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Byte Sized Series - Big Data Trunk https://project.bigdatatrunk.com Quality Corporate and Classroom Training in Bay Area CA Fri, 15 May 2026 14:28:33 +0000 en-US hourly 1 https://wordpress.org/?v=7.0 MS-500: Microsoft 365 Security Administrator https://project.bigdatatrunk.com/courses/ms-500-microsoft-365-security-administrator/ https://project.bigdatatrunk.com/courses/ms-500-microsoft-365-security-administrator/#respond Thu, 14 May 2026 17:47:27 +0000 https://www.bigdatatrunk.com/?post_type=lp_course&p=65914   AI developers, ML engineers, data scientists, and software professionals working with LLM-based applications

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  AI developers, ML engineers, data scientists, and software professionals working with LLM-based applications

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AZ-500: Microsoft Azure Security Technologies https://project.bigdatatrunk.com/courses/az-500-microsoft-azure-security-technologies/ https://project.bigdatatrunk.com/courses/az-500-microsoft-azure-security-technologies/#respond Thu, 14 May 2026 17:17:53 +0000 https://www.bigdatatrunk.com/?post_type=lp_course&p=65912 This course provides in-depth knowledge of implementing security controls, maintaining security posture, and managing identity and access in Microsoft Azure environments.

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AZ-500: Microsoft Azure Security Technologies


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This course provides in-depth knowledge of implementing security controls, maintaining security posture, and managing identity and access in Microsoft Azure environments.

  • Overview
  • Audience
  • Prerequisites
  • Curriculum
Description:

This course provides in-depth knowledge of implementing security controls, maintaining security posture, and managing identity and access in Microsoft Azure environments. Participants will learn how to protect data, applications, and networks in the cloud using Azure security technologies.

Through hands-on labs and real-world scenarios, learners will gain practical experience in managing security operations, configuring identity protection, implementing platform protection, and securing data and applications in Azure.

Duration: 

4 Days

Course Code: BDT89

Learning Objectives:

After this course, you will be able to:

  1. Manage identity and access using Azure Active Directory (Entra ID)
  2. Implement platform protection for Azure infrastructure
  3. Configure security operations and monitoring
  4. Secure data, applications, and networks in Azure
  5. Implement threat protection and vulnerability management
  6. Prepare for the AZ-500 certification exam

Security engineers, Azure administrators, IT professionals, and individuals preparing for the AZ-500 certification exam

Knowledge of Microsoft Azure services, networking, virtualization, and basic security concepts; AZ-104 or equivalent experience is recommended 

 

Course Outline:

Module 1: Manage Identity and Access

  1. Azure Active Directory (Entra ID) security features
  2. Identity protection and governance
  3. Role-Based Access Control (RBAC)
  4. Privileged Identity Management (PIM)

Module 2: Implement Platform Protection

  1. Network security (NSGs, Azure Firewall, DDoS Protection)
  2. Secure virtual networks and endpoints
  3. Host and container security
  4. Patch management and update strategies

Module 3: Manage Security Operations

  1. Azure Security Center (Microsoft Defender for Cloud)
  2. Security monitoring and alerts
  3. Log Analytics and SIEM (Microsoft Sentinel)
  4. Incident response and threat detection

Module 4: Secure Data and Applications

  1. Data encryption and key management (Azure Key Vault)
  2. Application security and identity integration
  3. Secure storage and databases
  4. API and app protection

Module 5: Governance, Risk, and Compliance

  1. Azure Policy and Blueprints
  2. Regulatory compliance and standards
  3. Security posture management
  4. Risk assessment and mitigation

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Certified Information Systems Security Professional (CISSP) https://project.bigdatatrunk.com/courses/certified-information-systems-security-professional-cissp/ https://project.bigdatatrunk.com/courses/certified-information-systems-security-professional-cissp/#respond Tue, 12 May 2026 09:37:36 +0000 https://www.bigdatatrunk.com/?post_type=lp_course&p=65844 This course provides comprehensive coverage of the CISSP Common Body of Knowledge (CBK) and prepares participants for the CISSP certification exam.

