HEAD
Rajiv Gandhi ProudyogikiVishwavidyalaya, Bhopal
S.N o. | Subject Code | Categ ory | Subject Name | Maximum Marks Allotted | Total Mar ks | Contact Hours per week | Total Credi ts | ||||||
Theory | Practical | ||||||||||||
End Sem | Mid Sem Exam | Quiz/ Assignment | End Sem | Term work | L | T | P | ||||||
Lab Work & Sessional | |||||||||||||
1. | AD801 | DC | Big Data | 70 | 20 | 10 | 30 | 20 | 150 | 2 | 1 | 2 | 4 |
2. | AD802 | DE | Departmental Elective | 70 | 20 | 10 | - | - | 100 | 3 | 1 | - | 4 |
3. | AD803 | OE | Open Elective | 70 | 20 | 10 | - | - | 100 | 3 | - | - | 3 |
4. | AD804 | D/O/E Lab | Departmental/Open Elective lab | - | -- | - | 30 | 20 | 50 | - | - | 6 | 3 |
5. | AD805 | P | Major Project-II | - | - | - | 70 | 30 | 100 | - | - | 8 | 4 |
6. | Additional Credits# | #Additional credits can be earned through successful completion of credit based MOOC’s Courses available on SWAYAM platform (MHRD) at respective level. | |||||||||||
Total | 210 | 60 | 30 | 130 | 70 | 500 | 8 | 2 | 16 | 18 |
Departmental Electives | Open Electives |
802 (A) Natural Language Processing | 803 (A)AI for Remote Sensing |
802 (B)Reinforcement Learning | 803 (B) Augmented & Virtual Reality |
802 (C)Robotic Process Automation | 803(C) Managing Innovation and Entrepreneurship |
# These Open Electives can be offered to students of all branches including the 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
=======Rajiv Gandhi ProudyogikiVishwavidyalaya, Bhopal
S.N o. | Subject Code | Categ ory | Subject Name | Maximum Marks Allotted | Total Mar ks | Contact Hours per week | Total Credi ts | ||||||
Theory | Practical | ||||||||||||
End Sem | Mid Sem Exam | Quiz/ Assignment | End Sem | Term work | L | T | P | ||||||
Lab Work & Sessional | |||||||||||||
1. | AD801 | DC | Big Data | 70 | 20 | 10 | 30 | 20 | 150 | 2 | 1 | 2 | 4 |
2. | AD802 | DE | Departmental Elective | 70 | 20 | 10 | - | - | 100 | 3 | 1 | - | 4 |
3. | AD803 | OE | Open Elective | 70 | 20 | 10 | - | - | 100 | 3 | - | - | 3 |
4. | AD804 | D/O/E Lab | Departmental/Open Elective lab | - | -- | - | 30 | 20 | 50 | - | - | 6 | 3 |
5. | AD805 | P | Major Project-II | - | - | - | 70 | 30 | 100 | - | - | 8 | 4 |
6. | Additional Credits# | #Additional credits can be earned through successful completion of credit based MOOC’s Courses available on SWAYAM platform (MHRD) at respective level. | |||||||||||
Total | 210 | 60 | 30 | 130 | 70 | 500 | 8 | 2 | 16 | 18 |
Departmental Electives | Open Electives |
802 (A) Natural Language Processing | 803 (A)AI for Remote Sensing |
802 (B)Reinforcement Learning | 803 (B) Augmented & Virtual Reality |
802 (C)Robotic Process Automation | 803(C) Managing Innovation and Entrepreneurship |
# These Open Electives can be offered to students of all branches including the 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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