Centre for Intelligent Robotics (CIR) | IIIT Allahabad
AI-TRAC 2026
AI Trainer Certification & Internship Program
for Robotics and Machine Intelligence Mentors
4-Week Summer Internship & Capacity Building Program · May 25 – June 19, 2026
“Training Future AI & Robotics Mentors for India’s Schools”
📋 Program at a Glance
1. Program Overview
The Centre for Intelligent Robotics (CIR), Indian Institute of Information Technology Allahabad (IIIT-A), in strategic collaboration with STEMLearn.AI (Teevra EduTech Pvt. Ltd.), proposes AI-TRAC 2026 — a four-week residential Capacity Building and Mentorship Program in AI, Robotics, Machine Learning and Smart Systems.
AI-TRAC 2026 is designed to train the next generation of AI and Robotics mentors who can deliver structured, outcome-oriented AI and robotics education to students in Grades 9–12 across Indian schools.
The program addresses the gap between subject-matter expertise and effective teaching practice by combining rigorous technical training in AI and robotics with structured pedagogy sessions, guided micro-teaching exercises, and capstone project development.
2. Rationale & Strategic Context
India’s school education system faces a critical shortage of trained AI and robotics educators. While national policy frameworks, including NEP 2020 and NSQF, emphasize AI literacy for secondary school students, the availability of qualified facilitators remains limited. This creates a significant gap between policy intent and on-ground implementation across schools.
The Centre for Intelligent Robotics (CIR) at IIIT Allahabad brings strong academic and research expertise in AI-enabled robotics, embedded systems, and intelligent automation. AI-TRAC 2026 builds on this foundation and integrates it with STEMLearn.AI’s curriculum design, learning management systems, and school outreach capabilities to create a high-quality, scalable, and replicable mentor-training pipeline.
2.1 Key Drivers
- India needs 1 lakh+ trained AI facilitators for school-level delivery by 2027 (NASSCOM estimate).
- 80% of existing school teachers are untrained in AI/ML pedagogy (NAS 2021).
- UG/PG students and working professionals represent an underutilised talent pool for school-level AI education.
- The Centre for Intelligent Robotics (CIR), IIIT Allahabad, provides world-class laboratory infrastructure and research oversight to validate all technical content.
2.2 Alignment with National Priorities
| National Policy / Initiative | Alignment with This Program |
|---|---|
| NEP 2020 | Competency-based, experiential AI learning aligned to NCERT principles |
| NSQF Level 3 & 4 | Intern curriculum mirrors NSQF modules for Grades 9–12 delivery |
| IndiaAI Mission | Builds grassroots AI literacy infrastructure via trained school mentors |
| CM’s AI-for-All (UP) | Creates AI-first workforce pipeline starting from Grades 9–12 |
3. Program Objectives
AI-TRAC 2026 is designed to achieve the following objectives:
- Equip interns with comprehensive, hands-on knowledge of AI, Data Science, Machine Learning, and Smart Systems aligned with NSQF Levels 3 & 4.
- Develop structured pedagogy and teaching skills so interns can effectively deliver AI courses to Grades 9–12 students in school settings.
- Build practical proficiency in Python programming, data analytics, ML model implementation, and Generative AI tools.
- Train interns to design and execute capstone AI projects, and to guide school students through similar project-based learning.
- Create a certified pool of 50+ AI & Robotics mentors available for deployment through STEMLearn.AI’s network.
- Promote interdisciplinary collaboration between academia (IIITA) and industry (STEMLearn.AI) in building scalable AI education infrastructure.
4. Eligibility Criteria
| Participant Category | Minimum Qualification | Preferred Background |
|---|---|---|
| UG Students | 2nd year onwards — B.Tech / B.Sc (CS, IT, ECE, EE, or allied) | Programming or Math coursework |
| PG Students | M.Tech / M.Sc (CS, AI, Data Science, Electronics, or allied) | Prior ML / Python exposure |
| Teachers / Professionals | Graduate degree with active teaching or industry role | Interest in school-level AI education |
5. Curriculum & Module Structure
The program spans 80 instructional hours over four weeks, structured into eight modules combining theory, lab practicals, and guided teaching practice. The curriculum is directly mapped to the NSQF Level 3 & 4 AI course content, ensuring interns master both the subject matter and its pedagogical delivery.