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Certified Information Systems Security Professional (CISSP)

This course provides comprehensive coverage of the CISSP Common Body of Knowledge (CBK) and prepares participants for the CISSP certification exam.

  • Overview
  • Audience
  • Prerequisites
  • Curriculum
Description:

This course provides comprehensive coverage of the CISSP Common Body of Knowledge (CBK) and prepares participants for the CISSP certification exam. It covers the eight domains of information security, including risk management, asset security, security architecture, network security, identity management, and security operations.

Through instructor-led sessions, real-world examples, and practice questions, participants will gain a deep understanding of security principles, frameworks, and best practices required to design, implement, and manage a secure enterprise environment.

Duration:

1Day

Course Code: BDT82

Learning Objectives:

After this course, you will be able to:

  1.  Understand the CISSP CBK domains and core security concepts

  2. Apply risk management and security governance principles

  3. Design and implement secure network and system architectures

  4. Manage identity and access control mechanisms

  5. Implement security operations and incident response strategies

  6. Understand legal, regulatory, and compliance requirements
  7. Prepare effectively for the CISSP certification exam

IT professionals, security analysts, security consultants, auditors, network architects, and professionals preparing for the CISSP certification

Basic understanding of IT infrastructure, networking, and security concepts; at least 2–5 years of experience in IT/security is recommended 

 

Course Outline:

Module 1: Security and Risk Management

  1. Security principles and governance
  2. Risk management processes
  3. Compliance, laws, and regulations
  4. Ethics and professional conduct

Module 2: Asset Security

  1. Data classification and ownership
  2. Data handling and protection methods
  3. Privacy and data security controls

Module 3: Security Architecture and Engineering

  1. Secure design principles
  2. Cryptography fundamentals
  3. Security models and frameworks
  4. Physical security considerations

Module 4: Communication and Network Security

  1. Network architecture and secure design
  2. Secure communication channels
  3. Network attacks and defenses

Module 5: Identity and Access Management (IAM)

  1. Authentication and authorization mechanisms
  2. Identity lifecycle management
  3. Access control models

Module 6: Security Assessment and Testing

  1. Security testing strategies
  2. Vulnerability assessments and penetration testing
  3. Audit and compliance checks

Module 7: Security Operations

  1. Incident response and handling
  2. Disaster recovery and business continuity
  3. Logging, monitoring, and investigations

Module 8: Software Development Security

  1. Secure software development lifecycle (SDLC)
  2. Application security principles
  3. Common vulnerabilities (OWASP Top 10)

Training Material Provided

  1. Comprehensive CISSP study guide aligned with CBK
  2. Practice questions and mock exams
  3. Case studies and real-world security scenarios
  4. Quick revision notes and exam tips

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Introduction to Deep Learning https://project.bigdatatrunk.com/courses/introduction-to-deep-learning/ https://project.bigdatatrunk.com/courses/introduction-to-deep-learning/#respond Tue, 12 May 2026 09:35:54 +0000 https://www.bigdatatrunk.com/?post_type=lp_course&p=65843 This course provides a foundational introduction to deep learning, a subset of artificial intelligence focused on neural networks and data-driven learning.

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Introduction to Deep Learning

This course provides a foundational introduction to deep learning, a subset of artificial intelligence focused on neural networks and data-driven learning. 

  • Overview
  • Audience
  • Prerequisites
  • Curriculum
Description:

This course provides a foundational introduction to deep learning, a subset of artificial intelligence focused on neural networks and data-driven learning. Participants will explore how deep learning models work, understand key architectures, and learn how these models are applied in real-world scenarios such as image recognition, natural language processing, and speech analysis.

Through conceptual explanations and basic demonstrations, learners will gain a clear understanding of how deep learning differs from traditional machine learning and how it powers modern AI applications.

