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Academic Transformation · AI-Native Degree Pathway

4-year AI-Native Engineering pathway for partner universities

Student-first pathway under Academic Transformation: eight semesters, production builds, research outcomes, internships, and evidence-driven career readiness.

Back to Academic Transformation hubStart with Campus-to-CareerDiscuss degree partnership

You are here in the ATRISI system

Option A lock: Academic Transformation is the umbrella, Amplify is the student capability engine, and Resonance is the faculty pathway.

Programs

Capability entry

Ecosystem

System model

Platforms

Operating engines

Research & Evidence

Knowledge loop

Collaborate

Deployment path

Year Architecture

Eight semesters, one progression model

Every year follows the same transformation loop: learn, build, deploy, research, internship, industry experience, and placement readiness.

Year 1

AI Foundations

Computational thinking, programming fundamentals, data basics, and career discovery.

  • Semester 1: AI and technology foundations, Python, Git/Linux, communication, problem solving
  • Semester 2: data structures, SQL, statistics/probability, APIs, automation, analytics projects

Year 2

Core AI Engineering

Machine learning and deep learning fundamentals with startup-linked internships.

  • Semester 3: regression, classification, clustering, feature engineering, model pipelines
  • Semester 4: CNN/RNN/Transformers, PyTorch/TensorFlow, computer vision build projects

Year 3

Advanced AI Systems

NLP and GenAI production systems with enterprise problem contexts.

  • Semester 5: NLP systems, vector databases, embeddings, search, document intelligence
  • Semester 6: LLMs, RAG, agents, guardrails, evaluation, enterprise copilots

Year 4

Research and Career Launch

MLOps and cloud systems, capstone specialization, residency, and placement acceleration.

  • Semester 7: MLOps, cloud AI, distributed systems, security, responsible AI
  • Semester 8: role-based capstone with product, research, case study, and startup proposal

8-Pillar Learning Model

Capability stack for student outcomes

AI Foundations
Industry Skill Development
Project-Based Learning
Research
Industry Experience
Internships
Professional Development
Career Acceleration

Internship progression

Year 1

Foundation Internship

Duration: 8 weeks

Year 2

Startup AI Internship

Duration: 12 weeks

Year 3

Enterprise AI Internship

Duration: 16 weeks

Year 4

Corporate or Research Residency

Duration: 24 weeks

Specialization tracks (Year 3 onward)

Data Science
Machine Learning Engineering
Generative AI
Natural Language Processing
AI Research
AI Product Engineering
Computer Vision
AI + Robotics

Evidence and outcomes guardrails

Public outcomes must remain evidence-governed. Claims on internships, placements, research, and deployed products should be published only when observed and auditable under the Evidence Standard.

Build from entry wedge to full degree pathway

Institutions can begin with Campus-to-Career, then expand into minors, honors, and full degree realizations as partnership depth and evidence maturity increase.

Campus-to-CareerDegree partnership