<<<<<<< HEAD rgpv scheme MTech Grading System 3rd Semester Microsoft Word - III Sem AI & Data Science Scheme Final

image

Rajiv Gandhi Proudyogiki Vishwavidyalaya, Bhopal(M.P.)

Scheme of Examination (w.e.f. 20-21)

Third Semester- M.E./M.Tech (Artificial Intelligence & Data Science)



S.No.

Subject Code

Subject Name

Periods per week

Credits

Maximum Marks (Theory Slot)

Maximum Marks (Practical Slot)

Total Marks

End Sem. Exam.

Tests (Two)

Assign ments

/Quiz

End Sem. Practic al/Viva

Practical Record/ Assignm ent/Quiz

/Present

ation


L


T


P

1.

MTAD 301

Elective III

3

1

-

4

70

20

10

-

-

100

2.

MTAD 302

Elective IV

3

1

-

4

70

20

10

-

-

100

3.

MTAD 303

Seminar

-

-

4

4

-

-

-

-

100

100

4.

MTAD 304

Dissertation Part- I

(Literature

Review/Problem Formulation/ Synopsis)

-

-

8

8

-

-

-

120

80

200



Total

6

2

12

20

140

40

20

120

180

500



L: Lecture - T: Tutorial - P: Practical


Elective-III: Elective-IV:

  1. Image processing & Computer Vision (A) Pattern Recognition

  2. Modern information retrieval (B) Bio-Informatics Computing

  3. Information Security (C) Social Network Analysis

  4. Internet of Things (D) Mathematical modeling & Simulation

======= rgpv scheme MTech Grading System 3rd Semester Microsoft Word - III Sem AI & Data Science Scheme Final

image

Rajiv Gandhi Proudyogiki Vishwavidyalaya, Bhopal(M.P.)

Scheme of Examination (w.e.f. 20-21)

Third Semester- M.E./M.Tech (Artificial Intelligence & Data Science)



S.No.

Subject Code

Subject Name

Periods per week

Credits

Maximum Marks (Theory Slot)

Maximum Marks (Practical Slot)

Total Marks

End Sem. Exam.

Tests (Two)

Assign ments

/Quiz

End Sem. Practic al/Viva

Practical Record/ Assignm ent/Quiz

/Present

ation


L


T


P

1.

MTAD 301

Elective III

3

1

-

4

70

20

10

-

-

100

2.

MTAD 302

Elective IV

3

1

-

4

70

20

10

-

-

100

3.

MTAD 303

Seminar

-

-

4

4

-

-

-

-

100

100

4.

MTAD 304

Dissertation Part- I

(Literature

Review/Problem Formulation/ Synopsis)

-

-

8

8

-

-

-

120

80

200



Total

6

2

12

20

140

40

20

120

180

500



L: Lecture - T: Tutorial - P: Practical


Elective-III: Elective-IV:

  1. Image processing & Computer Vision (A) Pattern Recognition

  2. Modern information retrieval (B) Bio-Informatics Computing

  3. Information Security (C) Social Network Analysis

  4. Internet of Things (D) Mathematical modeling & Simulation

>>>>>>> html