Duration:

1Day

Course Code: BDT66

Learning Objectives:

After this course, you will be able to:

  1. Understand the fundamentals of deep learning and neural networks

  2. Explain how deep learning differs from traditional machine learning

  3. Identify key components such as layers, neurons, and activation functions

  4. Recognize common deep learning architectures (CNNs, RNNs, etc.)

  5. Understand how deep learning models are trained and evaluated

  6. Explore real-world applications of deep learning

Beginners in AI/ML, students, data analysts, and developers interested in deep learning concepts

 Basic knowledge of Python and fundamental machine learning concepts

 

Course Outline:

Module 1: Introduction to Deep Learning

  1. What is deep learning
  2. Evolution from machine learning to deep learning
  3. Key use cases and applications

Module 2: Neural Network Fundamentals

  1. Structure of artificial neural networks
  2. Neurons, layers, and connections
  3. Activation functions

Module 3: Training Deep Learning Models

  1. Forward and backward propagation
  2. Loss functions and optimization
  3. Overfitting and model evaluation

Module 4: Deep Learning Architectures

  1. Introduction to Convolutional Neural Networks (CNNs)
  2. Introduction to Recurrent Neural Networks (RNNs)
  3. Overview of modern architectures (Transformers)

Module 5: Tools and Frameworks

  1. Overview of popular frameworks (TensorFlow, PyTorch)
  2. Basic workflow for building models
  3. Demonstration of a simple model

Module 6: Applications of Deep Learning

  1. Computer vision use cases
  2. Natural language processing
  3. Speech and recommendation systems

Module 7: Challenges and Future Trends

  1. Data requirements and computational needs
  2. Ethical considerations
  3. Emerging trends in deep learning

Training Material Provided

  1. Presentation slides and conceptual diagrams
  2. Sample notebooks and basic code examples
  3. Case studies and real-world examples
  4. Reference guide for deep learning concepts

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Cited Search and Grounded Q&A with NotebookLM https://project.bigdatatrunk.com/courses/cited-search-and-grounded-qa-with-notebooklm/ https://project.bigdatatrunk.com/courses/cited-search-and-grounded-qa-with-notebooklm/#respond Sun, 10 May 2026 17:42:27 +0000 https://www.bigdatatrunk.com/?post_type=lp_course&p=65807 NotebookLM's source-grounded chat eliminates the guesswork and risk of AI hallucination.

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Cited Search and Grounded Q&A with NotebookLM

NotebookLM’s source-grounded chat eliminates the guesswork and risk of AI hallucination. This session explores how to ask questions of your uploaded documents and receive answers that link directly back to original passages, with full transparency and verifiability.

  • Overview
  • Audience
  • Prerequisites
  • Curriculum
Description:

NotebookLM's source-grounded chat eliminates the guesswork and risk of AI hallucination. This session explores how to ask questions of your uploaded documents and receive answers that link directly back to original passages, with full transparency and verifiability. Participants will learn to structure effective queries, organise document sets for reliable retrieval, and use NotebookLM's suggested questions to surface insights they might not have considered. Whether you're conducting research, managing compliance, or extracting value from large document collections, this hands-on session shows you how to build a querying workflow that delivers accurate, cited answers every time.

Duration:

90 minutes

Course Code: BDT624

Learning Objectives:

After this course, you will be able to:

  1. Understand how source-grounded search and chat differ from general AI chat
  2. Effectively upload, organize, and structure document sets in NotebookLM
  3. Craft targeted questions designed for accurate, cited retrieval
  4. Use inline citations to trace answers back to specific source passages and verify accuracy
  5. Leverage suggested questions and conversational follow-ups to surface deeper insights
  6. Design a sustainable querying workflow for document sets relevant to their work or research
  1. Researchers and analysts working with large document collections
  2. Compliance and legal professionals needing verifiable, cited answers
  3. Operations and project managers extracting insights from reports and documentation
  4. Students and knowledge workers organizing complex source material
  5. Anyone seeking AI-assisted research with built-in source verification
  1. Google account with access to Google NotebookLM (free)
  2. Familiarity with basic document uploads and cloud storage
  3. A sample document or document set you'd like to explore (optional but recommended)
  4. Basic understanding of how AI search differs from traditional keyword search

 

Course Outline:
  1. How NotebookLM Works: Source-Grounding vs. General AI Chat
  2. The Problem with Hallucination and How Citations Solve It
  3. Preparing Documents: Best Practices for Upload and Organization
  4. Hands-On: Uploading Your First Document Set
  5. Asking Effective Questions: Prompting Strategies for Cited Responses
  6. Understanding Inline Citations: Tracing Answers to Source Passages
  7. Using Suggested Questions to Discover Hidden Insights
  8. Real-World Applications: Research, Compliance, Operations, and Knowledge Management
  9. Building Your NotebookLM Workflow: Document Organization to Query Execution
  10. Live Demo and Q&A

