Course Outline
Applied AI Workshop
Format: Deep hands-on workshop
Goal: Develop practical AI proficiency across leading AI platforms and real-world workflows.
Module 1 – AI Platform Capabilities and Comparison (75 minutes)
This module introduces participants to the core capabilities of leading AI platforms used in modern workplaces.
Platforms compared:
• ChatGPT
• Google Gemini
• Microsoft Copilot
Topics explored:
• File handling and document limits
• Context window behavior
• Data handling and privacy considerations
• Available tools and integrations
• Automation and workflow capabilities
• Strengths and limitations of each platform
Instructor Demonstration
The instructor walks through key features and differences between platforms while demonstrating real-world use cases.
Independent Hands-On
Participants create their own AI tool comparison matrix using a provided template.
Participants evaluate:
• Ease of use
• Output quality
• Research capabilities
• Workflow integration potential
By the end of this module participants will be able to:
• Compare major AI platforms and their capabilities
• Identify strengths and limitations of each tool
• Select the appropriate AI tool for different types of work tasks
Module 2 – Research and Multimodal Lab (90 minutes)
This module focuses on using AI for research, synthesis, and critical evaluation of information.
Exercise 1 Long Document Reasoning
Independent Hands-On
Participants upload a multi-document dataset and test analysis across two AI platforms.
Participants evaluate:
• Citation quality
• Logical consistency
• Depth of synthesis
• Ability to summarize complex material
Exercise 2 Hallucination Detection Drill
Independent Hands-On
Participants:
• Ask obscure factual questions
• Verify citations manually
• Compare responses across tools
Group discussion focuses on techniques for identifying and mitigating hallucinations.
Exercise 3 Voice Interaction Lab
Guided Hands-On
Participants:
• Brainstorm ideas using voice interaction
• Interrupt the AI mid-response
• Request revisions conversationally
Debrief discussion covers:
• When voice interaction is more effective than typing
• When structured prompting works better
By the end of this module participants will be able to:
• Evaluate AI responses for accuracy and reliability
• Use AI tools for research and document analysis
• Apply verification techniques to detect hallucinated information
Module 3 – Custom AI Assistants (2 hours)
Participants explore how modern AI platforms allow users to create custom assistants tailored to specific tasks.
Platforms introduced:
• ChatGPT Custom GPTs
• Google Gemini Gems
• Microsoft Copilot Agents
Instructor Demonstration
The instructor demonstrates how to build a custom AI assistant including:
• Defining purpose and scope
• Writing instructions and behavioral guidance
• Uploading knowledge documents
• Testing and refining responses
Independent Hands-On
Participants choose one platform and build their own custom AI assistant.
Participants:
• Define the assistant’s purpose
• Create instructions and system guidance
• Upload supporting documents or knowledge
• Test behavior and refine outputs
Instructor provides active facilitation and troubleshooting.
By the end of this module participants will be able to:
• Design custom AI assistants for specific workflows
• Configure instructions and knowledge sources
• Deploy assistants that automate common knowledge tasks
Module 4 – Workflow Automation Lab (90 minutes)
Participants explore how AI can streamline real-world work processes by integrating with productivity tools.
Participants choose one of two workflow tracks.
Track A – Microsoft Ecosystem
Participants use AI with Microsoft tools to:
• Analyze Excel datasets
• Generate insights and summaries
• Convert findings into PowerPoint presentations
Track B – Google Ecosystem
Participants use AI with Google tools to:
• Analyze documents stored in Google Drive
• Generate structured reports
• Create summarized outputs for email communication
Heavy facilitator support is provided during the exercises.
By the end of this module participants will be able to:
• Use AI to accelerate analysis workflows
• Integrate AI outputs with productivity tools
• Design simple automation pipelines for common tasks
Module 5 – Advanced Data Analysis with AI (75 minutes)
Participants explore how AI tools assist with data exploration, code generation, and visualization.
Python and Data Visualization Exercise
Independent Hands-On
Participants upload a dataset and use AI tools to:
• Perform exploratory data analysis
• Generate charts and visualizations
• Refine insights through iterative prompting
Participants compare platform behavior in terms of:
• Code transparency
• Error correction and debugging
• Visualization clarity
Discussion focuses on how non-developers can leverage AI-assisted data analysis.
By the end of this module participants will be able to:
• Use AI tools to analyze datasets
• Generate visualizations and insights
• Iterate on data analysis using AI-assisted workflows
Requirements
An understanding of:
• Basic workplace productivity tasks such as research, writing, document creation, and information analysis
• How AI assistants can support common professional workflows
Experience with:
• Using AI tools such as ChatGPT, Google Gemini, and Microsoft CoPilot for basic prompting or task assistance
Programming experience:
• No programming experience is required
Participants should have access to at least one AI platform (free versions are sufficient).
Audience
• Analysts
• Researchers
• Business professionals
• AI champions exploring practical AI workflows
