<<<<<<< HEAD rgpv scheme MTech Grading System 3rd Semester Microsoft Word - SCHEME OF CSDS MTECH 3 SEM

image

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

Scheme of Examination

Third Semester-M.E./M.Tech. Computer Science and Engineering (Data Science) (w.e.f 2023-24)



S.No.

Subject Code

Subject Name

Periods perweek

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.

MTCD 301

Elective III

3

1

-

4

70

20

10

-

-

100

2.

MTCD 302

Elective IV

3

1

-

4

70

20

10

-

-

100

3.

MTCD 303

Seminar

-

-

4

4

-

-

-

-

100

100

4.

MTCD 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) Quantum Computing

  2. Pattern Recognition (B) Social Network Analysis

  3. Green Computing

======= rgpv scheme MTech Grading System 3rd Semester Microsoft Word - SCHEME OF CSDS MTECH 3 SEM

image

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

Scheme of Examination

Third Semester-M.E./M.Tech. Computer Science and Engineering (Data Science) (w.e.f 2023-24)



S.No.

Subject Code

Subject Name

Periods perweek

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.

MTCD 301

Elective III

3

1

-

4

70

20

10

-

-

100

2.

MTCD 302

Elective IV

3

1

-

4

70

20

10

-

-

100

3.

MTCD 303

Seminar

-

-

4

4

-

-

-

-

100

100

4.

MTCD 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) Quantum Computing

  2. Pattern Recognition (B) Social Network Analysis

  3. Green Computing

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