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Sharda School of Computing Science & Engineering (SSCSE)
SET0127
Post Graduate
2 Years
Programme Educational Objectives (PEOs):
Program Outcomes (PO’s)
 
 
| 1st Year 125000 | 2nd Year 128750 |
| Fee Per Semester | Fee Per Year |
|---|---|
| NA | 5000** |
Sharda School of Computing Science & Engineering |
|||||||||
Department of Computer Science & Applications |
|||||||||
Programme Name: |
MSC - AIML |
  |
Programme Code:  SET0127 |
||||||
Batch: 2026 Onwards |
SEMESTER: I |
||||||||
S. No. |
Course Code |
Paper ID |
Course |
Teaching Load |
Credits |
Pre-requisites |
Type of |
||
L |
T |
P |
|||||||
THEORY SUBJECTS |
|||||||||
1 |
MSCS1101 |
  |
Database Management System |
4 |
0 |
0 |
4 |
Fundamentals of computers |
CC |
2 |
MSCS1102 |
  |
C Programming and File Handling |
4 |
0 |
0 |
4 |
Fundamentals of computers and basic mathematics |
CC |
3 |
MSAI1101 |
  |
Artificial Intelligence and Machine Learning |
4 |
0 |
0 |
4 |
Fundamentals of computers |
CC |
4 |
MSCS1104 |
  |
Computer Architecture and Organization |
3 |
0 |
0 |
3 |
Boolean Algebra |
CC |
5 |
MSCS1105 |
  |
Computing and Innovation |
2 |
0 |
0 |
2 |
Fundamentals of computers |
CC |
Practical/Viva-Voce/Jury |
|||||||||
6 |
MSCS1501 |
  |
Database Management Systems Lab |
0 |
0 |
2 |
1 |
Fundamentals of computers |
CC |
7 |
MSCS1502 |
  |
C Programming and File Handling Lab |
0 |
0 |
2 |
1 |
Fundamentals of computers |
CC |
8 |
MSAI1501 |
  |
Artificial Intelligence and Machine Learning Lab |
0 |
0 |
2 |
1 |
Fundamentals of computers |
CC |
TOTAL CREDITS |
  |
  |
  |
  |
  |
20 |
  |
  |
|
Sharda School of Computing Science & Engineering |
|||||||||
Department of Computer Science & Applications |
|||||||||
Programme Name: |
MSC - AIML |
  |
Programme Code:  SET0127 |
||||||
Batch: 2026 Onwards |
SEMESTER: II |
||||||||
S. No. |
Course Code |
Paper ID |
Course |
Teaching Load |
Credits |
Pre-requisites |
Type of |
||
L |
T |
P |
|||||||
THEORY SUBJECTS |
|||||||||
1 |
MSCS1106 |
  |
Data Structure Using C |
3 |
1 |
0 |
4 |
C Programming |
CC |
2 |
MSCS1201 |
  |
Application Programming in Python |
4 |
0 |
0 |
4 |
C Programming |
DSE |
3 |
MSAI1102 |
  |
Advanced Prompt Engineering |
3 |
0 |
0 |
3 |
Basics of Mathematics |
CC |
4 |
MSCS1401 |
  |
Probability and Statistics |
2 |
0 |
0 |
2 |
Basics of Mathematics |
SEC |
POE-I |
|||||||||
  |
MSCS1001 |
  |
Big Data Analytics |
3 |
0 |
0 |
3 |
Basics of Computers |
POE |
MSAI1001 |
  |
Soft Computing |
Basics of Computer Networks |
||||||
MSAI1002 |
  |
Cognitive Computing |
Basics of Computers |
||||||
Practical/Viva-Voce/Jury |
|||||||||
6 |
MSCS1504 |
  |
Data Structure Using C Lab |
0 |
0 |
2 |
1 |
C Programming |
CC |
7 |
MSCS1505 |
  |
Application Programming in Python Lab |
0 |
0 |
2 |
1 |
C Programming |
DSE |
POE I (Practical) |
|||||||||
  |
MSXXXX |
  |
Big Data Analytics |
0 |
0 |
2 |
1 |
Methodology |
POE |
MSXXXX |
  |
Soft Computing |
Methodology |
||||||
MSXXXX |
  |
Cognitive Computing |
Methodology |
||||||
9 |
MSCS1601 |
  |
Project Minor |
0 |
0 |
6 |
3 |
Methodology |
Project |
10 |
MSCS1601 |
  |
Community Connect |
0 |
0 |
0 |
0 |
  |
Audit |
11 |
NVXXXX |
  |
VAT course |
3 |
0 |
0 |
0 |
  |
VAT |
TOTAL CREDITS |
  |
  |
  |
  |
  |
22 |
