Mahatma Education Society’s
Pillai HOC College of Engineering and Technology, Rasayani
Department of Computer Engineering
Academic Year: 2024-25 Semester: VII Subject: NLP
INDEX
Assessment Parameters/Rubrics for
Sr. Page Performance Submission Total (Out
Title of Experiment/Assignment experiment evaluation Sign
No. No. Date Date of 10 )
Understanding Analysis Design Output Time- bound
Case Study: Text
1 Summarization on
Documents Using NLP
Apply various text pre-
2 processing techniques for
any given text.
To Perform Regular
3 Expression for a given
string.
Implement N-gram model
4 for the given input.
To study different POS
5 Taggers and perform POS
tagging for each Text.
To Perform chunking and
6 parsers for given text
input.
Implement Named Entity
7 Recognizer for the given
text input.
Write a program to
8 perform WordNet in NLP.
Write a program to
9 perform Word Sense
Disambiguation in NLP.
10
Mini Project
Understanding (20% of Total Marks) : The student has a clear understanding of the theortical concepts corresponding to the experiment
Analysis (20% of Total Marks) : The student exhibits good analysis and research skills to design solutions using different tools
Design (20% of Total Marks) : The student has used cognitive skills for designing solution
Output (20% of Total Marks) : The student has generated relevant output without much supervision
Time- bound (20% of Total Marks) : The student is able to manage the given time and follows deadlines for on time submission
Signature of Student Signature of Staff Incharge
Mahatma Education Society’s
Pillai HOC College of Engineering and Technology, Rasayani
Department of Computer Engineering
LAB OUTCOMES
Course Code: CSDL7O13 Course Name: Natural Language processing Lab
Lab Outcome 1 Apply various text processing techniques.
Lab Outcome 2 Design language model for word level analysis.
Lab Outcome 3 Model linguistic phenomena with formal grammar.
Lab Outcome 4 Design, implement and analyze NLP algorithms.
Lab Outcome 5 To apply NLP techniques to design real world NLP applications such as machine
translation, sentiment analysis, text summarization, information extraction, Question
Answering system etc.
Lab Outcome 6 Implement proper experimental methodology for training and evaluating empirical NLP
systems.
PROGRAM OUTCOMES
Engineering Graduates will be able to:
1. Engineering knowledge: Apply the knowledge of mathematics, science, engineering fundamentals, and anengineering
specialization to the solution of complex engineering problems.
2. Problem analysis: Identify, formulate, review research literature, and analyze complex engineering problemsreaching
substantiated conclusions using first principles of mathematics, natural sciences, and engineering sciences.
3. Design/development of solutions: Design solutions for complex engineering problems and design system components or
processes that meet the specified needs with appropriate consideration for the public health andsafety, and the cultural,
societal, and environmental considerations.
4. Conduct investigations of complex problems: Use research-based knowledge and research methods includingdesign of
experiments, analysis and interpretation of data, and synthesis of the information to provide valid conclusions.
5. Modern tool usage: Create, select, and apply appropriate techniques, resources, and modern engineering and ITtools
including prediction and modeling to complex engineering activities with an understanding of the limitations.
6. The engineer and society: Apply reasoning informed by the contextual knowledge to assess societal, health,safety, legal
and cultural issues and the consequent responsibilities relevant to the professional engineering practice.
7. Environment and sustainability: Understand the impact of the professional engineering solutions in societal and
environmental contexts, and demonstrate the knowledge of, and need for sustainable development.
8. Ethics: Apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering
practice.
9. Individual and team work: Function effectively as an individual, and as a member or leader in diverse teams,and in
multidisciplinary settings.
10. Communication: Communicate effectively on complex engineering activities with the engineering community and with
society at large, such as, being able to comprehend and write effective reports and design documentation, make effective
presentations, and give and receive clear instructions.
11. Project management and finance: Demonstrate knowledge and understanding of the engineering and management
principles and apply these to one’s own work, as a member and leader in a team, to manage projectsand in multidisciplinary
environments.
