Model Online / On-Site
Duration
Modules 5 modules

Course Objective & Scope

Many organisations either give staff access to more than one AI assistant or want deeper adoption of a chosen enterprise platform. This hands-on course compares and applies the strengths of ChatGPT Enterprise, Gemini for Workspace and Claude across deep reasoning, long-document analysis, data analysis, side-by-side editing with Canvas/Artifacts and persistent context in Projects/Gems.

Participants run real tasks from their own departments and build a team standard combining shared project spaces, role-based prompt templates and verification rules.

Who Should Attend?

  • Corporate teams using ChatGPT Enterprise/Team, Claude or Gemini for Workspace
  • Managers, analysts, consultants and domain specialists
  • Leads involved in selecting and rolling out internal AI tools
  • Prerequisite: no technical background required

Key Takeaways

  • Pick between fast chat, reasoning models and deep research modes based on the task
  • Co-edit documents and tables iteratively using Claude Artifacts and ChatGPT Canvas
  • Analyse long PDFs, contracts and spreadsheets while managing context effectively
  • Set up shared team workspaces with Projects, Custom GPTs and Gems
  • Protect confidential data by understanding enterprise privacy guarantees versus personal accounts

Curriculum

Choosing Assistants and Models: ChatGPT, Claude, Gemini
  • Differences between standard chat, reasoning models and deep research modes
  • Matching tasks to the right platform and feature
Advanced Prompting and Co-Editing with Canvas and Artifacts
  • Structured context, few-shot examples and self-critique prompts
  • Iterating on copy, tables and diagrams in Canvas and Artifacts
Multi-Document and Data Analysis
  • Querying bundles of reports, contracts and presentations together
  • Uploading CSV/Excel files for calculations, charts and summaries
Persistent Context: Projects, Custom GPTs and Gems
  • Setting up project spaces with department knowledge and standing instructions
  • Team sharing and a common prompt library
Enterprise Security, Verification and Working Standards
  • Data handling differences between enterprise and consumer accounts
  • Human review and verification protocols for critical outputs

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