Track B · AI for Design

Track B

A 6-course AI specialization for B.Des, M.Des, and B.Arch students at Indian private universities. Generative design, AI-assisted UX/UI, 3D/motion AI, AI product design. NEP-aligned, on-campus.

Talk to our partnerships team Download the Track B curriculum

Track B curriculum snapshot — six courses B1 through B6.

NEP 2020Credit-mapped NAACEvidence-ready AICTEModel-curriculum aligned NBAOBE-mapped

The course list

7 courses in Track B.

Each module is co-evaluated by Kompas resident faculty and your university's academic council. Module content refreshes every six months.

AI Literacy for Designers

Sem 3–43 credits

Skill outcomes

Explain how generative models work without relying on mathematical formalism
Practice prompt fluency as a craft skill across image, text, and multimodal tools
Critique the ethical implications of generative tools in design practice
Reason about intellectual property and provenance in AI-generated work

Generative Design Studio

Sem 4–53 credits

Skill outcomes

Operate Midjourney, Stable Diffusion, ControlNet, and Flux at studio quality
Produce brand-aligned, design-system-constrained generative output
Generate work in a defined house style without losing its signature
Defend studio work in weekly critique against professional standards

Prerequisites: B1

AI-Assisted UX/UI Design

Sem 53 credits

Skill outcomes

Integrate Figma AI, Galileo, and Uizard into a production UX workflow
Drive wireframing and prototyping through prompt-led iteration
Synthesize user research using AI-assisted and conversational research methods
Ship interactive prototypes that pass review by working product designers

Prerequisites: B1

3D, Motion & Video AI

Sem 5–63 credits

Skill outcomes

Build motion and video pipelines with Runway, Pika, and Sora-class tools
Apply AI-assisted CAD and parametric workflows to 3D form-finding
Produce architectural visualization combining parametric tools with Stable Diffusion
Integrate generative AI into motion graphics and video editing pipelines

Prerequisites: B2

AI in Product & Industrial Design

Sem 63 credits

Skill outcomes

Drive generative product form-finding from brief to physical concept
Apply materials AI to inform material selection and exploration
Embed AI into physical prototyping and iteration pipelines
Evaluate the role of AI in design-for-manufacturing decisions

Prerequisites: B2

Designing AI Experiences

Sem 6–73 credits

Skill outcomes

Design chat UX and agent UX patterns from first principles
Build trust patterns and conversational onboarding for AI products
Design error states and recovery flows for non-deterministic systems
Ship portfolio-grade interaction design for AI-first products

Prerequisites: B3

Capstone — Portfolio-Grade Project

Sem 7–84 credits

Skill outcomes

Scope a capstone brief sourced from the partner hiring network
Deliver a portfolio-grade artifact (AI-augmented brand system, AI-native app, generative architectural concept, or generative fashion line)
Defend the project in co-evaluation with a working senior designer
Publish a portfolio piece ready for AI-first studios, agencies, and product companies

Prerequisites: B1 → B2 → B3 → B6

Skill Score on exit

Mastery is measured, not assumed.

Every Track B graduate exits with a verifiable Kompas AI Skill Score, calibrated against an industry-co-signed rubric and applied identically across every campus we operate on.

Foundational
Practitioner
Applied
Advanced
Expert

Track B graduates typically exit between Practitioner and Applied. Industry-sponsored capstone work moves the strongest students into the Advanced band.

Capstones from this track

What a Track B student ships at the end.

Examples below are illustrative until real partner-cohort capstones land. The shape — sponsor, problem, outcome, public artefact — does not change.

See the full capstone library

Track BBrand · GenerativeD2C consumer brand

AI-augmented brand system for an Indian D2C

Problem

A small consumer brand needs a coherent visual identity that scales across hundreds of generated assets without losing the founder's signature tone.

Target outcome

A house-style ControlNet + LoRA stack producing on-brand campaigns at production quality, paired with a short style-discipline guide so non-designers on the team can stay on brand without supervision.

Track BArchitecture · GenerativeIndependent architectural studio

Climate-adapted residential typology with generative tooling

Problem

Mid-tier Indian housing under increasing climate stress needs typologies that perform in heat and humidity. Generative tooling has so far produced visually striking but climatically poor concepts.

Target outcome

A parametric + diffusion concept set tuned against measured climate data for a sample city; portfolio-grade visual narrative defended in studio crit. Includes the climate-aware brief that any future generation must pass.

See 4 more Track B capstones →

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