Model A
Institution-owned lab
We set up your lab, supply kits & books, train your teachers — you operate day-to-day.
- ● AI lab seating
- ● Dataset governance policy
- ● Faculty certification
Model B — Popular
Fully managed by RSIL
Labs, books, kits and teachers off-the-shelf. Your institution focuses on core academics — we run STEM end-to-end.
- ● RSIL AI lab operators
- ● Content updates each term
- ● Student mentoring hours
School pathway
K–12 · Easy to learn · Strong pedagogy
Classes 6–8 AI awareness · 9–12 applied AI projects
Academic pedagogy
Inquiry + ethics-first: students ask good questions of data before they ‘train a model’. Aligns with NEP computational thinking.
Ease of learning: No heavy maths wall—visual datasets, drag-train tools, then optional Python notebooks for seniors.
Syllabus snapshot
- → What AI can/cannot do; bias stories
- → Classification vs prediction with classroom datasets
- → Vision & language demos (safe, filtered)
- → Capstone: AI for school problem (attendance insights, library, etc.)
Learning outcomes
- ● Describe AI systems in plain language
- ● Train a simple model and read its mistakes
- ● Discuss fairness, privacy and human oversight
Course books
- AI Literacy Workbook
- Data Detectives Journal
- Ethics Cards for Classrooms
Student kits by level
- ● Vision Cam Classroom Kit
- ● Dataset Explorer Pack
Assessment: Model cards (student version), posters and peer critique.
College · University · Professional
Technical depth with professional pedagogy
From classical ML to deep learning workflows with evaluation science and responsible deployment.
Professional pedagogy
Research-informed teaching: paper clubs, reproducible labs, ablations and industry case studies.
Syllabus / module map
- → Feature engineering, validation, leakage control
- → Supervised/unsupervised/deep learning tracks
- → NLP & CV applied labs
- → MLOps lite: versioning, monitoring, drift
Technical learning outcomes
- ● Build evaluated ML pipelines with clear metrics
- ● Communicate model limitations to stakeholders
- ● Ship a demable service with monitoring hooks
Course books & manuals
- Applied ML Lab Manual
- Responsible AI Playbook
Lab / professional kits
- ● GPU lab seats / cloud credits pack
- ● Edge AI inferencing kit
Assessment: Reproducible repos, reports, oral exams and stakeholder demos.
Aligned to global trends
GenAI literacyAI safety educationTinyMLCompetency-based AI credentials
Introduce AI / Machine Learning at your institution
Choose curriculum and kits, or let RSIL manage delivery for you. Both options include the learning platform, simulators and assessment support.