Course

UNIT 1

Python Programming and Text Processing Foundations

Python string manipulation, regular expressions, text cleaning, tokenisation, file handling, CSV and JSON processing, PDF text extraction, API handling, and Python libraries including re, json, requests, pdfplumber, and pandas.

UNIT 2

Natural Language Processing and MongoDB for Text Understanding

Stopword removal, stemming, lemmatisation, Named Entity Recognition (NER), keyword extraction, sentiment analysis, text vectorisation, document preprocessing, MongoDB collections, CRUD operations, querying, and MongoDB integration with Python.

UNIT 3

Text Generation and Summarisation for Multilingual Systems

Pretrained language models, extractive and abstractive summarisation, multilingual translation, response generation, content creation and Python libraries including transformers, deep-translator, and torch.

UNIT 4

Semantic Search, Retrieval-Augmented Generation (RAG), and Intelligent Document Systems

Web text extraction, semantic embeddings, cosine similarity, vector databases, document indexing, semantic search pipelines, FAQ systems, and Python libraries including sentence-transformers, langchain, chromadb, and faiss.

Nature of Course

Theory & Lab

Course Objectives

• The course covers the practical application of Python programming in scientific research, with a focus on developing effective data analysis and literature synthesis skills for exploring Indian textbooks – IKS.
• The subject provides an overview of computational methodologies and their relationship between data analysis, traditional philosophical frameworks and scholarly communication.
• The course focuses on the application level of programming tools and how they enhance research efficiency, critical thinking, and advanced academic analysis of ancient texts and knowledge systems – IKS.

Course Outcomes

After successful completion of the course, Students will be able to:

POs Programme Outcomes

• PO1: Engineering Knowledge
• PO2: Problem Analysis
• PO3: Design/Development of Solutions
• PO4: Conduct Investigations of complex problems
• PO5: Modern tools usage
• PO6: Engineer and Society
• PO7: Environment and Sustainability
• PO8: Ethics
• PO9: Individual & Teamwork
• PO10: Communication
• PO11: Project management & Finance
• PO12: Lifelong learning

CO-PO Mapping
[affinity#: 3 – high; 2- moderate; 1- slightly]

• Sweigart, A. (2019). Automate the boring stuff with Python: Practical programming for total beginners (2nd ed.). No Starch Press.
• Bird, S., Klein, E., & Loper, E. (2009). Natural language processing with Python. O’Reilly Media.
• Jurafsky, D., & Martin, J. H. (2025). Speech and language processing (3rd ed. draft). Stanford University.
• Banker, K. (2011). MongoDB in action. Manning Publications.
• Chodorow, K. (2019). MongoDB: The definitive guide (3rd ed.). O’Reilly Media.