12. Life-long learning: Recognize the need for, and have the preparation and ability to engage in independent andlife-long
learning in the broadest context of technological change.
Mahatma Education Society’s
Pillai HOC College of Engineering and Technology, Rasayani
Department of Computer Engineering
Academic Year: 2024-25 Semester: VII Subject: BLOCKCHAIN
INDEX
Assessment Parameters/Rubrics for
Sr. Page Performance Submission Total (Out
Title of Experiment/Assignment experiment evaluation Sign
No. No. Date Date of 10 )
Understanding Analysis Design Output Time- bound
Cryptography in
1 Blockchain, Merkle root
tree hash
Creating Smart Contract
2 using Solidity and Remix
IDE.
Creating Transactions
3 using Solidity and Remix
IDE.
Embedding wallet and
4 transaction using Solidity.
Blockchain platform
5 ethereum using Geth.
Blockchain platform
6 Ganache.
Case Study on
7 Hyperledger
Case Study on Other
8 Blockchain platforms.
Creating a blockchain
9 Application.
Understanding (20% of Total Marks) : The student has a clear understanding of the theortical concepts corresponding to the experiment
Analysis (20% of Total Marks) : The student exhibits good analysis and research skills to design solutions using different tools
Design (20% of Total Marks) : The student has used cognitive skills for designing solution
Output (20% of Total Marks) : The student has generated relevant output without much supervision
Time- bound (20% of Total Marks) : The student is able to manage the given time and follows deadlines for on time submission
Signature of Student Signature of Staff Incharge
Mahatma Education Society’s
Pillai HOC College of Engineering and Technology, Rasayani
Department of Computer Engineering
LAB OUTCOMES
Course Code: CSDL7022 Course Name: Blockchain Lab
Lab Outcome 1 Creating Cryptographic hash using merkle tree.
Lab Outcome 2 Design Smart Contract using Solidity.
Lab Outcome 3 Implementing ethereum blockchain using Geth.
Lab Outcome 4 Demonstrate the concept of blockchain in real world application.
PROGRAM OUTCOMES
Engineering Graduates will be able to:
1. Engineering knowledge: Apply the knowledge of mathematics, science, engineering fundamentals, and anengineering
specialization to the solution of complex engineering problems.
2. Problem analysis: Identify, formulate, review research literature, and analyze complex engineering problemsreaching
substantiated conclusions using first principles of mathematics, natural sciences, and engineering sciences.
3. Design/development of solutions: Design solutions for complex engineering problems and design system components or
processes that meet the specified needs with appropriate consideration for the public health andsafety, and the cultural,
societal, and environmental considerations.
4. Conduct investigations of complex problems: Use research-based knowledge and research methods includingdesign of
experiments, analysis and interpretation of data, and synthesis of the information to provide valid conclusions.
5. Modern tool usage: Create, select, and apply appropriate techniques, resources, and modern engineering and ITtools
including prediction and modeling to complex engineering activities with an understanding of the limitations.
6. The engineer and society: Apply reasoning informed by the contextual knowledge to assess societal, health,safety, legal
and cultural issues and the consequent responsibilities relevant to the professional engineering practice.
7. Environment and sustainability: Understand the impact of the professional engineering solutions in societal and
environmental contexts, and demonstrate the knowledge of, and need for sustainable development.
8. Ethics: Apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering
practice.
9. Individual and team work: Function effectively as an individual, and as a member or leader in diverse teams,and in
multidisciplinary settings.
10. Communication: Communicate effectively on complex engineering activities with the engineering community and with
society at large, such as, being able to comprehend and write effective reports and design documentation, make effective
presentations, and give and receive clear instructions.
11. Project management and finance: Demonstrate knowledge and understanding of the engineering and management
principles and apply these to one’s own work, as a member and leader in a team, to manage projectsand in multidisciplinary
environments.
