Architecture, interior design, and course FAQ

Prepare site or existing-condition information, budget range, expected users, timeline, and reference spaces you like or dislike. If information is incomplete, consultation can help structure it.

Architecture usually covers site, massing, structure, envelope, regulations, and spatial relationships. Interior design focuses more on function, finishes, lighting, furniture, and details within a defined space.

Yes. Early consultation is useful for direction, budget feasibility, site constraints, and deciding whether a full design scope is needed.

Cost depends on area, construction scope, custom furniture, material grade, equipment updates, and whether MEP, air-conditioning, lighting, or structural changes are involved.

Small spaces benefit from precise planning because mistakes in circulation, storage, furniture scale, and lighting are amplified.

Yes. Layout consultation is useful when buying a home, renting a shop, planning a studio, or estimating renovation scope.

Yes. Photos show surface conditions, but leaks, drainage, walls, windows, slabs, and utilities usually require on-site review.

Yes, but electrical, waterproofing, air-conditioning, and core storage should be planned early to avoid repeated demolition.

Redecoration is mostly surface renewal. Renovation often addresses layout, utilities, equipment, waterproofing, materials, and long-term use.

Yes. HanSun Architects offers public AI foundation classes, one-to-one training, and corporate programs tailored to architecture, interior design, engineering management, or company workflows. Dates and syllabi are listed on each course page.

Prioritize real work cases, data security, output verification, reusable workflows, and an instructor who understands design, engineering, and project delivery. Prompt or image-generation demonstrations alone rarely cover professional practice.

Yes. Public foundation classes start from everyday work scenarios and do not require programming. One-to-one and corporate programs are scoped after reviewing experience, tools, and goals.

Coverage follows each syllabus and current tool versions. The focus is selecting suitable tools for research, proposals, documents, engineering management, and automation rather than following one product. Check the current course page for details.

Yes. One-to-one training is suited to a specific project or personal workflow, while corporate programs are planned around roles, group size, data security, and expected outcomes. Submit your needs through the course or consultation page.

They are designed for professionals applying AI to architecture, interior proposals, documents, estimating, or project management. Public classes establish shared foundations; one-to-one or corporate formats suit specific projects and company workflows. Current course pages define the actual tools, dates, and syllabus.

It suits architects, designers, engineers, project managers, and teams who need better research, proposals, documents, or estimates. The curriculum is scoped to work context rather than programming experience.

Topics can include interview synthesis, style and material comparison, proposal presentations, drawing documents, estimate drafts, and project tracking. Professionals still verify dimensions, codes, fire safety, materials, and buildability.

The architecture and interior AI curriculum is planned and taught by Shilun Yen, drawing on professional practice across architecture, interiors, and engineering management. The teaching focuses on verifiable, reusable workflows.

It is useful for concept exploration, reference collection, scenario scripts, material vocabulary, proposal structure, draft presentations, and course exercises. Construction drawings, code, and budget still need professional review.

Not directly. AI improves exploration speed, but it cannot fully own site judgment, regulatory responsibility, construction coordination, material feasibility, or client communication.

Yes, but the focus is not chasing tools. Learners should define problems, write effective prompts, evaluate outputs, and turn AI results into discussable design proposals.