Training program

Master of AI-Augmented Coding

A practical training program for professionals who want to design, build and safely manage AI workflows around real work.

Program information Admissions

Program at a glance

Competence level

B1.1

Package scope

14 / 22 / 29 teaching hours

Formats

In person, online or through self-study

Program information

How to read the names. Master of AI-Augmented Coding is the name of the entire training program. The program consists of four cumulative levels and is sold in three scope packages, which differ by the highest level a participant reaches: Master of AI-Augmented Coding (levels 1–2, 14 teaching hours), Master of AI-Augmented Orchestration (levels 1–3, 22 teaching hours), and Master of AI-Augmented Company (levels 1–4, 29 teaching hours). A package carries the name of the highest level it includes, and the levels themselves carry the same names. This is therefore one training program in three scopes, not three separate programs; the certificate of completion always carries the program name and states the completed package scope in teaching hours.

Entry level. Augmented Foundations (level 1 on its own) is sold on the augmented.club learning platform outside this training program. It does not end with the final assessment or the certificate of completion described on this page—the participant receives a learning-platform certificate for completing the level. The registered program consists of the three packages listed below.

Program name	Master of AI-Augmented Coding
Target group	Working adult professionals—developers and technical teams, as well as non-technical professionals who want to bring AI into their own work.
Entry requirements	Basic digital literacy at level A2.2 of the Reference Framework for Digital Skills Development; a laptop with internet access; at least one year of programming experience for the engineering track. See full details on Admissions and Participation Terms.
Learning objectives—outcome competences	A graduate can: design and set up their own AI workflows around a real project; create and use reusable components (commands, rules, tools); build and debug a multi-level orchestrator; verify what an AI system actually did; bound its permissions and handle failure states safely.
Content and structure	Cumulative packages across four levels; in person, one level corresponds to one training day, while self-study participants cover the same level asynchronously. Level 1—Augmented Foundations — the user layer: commands, memory, MCP servers, reusable skills, prompting and git workflows. Level 2—Augmented Coding — the system layer and the first orchestrator. Level 3—Augmented Orchestration — developing multi-level orchestrators with self-repair loops. Level 4—Augmented Company — advanced techniques and team infrastructure: patterns beyond the orchestrator (convergent loop, pipeline, generator–critic, swarm, workflows), distribution of a custom setup through plugins and a private marketplace, governance and enforcement in an AI-augmented team, and abstraction over data and code through a bounded team MCP server.
Scope	Scope is determined by the package, not the format—the same material delivered in person or through self-study has the same number of teaching hours. Master of AI-Augmented Coding — levels 1–2—14 teaching hours (2 days in person, 3 weeks through self-study). Master of AI-Augmented Orchestration — levels 1–3—22 teaching hours (3 days in person, 5 weeks through self-study). Master of AI-Augmented Company — levels 1–4—29 teaching hours (4 days in person, 7 weeks through self-study). One teaching hour is 45 minutes; an in-person training day contains 330 minutes of teaching time.
Formats and methods	Formats: in person at the client’s premises, online, and self-study (asynchronous)—the same registered material delivered through recorded lessons with one 60–90 minute live Q&A session each week. Methods: practical, task-based learning—theory, a live demonstration, and an independent hands-on exercise after each unit. There are at most 10 participants per instructor; larger groups are taught by two or three instructors together.
Assessment of outcomes	Ongoing tests in the individual modules of the learning platform, a final practical assignment, and a short final test. Pass threshold: at least 80% in the tests and a submitted final assignment.
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: Problem-solving strategies—in full — formulating and testing hypotheses; solving problems; innovating procedures; testing options and revising procedures; creating strategies; solving complex problems. Digital content creation — specifying achievable goals; identifying and verifying alternatives; creating strategies and procedures; creating content; planning and flexibility. Cybersecurity — recognising risks; preventing risks; selecting a solution with regard to risk and resilience. Data processing and working with information — assessing and selecting alternatives; identifying analogies and connections; analysis and critical thinking. Communication and collaboration — writing; dialogue; decision-making and justification; evaluating one’s own impact.