Master qualitative research methods enhanced by generative AI tools, designed specifically for professionals with quantitative backgrounds.
Master qualitative research methods enhanced by generative AI tools, designed specifically for professionals with quantitative backgrounds.
This innovative course bridges the gap between quantitative and qualitative analysis using generative AI technologies. Designed for professionals with strong quantitative backgrounds, it introduces qualitative research methods through the lens of AI tools. Students learn to leverage Large Language Models for data interpretation, decision-making, and resource allocation while maintaining critical human oversight. The curriculum emphasizes practical applications of qualitative analysis in technical environments, teaching students to extract meaningful insights from unstructured data using modern AI tools.
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Instructors:
English
What you'll learn
Master qualitative analysis techniques using AI tools
Leverage LLMs for enhanced data interpretation
Integrate qualitative insights with quantitative methods
Develop AI-assisted decision-making strategies
Create and maintain living documents with AI
Optimize resource allocation using qualitative data
Skills you'll gain
This course includes:
44 Minutes PreRecorded video
6 assignments
Access on Mobile, Tablet, Desktop
FullTime access
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There are 7 modules in this course
This innovative course explores the integration of qualitative research methods with AI-powered analysis tools across seven comprehensive modules. Students learn to balance quantitative and qualitative approaches, using Large Language Models to enhance data interpretation and decision-making. The curriculum covers key topics including qualitative analysis fundamentals, AI-enhanced data interaction, decision-making frameworks, and resource allocation strategies. Special emphasis is placed on maintaining human oversight while leveraging AI capabilities for improved analytical outcomes.
Course Welcome
Module 1 · 1 Minutes to complete
Part 1: What is Qualitative Analysis
Module 2 · 23 Minutes to complete
Part 2: Chatting with Your Data
Module 3 · 23 Minutes to complete
Part 3: Qualitative Considerations
Module 4 · 23 Minutes to complete
Part 4: Time is Our Most Valuable Asset
Module 5 · 24 Minutes to complete
Part 5: A Tale of Three Hats
Module 6 · 24 Minutes to complete
Course Wrap-Up
Module 7 · 1 Hours to complete
Fee Structure
Payment options
Financial Aid
Instructor
Professor of Electrical and Computer Engineering at Vanderbilt University
Dr. Bennett Landman is a Professor of Electrical and Computer Engineering at Vanderbilt University, where he also serves as the Director of the Vanderbilt Lab for Immersive AI Translation (VALIANT) and leads the Medical-image Analysis and Statistical Interpretation (MASI) lab. He earned his Ph.D. in Biomedical Engineering from Johns Hopkins University in 2008, following an M.Eng. and B.S. in Electrical Engineering and Computer Science from the Massachusetts Institute of Technology. Dr. Landman's research focuses on medical image processing, particularly in neuroimaging, with an emphasis on diffusion-weighted magnetic resonance imaging (MRI) related to Alzheimer's disease and aging. His lab has developed a comprehensive medical image processing system that supports over 400 IRB-approved projects, handling more than 100,000 imaging sessions. Dr. Landman aims to integrate image processing technologies with electronic health data to enhance personalized medicine and improve anatomical understanding. His work has significant implications for advancing biomarkers in clinical studies and addressing challenges in medical imaging through artificial intelligence.
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