 

Training Materials Provided: Yes (Digital Format)

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Using AI to Brainstorm, Test, and Plan https://project.bigdatatrunk.com/courses/using-ai-to-brainstorm-test-and-plan/ https://project.bigdatatrunk.com/courses/using-ai-to-brainstorm-test-and-plan/#respond Sun, 10 May 2026 17:41:12 +0000 https://www.bigdatatrunk.com/?post_type=lp_course&p=65806 Some of the best thinking happens away from your desk. This session explores how AI voice and conversational tools can serve as always-available thought partners for leaders, managers, and knowledge workers.

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Using AI to Brainstorm, Test, and Plan

Some of the best thinking happens away from your desk. This session explores how AI voice and conversational tools can serve as always-available thought partners for leaders, managers, and knowledge workers.

  • Overview
  • Audience
  • Prerequisites
  • Curriculum
Description:

Some of the best thinking happens away from your desk. This session explores how AI voice and conversational tools can serve as always-available thought partners for leaders, managers, and knowledge workers. Rather than working through complex decisions alone or waiting for a meeting, participants will practice using AI for real-time brainstorming, stress-testing assumptions, rehearsing difficult conversations, and thinking through strategic decisions, hands-free and on the go. Walk away with practical techniques for turning AI into your most reliable sounding board for critical thinking and decision-making.

Duration:

90 minutes

Course Code: BDT623

Learning Objectives:

After this course, you will be able to:

  1. Understand how AI voice and conversational modes enhance strategic thinking and planning
  2. Use AI to brainstorm ideas, challenge assumptions, and develop plans in real time
  3. Employ voice mode effectively to rehearse presentations, difficult conversations, and decision frameworks
  4. Apply different prompting techniques for reflective, analytical, and exploratory dialogue
  5. Build sustainable habits of AI-assisted strategic reflection and decision-making
  1. Leaders and managers navigating complex decisions
  2. Knowledge workers and strategists seeking thinking support
  3. Professionals who spend time away from their desk (traveling, in meetings, commuting)
  4. Anyone looking to improve decision-making through structured dialogue and idea stress-testing
  1. Access to at least one AI tool with voice or chat capabilities ChatGPT, Google Gemini, Claude
  2. Familiarity with basic AI prompting and conversational interactions
  3. A real workplace challenge or decision you're currently thinking through (optional but recommended)
Course Outline:
  1. How AI Voice and Conversational Modes Work: Capabilities and Limitations
  2. The Science of Thinking Out Loud: Why Dialogue Accelerates Clarity
  3. Prompting for Strategic Dialogue: Questions, Challenges, and Frameworks
  4. Hands-On: Real-Time Brainstorming with AI Voice Tools
  5. Stress-Testing Plans: Using AI to Challenge Assumptions and Identify Blind Spots
  6. Rehearsal Mode: Preparing for High-Stakes Conversations and Presentations
  7. Practical Scenarios: Leadership Decisions, Complex Planning, and Problem-Solving
  8. Building Your AI Thinking Practice: Sustainable Habits and Workflows
  9. Live Demo and Q&A

Training Materials Provided: Yes (Digital Format - Prompting Templates, Decision-Making Frameworks, Voice Mode Best Practices Guide)

 

 

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Personal AI Assistant: Encoding Your Professional Voice https://project.bigdatatrunk.com/courses/personal-ai-assistant-encoding-your-professional-voice/ https://project.bigdatatrunk.com/courses/personal-ai-assistant-encoding-your-professional-voice/#respond Sun, 10 May 2026 16:31:00 +0000 https://www.bigdatatrunk.com/?post_type=lp_course&p=65793   Every professional has a distinctive voice, set of values, and way of communicating. This hands-on session explores how to use system instructions and persona prompting to encode your professional identity into AI tools, so that they generate drafts, replies, and communications that genuinely sound like you.

