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Machine Learning Engineer
1. overview and introduction Artificial Intelligence in Requirements Engineering
- Definition and basics of artificial intelligence
- The basics of effective prompting
- Applications and advantages of AI in requirements engineering
2. AI tools and technologies in requirements engineering
- Overview of various AI tools and technologies that can be used in requirements engineering
3. AI use cases in requirements engineering
- Use of AI in the determination and analysis of requirements
- Automated documentation and management of requirements
- AI-supported quality assurance and validation of requirements
- More efficient management and prioritization of requirements with AI tools
- Improving communication and collaboration in requirements engineering through AI
4. limits, challenges and ethical aspects of AI in requirements engineering
- Dealing with possible risks and limitations of AI in requirements engineering
- Data protection and data security when using AI
- Ethical considerations and responsibility in dealing with AI in requirements engineering
5. outlook on the future of AI in requirements engineering
- Trends and developments in AI in requirements engineering
- Potentials and opportunities for future applications of AI in requirements engineering
Requirements:
For successful participation in the training, basic knowledge of requirements engineering is helpful in order to understand the use of AI methods in the right context. In addition, basic knowledge of information technology and data analysis is an advantage.
An essential prerequisite is the openness and willingness to engage with new technologies and concepts and to integrate innovative approaches into everyday working life.
- Understanding AI: Basic knowledge about AI, its history and possible applications in requirements engineering
- Automating requirements analyses: Using AI to automate the analysis and prioritization of requirements
- Improving quality assurance: using AI to improve the quality and consistency of requirements
- Efficient documentation: Application of AI tools for automated documentation and management of requirements
- AI-supported communication: Improving communication and collaboration in requirements management through the use of AI
This course consists of training training and is led by a trainer who supervises the participants live. Theory and practice are taught with live demonstrations and practical exercises. The video conferencing software Zoom is used.
This training is aimed at:
- Requirement Engineers: People who capture, analyze and document requirements will benefit from this training as it shows them how they can use AI to improve their work.
- Business analysts and business engineers: This group can use the training to understand how AI tools can support their analysis and requirements.
- Product engineers: People involved in the development of products learn how AI can optimize their requirements and development processes.
- Project staff: People who work in project management and have to set, define or interpret requirements can benefit from the new possibilities offered by AI.
- System analysts and test managers: Anyone specializing in testing will learn how to get efficient support when designing test cases and analyzing the test coverage of AI tools.
- developers developers and project managers: Strengthening skills in requirements management and project planning through the targeted use of AI tools.
- Quality managers and consultants consultants: Expanding understanding of the importance of requirements in quality assurance and using AI tools to optimize these processes.
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