INTRODUCTION FOR AI FOR R&D PRODUCTIVITY: RESEARCH, ANALYSIS & SCIENTIFIC DOCUMENTATION ENHANCING INNOVATION, ACCURACY & EFFICIENCY WITH AI TOOLS
This 2-day hands-on workshop is designed specifically for R&D professionals in the health supplement industry, focusing on how AI can enhance research, data analysis, documentation, and knowledge management.
Participants will learn how to use AI tools such as NotebookLM, Perplexity, Claude, Gemini, and Microsoft AI tools to:
- Conduct research using reliable sources
- Analyze scientific and experimental data
- Summarize articles, videos, and research papers
- Generate reports and documentation
- Create presentation slides and visual outputs
The training emphasizes accuracy, traceability, and responsible AI usage, ensuring outputs are suitable for research, product development, and compliance environments.
COURSE OBJECTIVES
By the end of this program, participants will be able to:
- Use AI tools to conduct structured research from reliable sources
- Summarize scientific articles, videos, and documents efficiently
- Apply AI for data analysis and insight generation
- Generate structured R&D documentation and reports
- Create visual outputs such as slides, infographics, and mind maps
- Improve productivity in research workflows using AI
- Understand limitations, risks, and validation methods for AI outputs
LEARNING OUTCOMES
Participants will be able to:
- Extract and summarize information from research papers and videos
- Use Perplexity to retrieve reliable, cited research data
- Use NotebookLM for structured documentation and knowledge management
- Apply Claude or Gemini for data analysis and interpretation
- Convert research findings into slides, mind maps, and infographics
- Generate meeting summaries and research notes using AI tools
- Integrate AI into R&D workflows for faster and more accurate output
WHO SHOULD ATTEND
- R&D Scientists and Researchers
- Product Development Teams
- Quality Assurance / Regulatory Teams
- Technical and Laboratory Staff
- Innovation and Research Analysts
Prerequisites:
Basic computer literacy and familiarity with research documentation.
COURSE METHODOLOGY
- 20% Theory
Understanding AI concepts, tools, and research accuracy - 80% Hands-On Practice
Participants work with real R&D scenarios and datasets - Live Demonstrations
Step-by-step use of AI tools for research and reporting
COURSE CONTENT
DAY 1 – AI for Research & Knowledge Extraction
Module 1 : AI Awareness for R&D
- Introduction to AI in research environments
- AI vs traditional research methods
- Understanding AI limitations and accuracy risks
- Importance of validation in scientific work
Module 2 : Research with Perplexity (Reliable Sources)
Topics Covered
- Using Perplexity for research with citations
- Searching for scientific articles and references
- Comparing multiple sources
- Extracting validated information
Practical Application
- Research ingredient benefits and clinical studies
- Compare sources for product formulation
Module 3 : NotebookLM – Source-Based Research & Summarization
Topics Covered
- Uploading research documents (PDF, articles)
- Managing multiple sources
- Asking questions based on sources
- Citation tracking and validation
Practical Application
- Summarize research papers
- Extract key findings and conclusions
Module 4 : NotebookLM Studio Tools
Topics Covered
- Audio overview from research content
- Generating slide deck from documents
- Mindmap generation from research
- Converting content into infographic structure
Practical Application
- Create a research summary presentation
- Generate visual knowledge map
Module 5: Multi-Source Learning (Video + Article + Data)
Topics Covered
- Extract insights from videos and articles
- Combine multiple knowledge sources
- Convert unstructured data into structured output
- Build research summary reports
Practical Application
- Analyze supplement-related video and article
- Create structured summary report
DAY 2 – AI for Data Analysis, Documentation & Reporting
Module 6: AI for Data Analysis (Claude / Gemini)
Topics Covered
- Upload and analyze dataset
- Identify trends and patterns
- Generate insights from experimental data
- Create summary outputs
Practical Application
- Analyze sample product test data
- Generate findings and interpretation
Module 7: AI for Scientific Documentation
Topics Covered
- Generating structured reports
- Writing technical documentation
- Converting notes into formal reports
- Using NotebookLM for documentation consistency
Practical Application
- Generate R&D report from raw data
Module 8: AI for Presentation & Communication
Topics Covered
- Generating presentation slides using AI
- Structuring technical content for stakeholders
- Creating executive summary slides
Practical Application
- Convert research into presentation slides
Module 9: Live Meeting Transcript & Summary
Topics Covered
- Using Microsoft Word AI for live transcription
- Converting meeting notes into structured summary
- Extracting action items and decisions
Practical Application
- Simulate meeting summary generation
Module 10: Integration – R&D AI Workflow
Participants will:
- Conduct research using Perplexity
- Summarize using NotebookLM
- Analyze data using Claude / Gemini
- Create report and presentation
Final Presentation & Wrap-Up
- Present findings
- Review AI workflow
- Key takeaways
- Q&A