12. Life-long learning: Recognize the need for, and have the preparation and ability to engage in independent andlife-long
learning in the broadest context of technological change.
Mahatma Education Society’s
Pillai HOC College of Engineering and Technology, Rasayani
Department of Computer Engineering
Academic Year: 2024-25 Semester: VII Subject: ML
INDEX
Assessment Parameters/Rubrics for
Sr. Page Performance Submission Total (Out
Title of Experiment/Assignment experiment evaluation Sign
No. No. Date Date of 10 )
Understanding Analysis Design Output Time- bound
To implement Linear
1 Regression
To implement Logistic
2 Regression
To implement Ensemble
3 learning
(bagging/boosting)
To implement a Support
4 Vector Machine.
To implement
5 PCA/SVD/LDA
To implement Graph
6 Based Clustering
Mini project on ML
7 application
Understanding (20% of Total Marks) : The student has a clear understanding of the theortical concepts corresponding to the experiment
Analysis (20% of Total Marks) : The student exhibits good analysis and research skills to design solutions using different tools
Design (20% of Total Marks) : The student has used cognitive skills for designing solution
Output (20% of Total Marks) : The student has generated relevant output without much supervision
Time- bound (20% of Total Marks) : The student is able to manage the given time and follows deadlines for on time submission
Signature of Student Signature of Staff Incharge
Mahatma Education Society’s
Pillai HOC College of Engineering and Technology, Rasayani
Department of Computer Engineering
LAB OUTCOMES
Course Code: CSL701 Course Name: Machine Learning Lab
Lab Outcome 1 To implement an appropriate machine learning model for the given application.
Lab Outcome 2 To implement ensemble techniques to combine predictions from different
models.
Lab Outcome 3 To implement support Vector Machine for classification
Lab Outcome 4 To implement Principal Component analysis
Lab Outcome 5 To implement Clustering and graph based clustering algorithms.
Lab Outcome 6 To implement the dimensionality reduction techniques.
PROGRAM OUTCOMES
Engineering Graduates will be able to:
13. Engineering knowledge: Apply the knowledge of mathematics, science, engineering fundamentals, and anengineering
specialization to the solution of complex engineering problems.
14. Problem analysis: Identify, formulate, review research literature, and analyze complex engineering problems reaching
substantiated conclusions using first principles of mathematics, natural sciences, and engineering sciences.
15. Design/development of solutions: Design solutions for complex engineering problems and design system
components or processes that meet the specified needs with appropriate consideration for the public health andsafety, and
the cultural, societal, and environmental considerations.
16. Conduct investigations of complex problems: Use research-based knowledge and research methods includingdesign
of experiments, analysis and interpretation of data, and synthesis of the information to provide valid conclusions.
17. Modern tool usage: Create, select, and apply appropriate techniques, resources, and modern engineering and ITtools
including prediction and modeling to complex engineering activities with an understanding of the limitations.
18. The engineer and society: Apply reasoning informed by the contextual knowledge to assess societal, health,safety,
legal and cultural issues and the consequent responsibilities relevant to the professional engineering practice.
19. Environment and sustainability: Understand the impact of the professional engineering solutions in societal and
environmental contexts, and demonstrate the knowledge of, and need for sustainable development.
20. Ethics: Apply ethical principles and commit to professional ethics and responsibilities and norms of the
engineering practice.
21. Individual and team work: Function effectively as an individual, and as a member or leader in diverse teams,and in
multidisciplinary settings.
22. Communication: Communicate effectively on complex engineering activities with the engineering community and with
society at large, such as, being able to comprehend and write effective reports and design documentation, make effective
presentations, and give and receive clear instructions.
23. Project management and finance: Demonstrate knowledge and understanding of the engineering and management
principles and apply these to one’s own work, as a member and leader in a team, to manage projectsand in multidisciplinary
environments.
24. Life-long learning: Recognize the need for, and have the preparation and ability to engage in independent andlife-long
learning in the broadest context of technological change.
