Artificial Intelligence, with Specialization in Robotics.
Sit at the intersection of the two fastest-growing fields — AI and robotics. Learn computer vision, deep learning and autonomy through live mentorship and an optional hands-on 5-day robotics lab at TIH, IIT Palakkad.
One call, when you book itWe reach out only when you ask.
Your details stay yoursNever shared. Never sold.
Upcoming cohorts
Choose your cohort.
Same curriculum, same mentors, same optional five-day lab at TIH, IIT Palakkad — three regional cohorts so the live sessions land in your evening.
Dec15
India
8:00 PM IST
Next cohort · Live online · optional 5-day lab at TIH, IIT Palakkad
Dec22
UAE
7:30 PM GST
Next cohort · Live online · optional 5-day lab at TIH, IIT Palakkad
Dec22
Singapore
9:00 PM SGT
Next cohort · Live online · optional 5-day lab at TIH, IIT Palakkad
Admissions
Simple, clean, and merit-based.
Science graduates from any domain, selected on merit. Four steps from application to seat — with a full refund window if it turns out not to be for you.
B.TechAny branch
B.ScScience stream
M.TechAny branch
M.ScScience stream
BCAComputer apps
MCAComputer apps
Any domain
Your degree does not have to be in robotics, or even in computer science. Science graduates from any branch are eligible.
Still studying? Still fine.
Currently pursuing or already completed — both count. Final-year students are welcome to apply.
No prior robotics needed
Built for freshers and early-career professionals. Module 01 starts at Python and the maths you actually need.
How it works
Four steps, start to seat.
No chasing, no pressure. You apply, you talk to us once, and then you decide.
01
Pay the application fee and start
Pick your course and the cohort for your region, and pay a small application fee to start your application.
02
Fill in your application
Submit your details: what you’ve studied, what you do today and what you want from the course. A person in admissions reads every answer.
03
Call with the admissions team
A 30-minute call at a time you book — fit, workload, outcomes and financing, and whether this cohort is right for you.
04
Pay and enrol
Confirm your seat — only 30 per batch, so this is where they get allocated — and pay in full or on EMI / instalments for your region. Your refund window starts with the batch.
15-day refund window. If you feel this course is not for you, the full fee is refunded within the first 15 days of the batch commencing.
No spam. Ever. No cold calls, emails or WhatsApp from us. We speak only when you book a call with admissions.
Generic Data Science is being automated and taught everywhere. What stays scarce is depth in a hard vertical — and robotics is the hardest, fastest-growing one of them all.
0101 · Breadth without depth
Generic Data Science no longer differentiates
Model training, dashboards and notebook analytics are now table stakes — increasingly automated and taught in every bootcamp. Competing on general AI skills means competing with everyone.
Robotics and autonomous vehicles need engineers who understand perception, control and real-world physics — not just clean datasets. Models that work on a benchmark still fail on a factory floor.
Depth is scarce — and scarcity is leverage
0303 · Who is hiring
Industries built on this exact overlap
Robotics, autonomous vehicles, drone technology and healthcare imaging all need people fluent in both the AI and the physical system it drives. Neither skill alone gets you in the room.
Four verticals, one skill set
0404 · The growth story
Demand is compounding, supply is not
Robots are moving out of labs into warehouses, roads, farms and hospitals. Every one of those deployments needs someone who can make perception work in the messy real world.
Neither field alone is rare any more. The overlap is — and that is exactly where this program puts you.
“
A model that only ever runs in a notebook is a demo. The moment it has to see a real room, judge a real distance and move a real machine, it becomes engineering — and that is the work the next decade is hiring for.
Why we built this program
The roles
Prepare for specialised roles that give you an edge.
Build depth for the fastest-growing industries and domains — with the AI-plus-physical-systems skill set each of these specialised roles demands.
Computer Vision Engineer
Build the machine's eyes — detection, segmentation, depth and tracking that hold up in changing light and motion.
CNNs & ViTsCalibrationReal-time inference
Robotics Researcher
Push the frontier — motion planning, SLAM and learned control for machines that must act, not just predict.
SLAMROS 2RL for control
AI Engineer
Take models out of notebooks and into machines — pipelines, deployment and monitoring that survive the field.
