Training program

Augmented metodológia v praxi

A standalone 10-week training program in which participants safely introduce AI workflows into their own work agenda and build a sustainable weekly routine.

Program at a glance

Competence level

B1.1

Duration and scope

10 weeks · 26 teaching hours

Format

Facilitated blended cohort

Program information

Augmented metodológia v praxi is a standalone training program with its own objective, outcome competences and assessment; it is not a workshop variant.

Program name

Augmented metodológia v praxi

Target group

Working adult professionals who already know or are beginning to use AI tools and want to introduce them systematically into their weekly work routine.

Entry requirements

Basic digital literacy at level A2.2 of the Reference Framework for Digital Skills Development; a laptop with internet access; and a personal work agenda in which the participant will introduce the workflows. Programming experience is not required. See full details on Admissions and Participation Terms.

Learning objectives—outcome competences

A participant can:

  • independently identify tasks in their own work that are suitable for AI support;
  • introduce a concrete workflow for those tasks and evaluate its benefit;
  • maintain the introduced workflow in a weekly routine after the program ends;
  • respect data protection and the boundaries of safe AI-tool use in their own work agenda.
Content and structure

The program does not have one syllabus shared by all participants. Each participant works with their own work agenda and agrees an individual plan of assignments relevant to their work with the instructor at the outset. The program is structured in phases:

  • Shared introduction—the first 2–3 weeks — safe use of AI tools, protection of company and personal data, boundaries of use for the participant’s own agenda, and agreement of the individual assignment plan.
  • Ongoing application phase — selecting and introducing workflows based on the participant’s own agenda, submitting solutions in the platform, and instructor review and approval.
  • Final evaluation — evaluation of approved solutions against the 80% pass threshold for the individually agreed plan.

A facilitated two-hour session takes place each week; between sessions, the participant applies workflows in their own work and submits assignments through the platform. The objective is to build a habit so that daily AI use remains part of ordinary work after the program ends.

Scope

10 weeks × 2 clock hours of contact teaching = 20 clock hours of contact teaching, corresponding to 26 teaching hours. One teaching hour is 45 minutes. Applying workflows in the participant’s own work between sessions is excluded from this scope.

Formats and methods

Blended format: weekly facilitated meetings with an instructor, application in the participant’s own work between meetings, and materials, assignments and feedback on the augmented.club learning platform.

Assessment of outcomes

During the program, the participant submits solutions to assignments (challenges) through the platform, each capturing a concrete workflow introduced or automated in their own work. The instructor reviews and approves every solution; approved solutions are the participant’s written output. At the outset, the participant and instructor agree an individual plan of at least five assignments; approximately eight assignments are recommended over ten weeks. The pass threshold is at least 80% approved solutions from this agreed plan.

Certificate of completion

A certificate of completion stating the program name, scope in teaching hours, content, and the attained level of the reference framework.

Digital competence level and areas

Level B1.1 of the Reference Framework for Digital Skills Development. Competence areas under the Reference Framework, as selected in the self-assessment tool:

  • Problem-solving strategies—in full — formulating and testing hypotheses; solving problems; innovating procedures; testing options and revising procedures; creating strategies; solving complex problems.
  • Data processing and working with information—partially — assessing and selecting alternatives; identifying analogies and connections; analysis and critical thinking.
  • Communication and collaboration—partially — writing; dialogue; decision-making and justification; evaluating one’s own impact.
  • Digital content creation—partially — specifying achievable goals; identifying and verifying alternatives; creating strategies and procedures; creating content; planning and flexibility.
  • Cybersecurity—partially — recognising risks; preventing risks; selecting a solution with regard to risk and resilience.