<<<<<<< HEAD rgpv scheme MTech Grading System 2nd Semester Microsoft Word - II Sem AI & Data Science Scheme

image

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

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

Second 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. Practical

/Viva

Practical Record/ Assignm ent/Quiz

/Present

ation


L


T


P

1.

MTAD 201


Soft Computing

3

1

-

4

70

20

10

-

-

100

2.

MTAD

202

Computational intelligence

3

1

-

4

70

20

10

-

-

100

3.

MTAD 203

Big Data

3

1

-

4

70

20

10

-

-

100

4.

MTAD

204

Natural Language Processing

3

1

-

4

70

20

10

-

-

100

5.

MTAD

205

Elective II

3

1

-

4

70

20

10

-

-

100

6.

MTAD 206

Lab-III

-

-

6

3

-

-

-

90

60

150

7.

MTAD

207

Lab-IV

-

-

6

3

-

-

-

90

60

150



Total

15

5

12

26

350

100

50

180

120

800


L: Lecture - T: Tutorial - P: Practical


Elective-II:

  1. Reinforcement Learning

  2. Recommender System

  3. Research Methodology and IPR

  4. Deep Learning

======= rgpv scheme MTech Grading System 2nd Semester Microsoft Word - II Sem AI & Data Science Scheme

image

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

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

Second 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. Practical

/Viva

Practical Record/ Assignm ent/Quiz

/Present

ation


L


T


P

1.

MTAD 201


Soft Computing

3

1

-

4

70

20

10

-

-

100

2.

MTAD

202

Computational intelligence

3

1

-

4

70

20

10

-

-

100

3.

MTAD 203

Big Data

3

1

-

4

70

20

10

-

-

100

4.

MTAD

204

Natural Language Processing

3

1

-

4

70

20

10

-

-

100

5.

MTAD

205

Elective II

3

1

-

4

70

20

10

-

-

100

6.

MTAD 206

Lab-III

-

-

6

3

-

-

-

90

60

150

7.

MTAD

207

Lab-IV

-

-

6

3

-

-

-

90

60

150



Total

15

5

12

26

350

100

50

180

120

800


L: Lecture - T: Tutorial - P: Practical


Elective-II:

  1. Reinforcement Learning

  2. Recommender System

  3. Research Methodology and IPR

  4. Deep Learning

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