Text Analytics Using Python for Behavioural & Qualitative Researchers | 6-Day Online FDP | Dr. Muhammed Niyas, Rajagiri Business School

6-Day Online FDP

Text Analytics Using Python for Behavioural & Qualitative Researchers

08 – 13 December 2025 | 6:00 PM – 9:00 PM (IST)

Mode: Online

Programme Features

• No prior programming knowledge required
• Hands-on sessions using Python & NLP libraries
• End-to-end data analysis workflow
• All practice codes, recordings, and e-certificates provided

Are you a faculty member, researcher, or scholar looking to build practical skills in text analytics and Python programming — even with no prior coding background?

Join this hands-on FDP designed to take you from basic Python coding to advanced text analysis techniques used in behavioural, social science, and qualitative research.

Day-wise Schedule

Day 1 – Python Essentials for Researchers

• Python syntax, variables, loops, and conditions
• Writing basic scripts for text reading and storage
• Application: Build coding literacy to handle text data independently.

Day 2 – Data Structures & Data Frames

• Lists, dictionaries, and string manipulation
• Handling textual data using Pandas
• Application: Structure unorganized narratives for thematic analysis.

Day 3 – Text Preprocessing & Basic Web Scraping

• Tokenization, lemmatization, and normalization (NLTK, spaCy)
• Word-frequency tables, n-grams, and word clouds
• Basic web scraping (requests, Beautiful Soup)
• Application: Clean and prepare raw text data for deeper analysis.

Day 4 – Named Entity Recognition (NER) & Event Extraction

• Extracting entities (people, organizations, places) using spaCy
• Event and sequence extraction from narratives
• Application: Identify patterns in interviews, news, or reports.

Day 5 – Sentiment Detection

• Sentiment analysis using VADER, TextBlob, and BERT/FinBERT
• Application: Quantify emotional tone and map attitudes in text data.

Day 6 – Topic Modeling & Integrated Workflow

• Topic modeling using Gensim (LDA) and BERT embeddings
• Visualizations using pyLDAvis and matplotlib
• Creating complete text analytics pipelines
• Application: Integrate preprocessing, sentiment, and topic modeling for qualitative insights.

Resource Person

Dr. Muhammed Niyas

Assistant Professor – Information Systems & Business Analytics

Rajagiri Business School

Who Can Attend

• Faculty Members
• PhD Scholars & Postdoctoral Fellows
• Research Analysts & Associates

Indians - FDP Fee: INR 1950/- (including GST) 

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Internationals - FDP Fee: USD 50

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For ServiceSetu Premium Members: Fee - INR 1500/-

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All practice codes, recordings, and e-certificates provided

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