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课程时长 14 小时
课程大纲
- Day 1: ChatGPT in daily work
- Overview of the OpenAI ecosystem
- Models and reasoning models, and when longer thinking pays off
- Plus, Business and Enterprise compared, data protection and data use
- Differences from Claude, Copilot and Gemini
- Exercise: Solve a typical task with a fast model and a reasoning model and compare them.
- Instructions and personalization
- Building personal instructions (custom instructions)
- Checking, correcting and switching off memory, temporary chat
- Good prompts with goal, context, examples and format
- Sharpening results in a targeted way instead of starting over
- Exercise: Write own standing instructions and test their effect on two tasks.
- Files and data analysis
- Uploading, querying and comparing PDF, Word and Excel
- Analyses, charts and pivot overviews with the analysis tool
- Viewing calculation paths and spot-checking them
- Exercise: Analyze an anonymized Excel list and support three findings with a chart.
- Canvas, images and voice
- Editing texts and documents together in Canvas
- Creating and adjusting graphics and images for presentations
- Voice mode and dictation for notes and preparation
- Exercise: Revise a report in Canvas and create a matching graphic for a slide.
- Outcome: Each participant has own standing instructions, a verified data analysis and a revised text from their daily work.
- Overview of the OpenAI ecosystem
- Day 2: Extending ChatGPT with projects, GPTs and agents
- Projects for recurring work
- Creating projects with files and instructions
- Shared projects in the team
- Keeping order when many chats accumulate
- Exercise: Set up a project for an ongoing topic with three files and one instruction.
- Custom GPTs without code
- Instructions, knowledge files and conversation starters
- Quality check with test questions
- Sharing in the workspace, permissions and maintenance
- Exercise: Build a GPT for a common type of request in the team and check it with five test questions.
- Deep research and web search
- When to use web search, model knowledge or deep research
- Research assignment with question, sources, exclusions and format
- Checking sources and reading supporting passages
- Exercise: Write a deep research assignment on a technical topic and verify three sources.
- Connectors and the ChatGPT agent
- Connectors to file storage, mail and calendar
- The ChatGPT agent for multi-step tasks in the browser
- Approval points, limits and risks of autonomous workflows
- Scheduled tasks for recurring overviews
- Exercise: Hand over a multi-step research task to the agent and follow the workflow with approvals.
- Looking ahead and team rules
- What Codex and Sora mean for departments, without technical depth
- Rules for data, review and shared GPTs
- Personal plan for the next 30 days
- Exercise: Formulate three rules for use in the own team.
- Outcome: Each participant has a project, a shared custom GPT and a verified piece of research. The team knows the agent, connectors and its own rules.
- Projects for recurring work
要求
- Laptop, ChatGPT account (Business or Enterprise recommended, Plus possible), anonymized sample files from daily work.
- No programming skills required.
Audience
- Employees and teams who use ChatGPT Plus, Business or Enterprise and want to move from single chats to projects, custom GPTs and agents.
客户评论 (3)
全面了解背景知识；如何编写提示词。
Olaf Kannt - Helios Klinikum Krefeld
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机器翻译
通过本次培训，我们可以掌握的技巧和推荐的提示
Lee Mei Lin - ST Engineering IHQ Pte Ltd
课程 - InVideo AI: Creating Engaging Short-Form Videos
机器翻译
使用恰当且有效的提示
Marses Pacaldo
课程 - Generative AI and Prompt Engineering for Corporate Professionals
机器翻译
