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 课程时长 21 小时

课程大纲

  • Beforehand: Discovery
    • Two discovery sessions
      • Conversations with the client and the departments
      • Collecting problems and bottlenecks
      • Selecting tools that fit the company
      • Defining success criteria
      • Exercise: Create a list of five to eight challenges with data situation and contacts.
    • Outcome: Challenges, tool selection and success criteria are defined.
  • Day 1: Tools, teams and start of the sprint
    • Tool onboarding
      • 20 minutes of hands-on practice per tool
      • ChatGPT, Claude and Claude Cowork
      • Lovable and Cursor for prototypes
      • Make.com and n8n for automations
      • Industry-specific tools
      • Exercise: Solve a mini task with each tool.
    • Teams and challenge
      • Teams of three to four people
      • Selecting and sharpening the challenge
      • Solution sketch and tool choice for each team
      • Exercise: Capture a one-page solution sketch.
    • Sprint start
      • Building the first version
      • The trainer rotates between the teams
      • Coaching on tools, prompts and structure
      • Exercise: Reach a first working version by the evening.
    • Outcome: Each team has a sharpened challenge and a first working version.
  • Day 2: Sprint, demo and usage plan
    • Sprint
      • Building, testing, improving
      • Testing with real data or cases
      • Interim review in the morning
      • Exercise: Test the solution on three real cases.
    • Demo and evaluation
      • Pitch to the management
      • Evaluation by benefit and feasibility
      • Taking in feedback
      • Exercise: Present the solution in five minutes.
    • Usage plan
      • What will be used from next week
      • Metrics for success
      • Next expansion stages
      • Exercise: Write a usage plan with three steps for the own solution.
    • Outcome: Each team has a working solution, a presented pitch and a plan for use from the following week.

要求

  • Laptop, access to the approved AI tools, and willingness to bring a concrete problem from the own area.
  • No technical prior knowledge required.

Audience

  • Mixed teams from departments and IT who want to try AI on their own problems and take working solutions with them.

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