Course

CO

Course Outcomes

Knowledge level [Bloom’s Taxonomy]

CO01

Develop Python programs using basic programming concepts, file handling, and text processing techniques.

Understanding

CO02

Apply Natural Language Processing techniques for analysing and preprocessing textual data.

Understanding, Analyzing

CO03

Develop IKS applications using MongoDB for storing, querying, and managing textual datasets.

Analyzing, Applying

CO04

Integrate Python libraries, APIs, and databases for document processing and text-based applications

Analyzing, Applying

POs Programme Outcomes

COs

PO1: Disciplinary knowledge: Capable of demonstrating comprehensive knowledge and understanding of one or more disciplines that form a part of the current program.

CO 1: Develop Python programs using basic programming concepts, file handling, and text processing techniques.

PO2: Problem-solving skills: Develop problem-solving skills in familiar and non-familiar contexts and apply one’s learning to real-life situations.

CO 2: Apply Natural Language Processing techniques for analysing and preprocessing textual data.

PO3: Critical and Analytical thinking: Inculcate critical and analytical thinking to analyse and evaluate the reliability and relevance of evidence, scientific arguments, draw valid conclusions, and support them with examples.

CO 3: Develop IKS applications using MongoDB for storing, querying, and managing textual datasets.

PO4: Scientific reasoning and Research-related skills: Ability to apply scientific reasoning in designing research-related problems, analyse, interpret, and draw conclusions from quantitative/qualitative data. Critically evaluate ideas, evidence, and report the results of an experiment or investigation.

CO 4: Integrate Python libraries, APIs, and databases for document processing and text-based applications (IKS) .

PO5: Communication Skills and Team work: Develop the individual ability to express thoughts and ideas effectively in writing and orally; and also to communicate with members of diverse teams to work effectively and respectfully.

PO6: Moral and ethical awareness: Capable of recognizing ethical issues, understanding intellectual property rights, promoting ethical practices in all tasks, and considering environmental and sustainability concerns.

PO7: Lifelong learning: Ability to acquire knowledge and skills, including self – directed learning, for lifelong learning, personal development, and adapting to evolving workplace demands through continuous skill development and reskilling to meet economic, social, and cultural goals.

COs

PO1

PO2

PO3

PO4

PO5

PO6

PO7

CO01

3

2

2

2

1

1

–

CO02

3

3

3

2

2

–

–

CO03

2

2

3

2

–

2

–

CO04

3

3

2

2

–

–

–

Lecture Hours

Topics

Subtopics

CO

PO

1–2

Introduction to Python

Python syntax, variables, data types, operators

CO1

PO1

3–4

Control Structures and Functions

Conditional statements, loops, functions

CO1

PO2

5–6

Python Data Structures

Lists, tuples, dictionaries, string manipulation

CO1

PO1

7–8

File Handling and Text Processing

Basic file handling, regular expressions, text cleaning

CO1

PO2

9–10

Data Formats and APIs

CSV and JSON processing, API handling

CO1

PO4

11–12

Python Libraries for Text Processing

re, json, requests, pdfplumber, pandas

CO1

PO4

13–14

NLP Fundamentals

Tokenisation, stopword removal, stemming, lemmatisation

CO2

PO1

15–16

Information Extraction

NER, keyword extraction, sentiment analysis

CO2

PO3

17–18

Text Representation

Text vectorisation, document preprocessing

CO2

PO4

19–20

Introduction to MongoDB

MongoDB collections, CRUD operations

CO3

PO1

21–22

Querying and JSON Handling

Querying, JSON document handling

CO3

PO2

23–24

MongoDB with Python

MongoDB integration with Python

CO3

PO4

Course Category

L-T-P

Internal: External

Internal (%)

External (%)

Mid-Term (%)

Continuous Evaluation -Theory (%)

Continuous Evaluation -Lab (%)

Theory with Lab Component

1-0-2

70: 30

70

30

20

10

40

Component

Weightage (%)

Description

Continuous Assessment – Theory

10

Assignments and class participation

Mid-Term Examination

20

Lab examination covering theory topics

Continuous Assessment – Lab

40

Lab Project

End Semester Theory Examination

30

Lab examination covering the complete syllabus.

Total

100