To collect information about existing solutions, that can be used to track progress in study courses.
To create a qualitive analysis more presisely and check grammar for report.
To transcribe the audio recordings, which saved time and improved accuracy compared to manual transcription.
To structure and organize the interview questions. It helped us focus on analyzing the content rather than on manual tasks.
Logo was generated with the use of AI.
Sprint 1:
Bootstraping of Hello world projects, dockerizatio (Dockerfiles generation), quick minor errors fixing.
Collecting information about quality requirements suitable for our project.
Checking plan for grammar mistakes.
To structure and organize the interview questions. It helped us focus on analyzing the content rather than on manual tasks. To transcribe the audio recordings, which saved time and improved accuracy compared to manual transcription.
To structure and organize the interview questions. It helped us focus on analyzing the content rather than on manual tasks.
To transcribe the audio recordings, which saved time and improved accuracy compared to manual transcription.
Sprint 2:
Drafting of frontend pages with components and mock data.
To structure and organize the interview questions. It helped us focus on analyzing the content rather than on manual tasks.
To transcribe the audio recordings, which saved time and improved accuracy compared to manual transcription.
Sprint 3:
To structure and organize the interview questions. It helped us focus on analyzing the content rather than on manual tasks.
To transcribe the audio recordings, which saved time and improved accuracy compared to manual transcription.
Sprint 4:
To structure acceptance criteria for Tasks
To orginize and grammar check the text in observability and analytics file