theory
2
7
AM 507
Computational Finance
2
8
AM 508
Advanced Graph Theory
2
9
AM 509
Quantum Calculus
2
2ND SEMESTER
1
AM 600
Seminar
2
2
AM 601
Weighted Norm Inequalities and Integral Operators on Function Spaces
3
AM 602
Swarm and Evolutionary Algorithms
4
4
AM 603
Robust Numerical Methods for Singularly Perturbed Problems
4
5
AM 604
Modelling of Biological Systems
4
6
AM 605
High Resolution Computational Methods for Partial Differential Equations
4
7
AM 606
Advanced Fuzzy Set Theory
4
8
AM 607
Soft Computing Technique for Differential Equations
4
9
AM 608
Spectral Graph Theory and Signed Graphs
4
A student will be required to opt any 5 courses out of the offered elective courses in the 1st semester, whereas in 2nd semester a student has to opt any one of the elective courses offered during the semester.
NOTE: A student has to earn 16 credits from among the elective courses.
Course Structure
Assigned Pre-Ph.D. / MPhil course work will be carried out over first two semesters and will carry 16 credits including credits for course work (14 credits), seminar and term papers (1 credit each).
At the end of first year candidates with CGPA less than 5.5 will be deemed to have failed and shall leave the university. No re-tests will be permitted.
Candidates with CGPA of 6.5 and above will be offered direct confirmation to Ph.D. programme. Candidates with CGPA between 5 to less than 6.5 will go to MPhil stream and carry out a one-year thesis work (8 Credits). After completion of MPhil, students with total MPhil CGPA of 6.5 or more will be allowed to register for PhD programme. Candidates with MPhil CGPA of 5 to less than 6.5 will leave the university with an MPhil degree.
Note: The course outline is tentative, and subject to modifications from time to time.
Course Structure
Candidates will be confirmed to the MPhil/PhD programme after successfully completing coursework of 18 credits within the prescribed period of two semesters with a minimum grade of B. Coursework includes two compulsory courses titled ‘Advanced Social Theory’ and ‘Advanced Research Methods’, worth 4 credits each.
Students must also pass the compulsory non-credit course, ‘Introduction to South Asia’. Candidates who have completed the course during their M.A studies at South Asian University shall be exempted from doing this course. All Students will choose two out of three optional courses offered by the Department, worth 4 credits each, and write a seminar paper worth 2 credits.
