After completing the course with a passing result, the student shall be able to:

Knowledge

• understand and explain the professional editing process in DaVinci Resolve, from import and structuring of material to final delivery according to industry standards
  
  
• explain editing principles and methods for colour correction, audio processing and visual enhancement in professional production environments
  
  
• describe how AI functions are integrated in established editing tools and analyse how these influence workflows, quality and efficiency in video and film production
  
  
• explain generative AI tools for video, audio and visual content, including their applications and limitations in professional contexts
  
  
• explain how automation and optimisation of work processes in DaVinci Resolve affect the structure and resource use of production processes
  
  
• analyse and explain ethical and legal aspects related to AI-assisted and AI-generated production, including copyright, integrity and professional responsibility
  
  

Skills

• improve efficiency in workflows in DaVinci Resolve and similar professional tools
  
  
• apply AI-based tools for editing, basic colour correction, visual enhancement and analysis of image and audio in professional contexts
  
  
• use generative AI tools to create, process and enhance video, audio and visual content
  
  
• analyse existing workflows and identify opportunities for automation and efficiency improvements using AI
  
  
• apply ethical and legal principles when working with AI-assisted and AI-generated content
  
  

Competence

• independently plan, carry out and evaluate AI-supported workflows in video and film production
  
  
• assess and critically evaluate how the choice of AI tools and methods affects quality, efficiency and professional responsibility
  
  
• take responsibility for ethical and legal considerations when using AI in production
  
  

work professionally and reflectively in teams in changing production environments where AI is an integrated part of the workflow

Teaching is conducted through a combination of theoretical instruction, supervised practical work, individual assignments and structured feedback.

The course includes, among other things:

• theoretical instruction
  
  
• supervised practical exercises
  
  
• individual assignments
  
  
• work with industry-related cases
  
  
• analysis of existing workflows
  
  

structured feedback

Assessment is carried out through supervised practical elements and individual assignments, evaluated according to professional quality criteria and professional responsibility.

The assessment concerns the student’s ability to:

• analyse existing workflows and identify areas for improvement
  
  
• apply AI-based tools in relation to quality, efficiency and professional requirements
  
  
• justify methodological and technical choices
  
  
• assess the consequences of AI use in relation to quality, ethics and legal frameworks
  
  
• work independently with practical tasks in professional production contexts
  
  

Assessment requires analytical ability, independence, reflection and professional responsibility at a post-secondary level.