5.1 Hour Distribution
| Component | Hours |
|---|---|
| Theory | 32 Hours |
| Practical / Lab | 28 Hours |
| Project + Teaching Practice | 20 Hours |
| Total | 80 Hours |
5.2 Module-wise Curriculum
| Week | Module | Title | Total Hrs | Theory | Practical | Project |
|---|---|---|---|---|---|---|
| Week 1 | Module 1 | AI Foundations & Smart Systems | 8 | 5 | 3 | – |
| Week 1 | Module 2 | Problem Solving & System Design | 8 | 4 | 4 | – |
| Week 1 | Module 3 | Data Literacy, Statistics & Analytics | 12 | 6 | 6 | – |
| Week 2 | Module 4 | Python Programming for AI | 14 | 6 | 8 | – |
| Week 2–3 | Module 5 | Machine Learning: Fundamentals & Applications | 14 | 7 | 7 | – |
| Week 3 | Module 6 | Generative AI & Responsible AI | 8 | 4 | 4 | – |
| Week 3 | Module 7 | AI Applications & Smart Systems | 6 | 4 | 2 | – |
| Week 4 | Module 8 | Capstone Project + Mentor Training | 10 | – | – | 10 |
| TOTAL | 80 | 36 | 34 | 10 | ||
5.3 Module Details
Module 1 — AI Foundations & Smart Systems (8 hrs: T:5 | P:3)
- What is AI? AI vs Human Intelligence; Types of AI (conceptual)
- AI in real-world domains: healthcare, agriculture, robotics, automation
- Smart systems basics — Sense → Think → Act framework
- Practical: AI use-case mapping, case study discussions
Module 2 — Problem Solving & System Design (8 hrs: T:4 | P:4)
- Problem decomposition; Input → Process → Output model
- Designing AI workflows; Introduction to flowcharts
- Practical: AI system architecture design exercises
Module 3 — Data Literacy, Statistics & Analytics (12 hrs: T:6 | P:6)
- Types of data; data collection, cleaning, and preprocessing
- Data visualization; Mean, Median, Mode; Introduction to EDA
- Data bias & fairness; structured vs. unstructured data
- Practical: Dataset handling and visualization using Python
Module 4 — Python Programming for AI (14 hrs: T:6 | P:8)
- Basics: variables, loops, conditions, functions
- Working with datasets (CSV); Introduction to NumPy & Pandas
- Practical: Program writing, data manipulation, and visualization
Module 5 — Machine Learning: Fundamentals & Applications (14 hrs: T:7 | P:7)
- Supervised vs. Unsupervised learning; Classification & Regression
- Model accuracy, confusion matrix; Decision Trees, KNN, Clustering
- Neural Networks (conceptual); Train-Test split; model comparison
- Practical: Simple ML model implementation and evaluation
Module 6 — Generative AI & Responsible AI (8 hrs: T:4 | P:4)
- Generative AI and Large Language Models (LLMs)
- Prompt engineering; Ethics, bias, and privacy in AI
- Responsible AI practices; Safe deployment guidelines
- Practical: Prompt design, bias detection exercises
Module 7 — AI Applications & Smart Systems (6 hrs: T:4 | P:2)
- Computer Vision basics; NLP basics; Chatbots
- AI in smart devices and intelligent automation
- Practical: Demo-based exploration of CV and NLP tools
Module 8 — Capstone Project + Mentor Training (20 hrs: Practical + Teaching Practice)
- Capstone Project Themes: Smart City/Environment System; Healthcare/Accessibility AI; Chatbot/Responsible AI Tool
- Pedagogy sessions: How to teach AI to school students (Grades 9–12)
- Lesson plan creation aligned to NSQF Level 3 & 4 modules
- Micro-teaching sessions with peer feedback
- Deliverables: AI capstone project + teaching module + demo session
6. Week-wise Schedule
| Week | Modules Covered | Key Activities |
|---|---|---|
| Week 1 May 25–31 | Modules 1, 2, 3 — Foundations + Data | Orientation, AI use-case mapping, data labs |
| Week 2 Jun 1–7 | Module 4 (Python) + Module 5 start (ML basics) | Python lab sessions, dataset handling |
| Week 3 Jun 8–14 | Modules 5, 6, 7 — ML + GenAI + Applications | ML model building, prompt engineering, CV/NLP demos |
| Week 4 Jun 15–19 | Module 8 — Capstone Project + Mentor Training | Project presentations, micro-teaching, certification |
7. Pedagogy & Delivery Methodology
The program employs a blended, active-learning pedagogy that mirrors the hybrid delivery model used in school deployments. This ensures interns not only learn the content but also experience the instructional format they will later replicate as mentors.