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Personal AI Assistant: Encoding Your Professional Voice

This hands-on session explores how to use system instructions and persona prompting to encode your professional identity into AI tools, so that they generate drafts, replies, and communications that genuinely sound like you

  • Overview
  • Audience
  • Prerequisites
  • Curriculum
Description:

Every professional has a distinctive voice, set of values, and way of communicating. This hands-on session explores how to use system instructions and persona prompting to encode your professional identity into AI tools, so that they generate drafts, replies, and communications that genuinely sound like you. Rather than wrestling with generic AI outputs, you'll build a persistent AI persona trained to reflect your unique writing style. Participants will practice writing effective system instructions, test them across real communication scenarios, and walk away with a reusable AI "voice template" for their most important workflows.

Duration:

90 minutes

Course Code: BDT622

Learning Objectives:

After this course, you will be able to:

  1. Understand how system instructions and persona prompting work within AI tools
  2. Identify and articulate their unique professional voice, tone, and values
  3. Write effective system instructions that capture your writing style and communication patterns
  4. Test and refine persona prompts across different communication types (emails, reports, creative content)
  5. Build a reusable AI persona template for their primary workflow
  1. Executives and professionals seeking to scale their communication style
  2. Content creators and writers wanting to maintain voice consistency
  3. Business professionals tired of editing AI-generated content to sound like themselves
  4. Remote workers and managers who communicate primarily through written channels
  1. Access to at least one free AI tool (ChatGPT, Google Gemini, or Claude)
  2. Basic familiarity with AI chatbots and how to write prompts
  3. A sample of your own professional writing (email, document, or communication style example)

 

Course Outline:
  1. What Are System Instructions? How AI Tools Learn Your Style
  2. Deconstructing Professional Voice: Tone, Values, and Communication Patterns
  3. Hands-On: Writing Your First Persona Prompt
  4. Testing Your Persona Across Scenarios (Emails, Reports, Social Content)
  5. Practical Examples: Real Professional Communications Refined with AI
  6. Troubleshooting Common Issues: When AI Doesn't Sound Like You
  7. Live Demo: Refining and Iterating Your AI Persona in Real Time
  8. Q&A and Feedback

 

Training Materials Provided: Yes (Digital Format -  Persona Prompt Guide, System Instruction Examples)

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Mapping Knowledge Connections with NotebookLM https://project.bigdatatrunk.com/courses/mapping-knowledge-connections-with-notebooklm/ https://project.bigdatatrunk.com/courses/mapping-knowledge-connections-with-notebooklm/#respond Sat, 09 May 2026 11:10:00 +0000 https://www.bigdatatrunk.com/?post_type=lp_course&p=65770 Mapping Knowledge Connections with NotebookLM Synthesizing insights across multiple documents is one of the most cognitively demanding tasks in research…

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Mapping Knowledge Connections with NotebookLM

Synthesizing insights across multiple documents is one of the most cognitively demanding tasks in research and knowledge work. NotebookLM is designed to support these tasks very efficiently.

  • Overview
  • Audience
  • Prerequisites
  • Curriculum
Description:

Synthesizing insights across multiple documents is one of the most cognitively demanding tasks in research and knowledge work. NotebookLM is designed to support these tasks very efficiently. This session explores how NotebookLM surfaces hidden relationships, recurring themes, and cross-document connections, helping you see the bigger picture across your entire knowledge base.

Duration:

90 minutes

Course Code: BDT617

Learning Objectives:

After this course, you will be able to:

  1. Upload a multi-document collection and use NotebookLM to identify cross-document themes and patterns.
  2. Use the Mind Map and synthesis features to visualize relationships across sources.
  3. Build a connected knowledge base that enables deeper insight and faster synthesis.
  1. Researchers, journalists, and investigators working across multiple sources or reports.
  2. Product managers and strategists synthesizing competitive research, user interviews, or market data.
  3. Knowledge workers managing large document libraries who need to extract overarching insights.

Participants should have a basic understanding of NotebookLM; ideally bring 3–5 related documents to work with.

