Offered by: Loptr Lab Program type: Applied technical training in game design, software engineering, and digital art Format: Self-paced, project-based, with milestone checkpoints Sponsoring project: Veiled Dominion Engine — an open-source 4-player asymmetric strategy game Hands-on exercise: Veiled Dominion Training — the graded TypeScript coding exercise this curriculum’s Track A milestones are based on —
This curriculum references two related but different repositories:
Participants following Track A may use the training repo for structured programming practice before contributing to the full engine project.
Canonical location note: For now, this curriculum page remains in the engine repository as the public program overview, while the hands-on exercise materials live in the separate training repository.
This curriculum trains participants in professional game development skills — programming, systems design, and technical art — through structured, hands-on contribution to a real, in-development project.
The program was developed by Loptr Lab, a creative studio building game design and IP development work, with a founding focus on accessibility within creative and maker industries. This curriculum is intended to support both independent learners and participants whose training activity must be documented for vocational rehabilitation, grant, or workforce-development purposes.
This program is intended for participants who are:
The curriculum consists of a shared foundational phase, followed by three specialized tracks. Participants may complete one track or progress through multiple, depending on their training plan and prior experience.
| Component | Estimated Duration | Format |
|---|---|---|
| Phase 0: Foundations (all tracks) | 1 week / ~10–15 hours | Reading, rules analysis, tabletop prototyping |
| Track A: Prototype Engineer | 4 weeks / ~80–100 hours | Applied C# / game engine programming |
| Track B: Systems Designer | 3 weeks / ~40–60 hours | Game economy modeling, playtesting, balance analysis |
| Track C: Technical Artist | 2–3 weeks / ~40–60 hours | Shader programming, real-time rendering |
Hours are estimates for a participant with no prior programming background progressing at a moderate, sustainable pace; actual duration will vary by individual and should be adjusted in coordination with a counselor, case manager, or training supervisor where applicable.
Objective: Participants understand the underlying rule system and codebase architecture well enough to explain it independently, before writing production code.
Activities:
board/, input/, pieces/, systems/) and map each module to its corresponding design rule.Completion checkpoint: Participant can, without reference materials, verbally or in writing explain the core game rules and correctly diagram the turn/phase loop architecture.
Focus: applied programming, spatial/mathematical logic, software architecture
Completion checkpoint / competency demonstrated: Participant independently implements and integrates a functioning, rules-accurate reduced-scope version of the core game loop.
Focus: game economy modeling, quantitative balance, structured playtesting
Completion checkpoint / competency demonstrated: Participant produces a documented balance analysis and a structured playtest report with data-supported design recommendations.
Focus: real-time shader programming, visual systems design
Completion checkpoint / competency demonstrated: Participant delivers at least two functioning custom shaders integrated into the working project, meeting a written visual specification.
For participants using this curriculum to satisfy training-hour or activity documentation requirements:
This training program is designed and administered by Loptr Lab with attention to accessible training practices, including:
Participants with specific accommodation needs are encouraged to contact Loptr Lab directly to discuss adjustments to pacing, format, or checkpoint structure.
Program sponsor: Loptr Lab Engine project: github.com/Loptr-Lab/veiled-dominion-engine Candidate exercise repo: github.com/Loptr-Lab/training