HEAD
S.No. | Subject Code | Category | Subject Name | Maximum Marks Allotted | Total Mark s | Contact Hours per week | Total Credits | |||||||
Theory | Practical | |||||||||||||
End Sem. | Mid Sem. Exam. | Quiz/ Assignment | End Sem | Term work | L | T | P | |||||||
Lab Work &Sessional | ||||||||||||||
1. | AD 701 | DC | AI for Computer Vision | 70 | 20 | 10 | 30 | 20 | 150 | 2 | 1 | 2 | 4 | |
2. | AD 702 | DE | Departmental Elective | 70 | 20 | 10 | - | - | 100 | 3 | 1 | - | 4 | |
3. | AD 703 | OE | Open Elective | 70 | 20 | 10 | - | - | 100 | 3 | 0 | 0 | 3 | |
4. | AD 704 | D Lab | Departmental Elective Lab | - | -- | - | 30 | 20 | 50 | - | - | 6 | 3 | |
5. | AD 705 | O/E lab | Open Elective Lab | - | - | - | 30 | 20 | 50 | - | - | 6 | 3 | |
6. | AD 706 | P | Major Project-I | - | - | - | 100 | 50 | 150 | - | - | 8 | 4 | |
7. | AD 607 | Evaluation of Internship -III | - | - | - | - | 100 | 100 | - | - | 6 | 3 | ||
8. | Addition al Credi ts# | #Additional credits can be earned through successful completion of credit based MOOC’s Courses available on SWAYAM platform (MHRD) at respective UG level. | ||||||||||||
Total | 210 | 60 | 30 | 190 | 210 | 700 | 8 | 2 | 28 | 24 |
Departmental Electives | Open Electives |
702(A) Cloud Computing | 703(A) Data Visualization |
702(B) Business Intelligence | 703(B) Mobile Application Development |
702(C)Computational Intelligence | 703(C) Advanced Statistical Analytics |
702(D) Predictive Analytics | 703(D)Social Media & Web Analytics |
# Open Electives can be offered to students of all branches including AI&DS branch. However, they can be offered to students of Non-AI&DS branches only if they have not taken any similar courses previously and have sufficient knowledge of pre-requisite courses (if any) of respective open electives subject.
1 Hr Lecture 1 Hr Tutorial 2 Hr Practical
1 Credit1 Credit1 Credit
=======S.No. | Subject Code | Category | Subject Name | Maximum Marks Allotted | Total Mark s | Contact Hours per week | Total Credits | |||||||
Theory | Practical | |||||||||||||
End Sem. | Mid Sem. Exam. | Quiz/ Assignment | End Sem | Term work | L | T | P | |||||||
Lab Work &Sessional | ||||||||||||||
1. | AD 701 | DC | AI for Computer Vision | 70 | 20 | 10 | 30 | 20 | 150 | 2 | 1 | 2 | 4 | |
2. | AD 702 | DE | Departmental Elective | 70 | 20 | 10 | - | - | 100 | 3 | 1 | - | 4 | |
3. | AD 703 | OE | Open Elective | 70 | 20 | 10 | - | - | 100 | 3 | 0 | 0 | 3 | |
4. | AD 704 | D Lab | Departmental Elective Lab | - | -- | - | 30 | 20 | 50 | - | - | 6 | 3 | |
5. | AD 705 | O/E lab | Open Elective Lab | - | - | - | 30 | 20 | 50 | - | - | 6 | 3 | |
6. | AD 706 | P | Major Project-I | - | - | - | 100 | 50 | 150 | - | - | 8 | 4 | |
7. | AD 607 | Evaluation of Internship -III | - | - | - | - | 100 | 100 | - | - | 6 | 3 | ||
8. | Addition al Credi ts# | #Additional credits can be earned through successful completion of credit based MOOC’s Courses available on SWAYAM platform (MHRD) at respective UG level. | ||||||||||||
Total | 210 | 60 | 30 | 190 | 210 | 700 | 8 | 2 | 28 | 24 |
Departmental Electives | Open Electives |
702(A) Cloud Computing | 703(A) Data Visualization |
702(B) Business Intelligence | 703(B) Mobile Application Development |
702(C)Computational Intelligence | 703(C) Advanced Statistical Analytics |
702(D) Predictive Analytics | 703(D)Social Media & Web Analytics |
# Open Electives can be offered to students of all branches including AI&DS branch. However, they can be offered to students of Non-AI&DS branches only if they have not taken any similar courses previously and have sufficient knowledge of pre-requisite courses (if any) of respective open electives subject.
1 Hr Lecture 1 Hr Tutorial 2 Hr Practical
1 Credit1 Credit1 Credit
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