 

Course Outline:
  1. How NotebookLM surfaces connections and patterns across multiple uploaded documents
  2. Building a multi-source notebook: what to upload and how to organize it
  3. Generating and reading the Mind Map: interpreting themes, clusters, and relationships
  4. Using cross-document Q&A to probe connections and contradictions
  5. Creating synthesis notes and building a living, connected knowledge base.

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Generating Study Flashcards with NotebookLM https://project.bigdatatrunk.com/courses/generating-study-flashcards-with-notebooklm/ https://project.bigdatatrunk.com/courses/generating-study-flashcards-with-notebooklm/#respond Sat, 09 May 2026 10:10:43 +0000 https://www.bigdatatrunk.com/?post_type=lp_course&p=65755 Active recall is one of the most evidence-backed study techniques available, and NotebookLM makes it easier than ever to apply it to your own learning material. This session shows students and lifelong learners how to supercharge their study sessions.

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Generating Study Flashcards with NotebookLM

Active recall is one of the most evidence-backed study techniques available, and NotebookLM makes it easier than ever to apply it to your own learning material.

  • Overview
  • Audience
  • Prerequisites
  • Curriculum
Description:

Active recall is one of the most evidence-backed study techniques available, and NotebookLM makes it easier than ever to apply it to your own learning material. This session shows students and lifelong learners how to supercharge their study sessions.

Duration:

90 minutes

Course Code: BDT616

Learning Objectives:

After this course, you will be able to:

  1. Generate accurate, curriculum-aligned flashcards from uploaded study material using NotebookLM.
  2. Customize and curate AI-generated flashcards for focused review sessions.
  3. Integrate NotebookLM flashcards into an active recall study routine.
  1. Students at school, university, or professional certification level preparing for exams.
  2. Lifelong learners who want efficient study tools from books, articles, or online content.
  3. Educators looking to create revision aids for their students quickly.

No prerequisites; participants should bring their own study material (PDFs, notes, textbook chapters).

 

Course Outline:
  1. Introduction to NotebookLM's study tools: flashcards, Q&A, and summaries
  2. Uploading study material and organizing it into focused notebooks
  3. Generating flashcards: how NotebookLM identifies key concepts and terms
  4. Reviewing, editing, and pruning your flashcard set for quality
  5. Active recall strategies: using your AI flashcards for maximum retention

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Conducting Cited Research and Q&A with NotebookLM https://project.bigdatatrunk.com/courses/conducting-cited-research-and-qa-with-notebooklm/ https://project.bigdatatrunk.com/courses/conducting-cited-research-and-qa-with-notebooklm/#respond Sat, 09 May 2026 09:45:10 +0000 https://www.bigdatatrunk.com/?post_type=lp_course&p=65742 Grounded, source-cited responses represent a significant advancement in how professionals and researchers can interact with large volumes of documentation

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Conducting Cited Research and Q&A with NotebookLM

Grounded, source-cited responses represent a significant advancement in how professionals and researchers can interact with large volumes of documentation

  • Overview
  • Audience
  • Prerequisites
  • Curriculum
Description:

Grounded, source-cited responses represent a significant advancement in how professionals and researchers can interact with large volumes of documentation. This session shows you how to ask precise questions, get sourced answers, and use NotebookLM's cited Q&A to research, verify, and extract insights faster than ever.

Duration:

90 minutes

Course Code: BDT615

Learning Objectives:

After this course, you will be able to:

  1. Perform grounded Q&A sessions with uploaded documents and interpret cited responses.
  2. Design effective questions to extract specific insights from complex source material.
  3. Use citation trails to verify AI-generated answers and trace information back to its source.
  1. Researchers, analysts, and legal professionals who need accurate, traceable answers from documents.
  2. Students working with academic papers, textbooks, or case studies.
  3. Business teams dealing with large policy documents, contracts, or technical manuals.

No prerequisites; helpful if participants bring a set of documents they work with regularly.

 

Course Outline:
  1. Understanding NotebookLM's grounded Q&A and how it differs from general AI chat
  2. Uploading a document set and setting up your research notebook
  3. Asking effective questions: specificity, scope, and framing for better answers
  4. Reading and using citations: tracing every answer back to its source
  5. Building a research workflow: iterative questioning, note-taking, and synthesis

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