  |
  |
|
Sharda School of Computing Science & Engineering |
|||||||||
Department of Computer Science & Applications |
|||||||||
Programme Name: |
MSC - AIML |
  |
Programme Code:  SET0127 |
||||||
Batch: 2026 Onwards |
SEMESTER: III |
||||||||
S. No. |
Course Code |
Paper ID |
Course |
Teaching Load |
Credits |
Pre-requisites |
Type of |
||
L |
T |
P |
|||||||
THEORY SUBJECTS |
|||||||||
1 |
MSCS2101 |
  |
Design and Analysis of Algorithms |
3 |
0 |
0 |
3 |
Data Structures |
CC |
2 |
MSAI2101 |
  |
Prediction Using Machine Learning |
3 |
0 |
0 |
3 |
C Programming |
CC |
3 |
MSCS2103 |
  |
Software Engineering |
3 |
0 |
0 |
3 |
Computer Fundamental |
CC |
4 |
MSCS2401 |
  |
Data Analysis and Visualization |
2 |
0 |
0 |
2 |
Python Fundamentals |
SEC |
POE II |
|||||||||
5 |
MSCS2001 |
  |
Mobile Computing |
3 |
0 |
0 |
3 |
Basics of Computers |
POE |
MSXXXX |
  |
Neural Networks |
Basics of Computers |
||||||
MSXXXX |
  |
Deep Learning |
Basics of Computers |
||||||
6 |
  |
  |
Research Methodology + IPR |
0 |
0 |
2 |
1 |
Research Methodology |
RM+IPR |
Practical/Viva-Voce/Jury |
|||||||||
7 |
MSAI2501 |
  |
Prediction using Machine Learning Lab |
0 |
0 |
2 |
1 |
C Programming |
CC |
8 |
MSCS2502 |
  |
Design and Analysis of Algorithms Lab |
0 |
0 |
2 |
1 |
Data Structures |
CC |
9 |
MSCS2503 |
  |
Software Engineering Lab |
0 |
0 |
2 |
1 |
Computer Fundamental |
CC |
POE II (Practicals) |
|||||||||
10 |
MSXXXX |
  |
Mobile Computing Lab |
0 |
0 |
2 |
1 |
  |
POE |
MSXXXX |
  |
Neural Networks Lab |
  |
||||||
MSXXXX |
  |
Deep Learning Lab |
  |
||||||
11 |
MSCS2504 |
  |
Data Analysis and Visualization Lab |
0 |
0 |
2 |
2 |
Python Fundamentals |
SEC |
12 |
MSCS2701 |
  |
Industry Connect |
0 |
0 |
0 |
2 |
  |
Project |
13 |
MSCS2601 |
  |
Dissertation |
0 |
0 |
4 |
2 |
Google Scholar |
Project |
TOTAL CREDITS |
  |
  |
  |
  |
  |
24 |
  |
  |
|
Sharda School of Computing Science & Engineering |
|||||||||
Department of Computer Science & Applications |
|||||||||
Programme Name: |
MSC - AIML |
  |
Programme Code:  SET0127 |
||||||
Batch: 2026 Onwards |
SEMESTER: IV |
||||||||
S. No. |
Course Code |
Paper ID |
Course |
Teaching Load |
Credits |
Pre-requisites |
Type of Course |
||
L |
T |
P |
|||||||
THEORY SUBJECTS |
|||||||||
1 |
MSCS2104 |
  |
Technical Skill Enhancement Course |
0 |
0 |
4 |
2 |
Computer Science Core Subjects |
CC |
POE-III |
|||||||||
2 |
MSAI2004 |
  |
Agentic AI |
3 |
0 |
0 |
3 |
Machine Learning |
POE |
MSCS2008 |
  |
Natural Language Processing |
Machine Learning |
||||||
MSAI2005 |
  |
Game Theory using AI |
Machine Learning |
||||||
POE-III (Practicals) |
|||||||||
3 |
MSAI2504 |
  |
Agentic AI Lab |
0 |
0 |
2 |
1 |
Programing methodology |
POE |
MSCS2508 |
  |
Natural Language Processing Lab |
Programing methodology |
||||||
MSAI2505 |
  |
Game Theory using AI Lab |
Programing methodology |
||||||
4 |
MSCS2603 |
  |
Project |
0 |
0 |
0 |
8 |
Research and Project Methodology |
Project |
TOTAL CREDITS |
  |
  |
  |
  |
  |
14 |
  |
  |
|
| For National Students |
|
| For International Students | The eligibility criterion for all programs for international applicants is minimum 50% in the qualifying examination and having studied the pre-requisite subjects for admission in to the desired program. |