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期間 21 時間
コース概要
- 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.
- Two discovery sessions
- 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.
- Tool onboarding
- 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.
- Sprint
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.
お客様の声 (3)
背景に関する包括性;プロンプトの作成方法。
Olaf Kannt - Helios Klinikum Krefeld
コース - Generative AI and Prompt Engineering in Healthcare
機械翻訳
このトレーニングから身につけられる、実践的なヒントと推奨プロンプト
Lee Mei Lin - ST Engineering IHQ Pte Ltd
コース - InVideo AI: Creating Engaging Short-Form Videos
機械翻訳
適切かつ効果的なプロンプトの活用
Marses Pacaldo
コース - Generative AI and Prompt Engineering for Corporate Professionals
機械翻訳
