KAI651: MACHINE LEARNING LAB
Course Outcomes:
| CO |
At the end of course , the student will be able to:
|
Bloom’s Level
|
|
CO1
|
Understand complexity of Machine Learning algorithms and their limitations; |
K5, K6
|
|
CO2
|
Understand modern notions in data analysis-oriented computing; |
K5, K5
|
|
CO3
|
Be capable of performing experiments in Machine Learning using real-world data.
|
K5, K6
|
|
CO4
|
Be capable of confidently applying common Machine Learning algorithms in
practice and implementing their own; |
K5, K5
|
Mapping Matrix of CO's and PO's
| COs |
PO1 |
PO2 |
PO3 |
PO4 |
PO5 |
PO6 |
PO7 |
PO8 |
PO9 |
PO10 |
PO11 |
PO12 |
PSO1 |
PSO2 |
PSO3 |
|
CO1
|
1 |
2 |
1 |
1 |
- |
- |
- |
- |
2 |
1 |
- |
2 |
- |
1 |
- |
|
CO2
|
2 |
1 |
2 |
- |
- |
- |
- |
- |
2 |
1 |
- |
2 |
2 |
- |
- |
|
CO3
|
- |
2 |
2 |
- |
- |
- |
- |
- |
1 |
1 |
- |
2 |
2 |
- |
- |
|
CO4
|
- |
- |
- |
2 |
- |
- |
- |
- |
2 |
1 |
- |
2 |
- |
- |
2 |
|
CO5
|
- |
- |
1 |
2 |
- |
- |
- |
- |
2 |
1 |
3 |
2 |
- |
- |
2 |
|
CO6
|
- |
1 |
- |
- |
- |
- |
- |
- |
- |
1 |
- |
2 |
- |
- |
2 |
|
Avg
|
1.5 |
1.5 |
1.5 |
1.67 |
- |
- |
- |
- |
1.8 |
1 |
3 |
2 |
2 |
1 |
2 |
