Introductory practical course for analysts who want to incorporate AI into their daily work. Participants will learn how to use AI in collecting requirements, creating processes and writing documentation, how to correctly assign tasks to it [...]
  • GOC4607
  • Duration 1 day
  • 10 ITK points
  • 0 terms
  • ČR (9 995 Kč)

    SR (420 €)

  • Beginner

Introductory practical course for analysts who want to incorporate AI into their daily work. Participants will learn how to use AI in collecting requirements, creating processes and writing documentation, how to correctly assign tasks to it and how to verify its outputs. An equally important part of the course is where AI cannot be relied on and why. The course is based on practical exercises and participants will take away procedures from it that they can use the next day at work. The course assumes basic experience with AI tools.

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The course is intended for business and IT analysts, product owners and other professions who work with requirements, processes and documentation and want to incorporate AI into their work. It is a suitable preparation for the course Artificial Intelligence in Practice: From Idea to Real Deployment (GOC4606).

  • recognize which analyst tasks are suitable for AI and which are not

  • work safely with data when using AI

  • correctly specify AI tasks

  • use AI when collecting requirements

  • create processes and diagrams with the help of AI

  • use AI when writing documentation

  • verify AI outputs

  • Basic orientation in the work of an analyst

  • Experience with AI tools is not necessary

AI in the work of an analyst

  • Possibilities and limits of language models
  • Suitable and unsuitable tasks for AI
  • Data security and confidentiality

Assigning AI tasks

  • Principles of good assignment
  • Working with documents
  • Templates for repetitive tasks

AI in collecting requirements

  • Preparation for an interview and workshop
  • Processing outputs from meetings

Creating processes using AI

  • From text to process model
  • Generating diagrams
  • Process control

AI in writing documentation

  • Creating and editing texts
  • Data model and interface

Verifying AI outputs

  • Consistency check

Typical AI errors

Where AI cannot be relied upon

  • Limits of using AI in analysis
  • Final exercise
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