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Course Outline

Applied Artificial Intelligence Workshop

Structure: Intensive, hands-on training session

Objective: Cultivate operational proficiency in leading AI frameworks and practical government workflows.

Module 1 – AI Platform Capabilities and Comparative Analysis (75 minutes)

This section provides an overview of the fundamental features of premier AI platforms utilized in contemporary professional and public sector environments.

Platforms analyzed:

• ChatGPT

• Google Gemini

• Microsoft Copilot

Subject matter covered:

• Document processing protocols and file constraints

• Context window dynamics

• Data management standards and privacy implications

• Functional tools and system integrations

• Process automation and workflow capabilities

• Advantages and constraints of each platform

Instructor-led Demonstration

The instructor illustrates key features and differentiates between platforms by demonstrating real-world application scenarios relevant to government operations.

Independent Practical Exercise

Participants construct a personalized AI tool comparison matrix using a provided standardized template.

Assessment criteria:

• Usability and user experience

• Quality and accuracy of generated content

• Information retrieval and research capacity

• Potential for workflow integration

Learning outcomes for this module:

• Distinguish between major AI platforms and their respective capabilities

• Identify specific strengths and limitations of each tool

• Select the appropriate AI tool for diverse professional tasks

 

Module 2 – Research and Multimodal Laboratory (90 minutes)

This segment focuses on the application of AI for research synthesis, information consolidation, and critical evaluation of data.

Exercise 1 Long-Form Document Reasoning

Independent Practical Exercise

Participants process a multi-document dataset to evaluate cross-platform analytical performance.

Assessment criteria:

• Citation integrity

• Logical coherence

• Depth of synthesis

• Summarization of complex material

Exercise 2 Hallucination Detection Protocol

Independent Practical Exercise

Participant actions:

• Query obscure factual information

• Manually verify cited sources

• Compare response consistency across tools

Group discussion addresses techniques for identifying and mitigating potential hallucinations.

Exercise 3 Voice Interaction Laboratory

Guided Practical Exercise

Participant actions:

• Utilize voice interaction for ideation

• Interrupt AI responses during generation

• Request revisions through conversational prompts

Debrief discussion topics:

• Scenarios where voice interaction outperforms text input

• Situations where structured prompting yields superior results

Learning outcomes for this module:

• Assess AI responses for accuracy and reliability

• Utilize AI tools for research and document analysis

• Apply verification techniques to detect erroneous information

 

Module 3 – Custom AI Assistant Development (2 hours)

Participants examine how modern AI frameworks enable the creation of custom assistants tailored to specific operational needs.

Platforms introduced:

• ChatGPT Custom GPTs

• Google Gemini Gems

• Microsoft Copilot Agents

Instructor-led Demonstration

The instructor demonstrates the process of building a custom AI assistant, covering:

• Defining objective and scope

• Drafting instructions and behavioral guidelines

• Uploading reference documents

• Testing and refining response quality

Independent Practical Exercise

Participants select one platform to develop a custom AI assistant.

Participant actions:

• Define the assistant’s intended purpose

• Create instructions and system guidance

• Upload supporting documents or knowledge bases

• Test behavior and refine outputs

Instructor provides active facilitation and technical troubleshooting.

Learning outcomes for this module:

• Design custom AI assistants for specific workflows

• Configure instructions and knowledge sources

• Deploy assistants that automate routine knowledge tasks

 

Module 4 – Workflow Automation Laboratory (90 minutes)

Participants investigate how AI can optimize real-world work processes through integration with productivity software.

Participants select one of two workflow tracks.

Track A – Microsoft Ecosystem

Participant tasks using Microsoft tools:

• Analyze Excel datasets

• Generate insights and summaries

• Convert findings into PowerPoint presentations

Track B – Google Ecosystem

Participant tasks using Google tools:

• Analyze documents stored in Google Drive

• Generate structured reports

• Create summarized outputs for email communication

Comprehensive facilitator support is provided during the exercises.

Learning outcomes for this module:

• Utilize 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 facilitate data exploration, code generation, and visualization.

Python and Data Visualization Exercise

Independent Practical Exercise

Participant tasks using AI tools:

• Perform exploratory data analysis

• Generate charts and visualizations

• Refine insights through iterative prompting

Platform comparison criteria:

• Code transparency

• Error correction and debugging capabilities

• Clarity of visualizations

Discussion focuses on how non-technical staff can leverage AI-assisted data analysis.

Learning outcomes for this module:

• Use AI tools to analyze datasets

• Generate visualizations and insights

• Iterate on data analysis using AI-assisted workflows

Requirements

Required 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

 4 Hours

Number of participants


Price per participant

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