| Methodology | Description |
|---|---|
| Lecture + Discussion | Concept-first delivery followed by real-world application discussion for each topic |
| Hands-on Lab Sessions | Python coding, data analysis, and ML model implementation in IIIT-A computer labs |
| Case Studies | Analysis of AI deployments in healthcare, agriculture, governance, and smart cities |
| Project-Based Learning | Capstone project developed across Week 4 with structured checkpoints and mentoring |
| Micro-Teaching | Interns design and deliver 15-minute teaching demonstrations to peers, simulating school delivery |
| Peer Learning | Group activities, peer code reviews, and collaborative problem-solving exercises |
| Expert Guest Sessions | Guest lectures by IIIT-A faculty and STEMLearn.AI industry experts on advanced topics |
8. Roles & Responsibilities
8.1 IIIT Allahabad — Centre for Intelligent Robotics (CIR)
- Overall academic oversight, quality assurance, and institutional hosting of the program
- Provision of campus infrastructure: computer labs, lecture halls, and hostel accommodation
- Faculty-led instruction for Modules 1, 5, 7 and all robotics/smart systems sessions
- Academic supervision of capstone projects by Prof. Sonali Agarwal and Dr. Surya Prakash
- Conduct of final assessments and issuance of joint certification
- Integration of interns into ongoing CIR research activities in AI-enabled robotics and embedded systems
8.2 STEMLearn.AI
- Curriculum design and provision of all learning materials — Techno-Books, LMS access, and digital resources
- Delivery of Modules 2, 3, 4, 6, and pedagogy/mentor training sessions in Module 8
- Provision of LMS (Learning Management System) with video modules, coding notebooks, and project templates
- Design and conduct of structured assessments and evaluation rubrics
- Post-internship deployment support: connecting certified interns with Project Praveen schools as mentors
- Management of fee collection, logistics coordination, and participant communication
8.3 Interns
- Attend all 80 hours of scheduled sessions (minimum 85% attendance mandatory for certification)
- Complete all module-level assignments, lab exercises, and quizzes on the LMS
- Develop and present a capstone AI project by end of Week 4
- Design a lesson plan and deliver a micro-teaching session as part of Module 8
- Adhere to IIIT-A campus rules, hostel regulations, and program code of conduct
9. Assessment & Certification
9.1 Assessment Structure
| Component | Description | Weightage |
|---|---|---|
| Module Quizzes | Online quizzes at the end of each module via LMS | 20% |
| Lab & Practical Exercises | Python coding tasks, dataset exercises, ML implementation | 30% |
| Capstone Project | AI project: problem definition, implementation, evaluation, presentation | 30% |
| Micro-Teaching Session | Lesson plan quality and teaching demonstration to peer group | 20% |
| Total | 100% | |
9.2 Certification Criteria
- Minimum 85% attendance across all sessions
- Minimum 60% aggregate score across all assessment components
- Submission of capstone project and teaching module within program timeline
Interns meeting all criteria will receive a Joint Certificate of Completion issued by IIIT Allahabad (Centre for Intelligent Robotics) and STEMLearn.AI, co-branded with institutional logos and signatures of faculty leads.
10. Fee Structure
| Fee Component | Amount | Notes |
|---|---|---|
| Program Fee (Tuition) | ₹6,000 | Per intern |
| GST @ 18% | ₹1,080 | As applicable |
| Total Program Fee (incl. GST) | ₹7,080 | |
| Hostel Accommodation | As per IIIT-A rates | Charged separately |
| Meals / Food | As per IIIT-A rates | Charged separately |
✅ What the Program Fee Includes
- Full 80-hour structured instruction by IIIT-A faculty and STEMLearn.AI experts
- Lab access at IIIT-A campus for all practical sessions
- Joint Certification (IIIT Allahabad + STEMLearn.AI)
- Study materials, datasets, and project templates
📌 Payment Terms
- Full fee payment required at time of registration confirmation
- Fee is non-refundable after the program commencement date (May 25, 2026)
- Hostel and food charges to be paid directly to IIIT Allahabad as per institute norms
- Group Discount: 5 or more from the same institution → 10% concession on program fee
Bank Payment Details
Bank Name: Indian Overseas Bank, Branch – Civil Lines Allahabad (Uttar Pradesh) 211001
Account Name: IIIT-A General A/C
Account Number: 035001000060976
IFSC Code: IOBA0000350
11. Expected Outcomes & Impact
🎓 For Interns
- Comprehensive, hands-on proficiency in AI, Python, ML, and Generative AI tools
- NSQF-aligned pedagogical skills to teach AI confidently to Grades 9–12 students
- A completed, presentable AI capstone project for portfolio/academic use
- Joint IIIT-A + STEMLearn.AI certificate, nationally recognised and industry-valued
- Priority pathway to mentor deployment through Project Praveen (paid opportunities)
- Access to CIR’s research ecosystem and STEMLearn.AI’s school network for career growth
🏠 For the School AI Ecosystem
- 50+ trained, certified AI mentors ready for school deployment in Year 1
- Direct impact on 2,500+ school students in Grades 9–12 through mentor-led sessions
- Scalable mentor pipeline: program to be repeated annually with increasing intake
- Strengthened Project Praveen delivery capacity across 500+ UP government schools
🏫 For IIIT Allahabad — CIR
- Establishment of a nationally visible mentor-training program anchored at IIIT-A
- Integration of summer interns into CIR’s AI-enabled robotics research activities
- Enhanced industry partnership with STEMLearn.AI for content, placement, and outreach
- Contribution to NEP 2020 implementation and national AI literacy objectives
13. Faculty & Mentors
13.1 Academic Faculty — IIIT Allahabad
The program is further strengthened by faculty members from IIIT Allahabad contributing domain expertise across AI, machine learning, and intelligent systems. Internship coordinators manage program delivery, scheduling, and participant engagement. The CIR research staff facilitate laboratory sessions, hands-on robotics demonstrations, and technical project support.
13.2 Industry Faculty — STEMLearn.AI
| Profile | Organisation | Role in Program |
|---|---|---|
| AI Curriculum Experts | STEMLearn.AI | Delivery of Python, Data Science, ML, and GenAI modules |
| Pedagogy & Mentor Trainers | STEMLearn.AI | Conduct of teaching practice, lesson plan design, micro-teaching sessions |
| LMS & Assessment Team | STEMLearn.AI | LMS setup, quiz design, project evaluation, progress tracking |
14. Application & Registration Process
| Step | Action | Details | Timeline |
|---|---|---|---|
| 1 | Application | Submit online application form with academic details and a brief statement of purpose | Opens: May 28, 2026 |
| 2 | Shortlisting | Applications reviewed by IIIT-A CIR and STEMLearn.AI; merit-based shortlisting | By: May 29, 2026 |
| 3 | Offer Letter | Offer letters issued to selected candidates with fee payment instructions | By: May 29, 2026 |
| 4 | Fee Payment | Program fee (₹7,080 incl. GST) and hostel booking to be completed | By: May 30, 2026 |
| 5 | Confirmation | Confirmation email + pre-reading materials + hostel check-in details shared | By: May 31, 2026 |
| 6 | Program Begins | Orientation + Day 1 at IIIT Allahabad campus | June 01, 2026 |
Application link and contact details are published on the IIIT Allahabad CIR website and STEMLearn.AI portal. For queries, contact: cir@iiita.ac.in | Stemlearn@speedlabs.in
15. Concluding Remarks
AI-TRAC 2026 represents a timely and impactful collaboration between two of India’s leading AI education stakeholders — the Centre for Intelligent Robotics at IIIT Allahabad and STEMLearn.AI. At a moment when India urgently needs trained AI educators for its school system, this program offers a structured, rigorous, and nationally scalable solution.
By training 50+ interns annually as certified AI and Robotics mentors — grounded in both academic depth and practical pedagogy — this program directly strengthens the knowledge delivery pipeline and contributes to India’s broader AI literacy mission.
We invite eligible students, educators, and professionals to be part of this transformative initiative and join the ranks of India’s next generation of AI educators.
Centre for Intelligent Robotics (CIR)
IIIT Allahabad
Coordinator, AI-TRAC 2026
Centre for Intelligent Robotics (CIR)
IIIT Allahabad
Co-Coordinator, AI-TRAC 2026
📍 Contact Us
Centre for Intelligent Robotics (CIR)
Computer Center-1, IIIT-Allahabad, Jhalwa Campus
Allahabad – 211 015, India
📞 +91 7408418438