MLOpsEdge deploySensor pipelines
Deep Learning Engineer
Design and train the models themselves — architecture choices, data strategy and the optimisation that makes them fit on a robot.
PyTorchTraining at scaleQuantisation
Partners & ecosystem
The industry and innovation network around TIH at IIT Palakkad — connecting learners to the wider robotics ecosystem.
Specialists compound. As the vertical grows, the people who understood it early end up owning the systems everyone else builds on.
PlatformSubsystemComponentSTART5 YEARS10 YEARS
YEAR 00Own components
Computer Vision / Robotics Engineer
Build and ship defined parts of a perception, autonomy or deployment pipeline.
Execute with guidance
YEAR 05Own a subsystem
Senior Engineer / Robotics Researcher
Lead perception, localisation or control end to end and guide the technical approach.
Lead technical decisions
YEAR 10Own the stack
Principal Engineer / Head of Autonomy
Set system direction, architecture and the decisions that shape an entire autonomy platform.
Define platform direction
Indicative progression based on how these roles are structured across the industry. Actual titles, pace and scope vary by company, country and individual performance.
Hear it from our alumni
The difference is not what you know. It is what you have shipped.
The same production-first standard our alumni experienced now extends into physical AI — with online depth followed by optional scheduled access to a real robotics lab.
“
I went from tutorial-hell to shipping a production AI feature in a real cohort, on a real timeline.
That is the standard behind this Robotics specialisation: models leave the notebook, meet real constraints, and are tested during an optional five-day physical lab experience at TIH, IIT Palakkad.
A technology innovation hub is where research meets real hardware. Partnering with one means this program is shaped by people building robotics systems, not just teaching them.
Our academic & research partnerDr. A P J Abdul Kalam Block · IIT Palakkad
IIT Palakkad Technology IHub Foundation
This is the building your optional lab week happens in — an IIT-anchored innovation hub with working robotics, fabrication and motion-capture facilities.
5Days on campus (Optional)
30Seats per batch
4Batches a year
3Specialist labs
A real robotics lab, not a simulator
Five optional days on campus working with actual robots — sensors that drift, motors that overshoot, and all the messiness a simulator hides from you.
Curriculum shaped by practitioners
What you learn tracks what the hub's researchers and its industry partners are actually working on, so the syllabus moves as the field does.
Into the innovation ecosystem
The hub sits at the centre of a network of startups, incubators, funds and industry partners — the people who hire, fund and build in this space.
Certification that carries weight
You finish with a credential tied to an IIT-anchored innovation hub — recognisable to exactly the hiring managers you want to reach.
Your Credential
The Certificate You Walk Away With.
A verifiable Certificate of Completion issued in collaboration with the IIT Palakkad Technology IHub Foundation for Artificial Intelligence with Specialization in Robotics.
Issued in collaboration with IIT Palakkad Technology IHub Foundation
Shows your Robotics specialisation and physical-lab learning experience
Six modules that build on each other — maths and Python at the base, perception and deep learning in the middle, an optional physical robotics lab plus deployment at the top.
Python for engineers — NumPy, Pandas, vectorised thinking.
The maths that actually matters: linear algebra, probability, optimisation.
Working with real, messy sensor data instead of clean textbook sets.
Supervised and unsupervised learning, honestly evaluated.
Feature engineering, leakage, and why offline metrics mislead.
Building an end-to-end ML pipeline — your first portfolio project.
Neural networks from first principles, then PyTorch in anger.
CNNs and vision transformers — detection, segmentation, depth.
Training tricks that matter on small, imperfect datasets.
ROS 2 — nodes, topics and the plumbing every robotics team uses.
Sensor fusion, calibration, SLAM and localisation.
Motion planning and control loops: making a model move something.
Five optional days on campus with real hardware, mentors and teammates.
Deploy your perception stack onto a physical robot and watch it fail — then fix it.
Hardware constraints: latency, power, thermals, and edge compute.
Model optimisation and quantisation for on-device inference.
Pipelines, monitoring and drift once the robot is in the field.
Portfolio review, mock interviews and introductions to hiring partners.
Why EdWagon
Built narrow, on purpose.
This is not a general data science course with a robotics chapter bolted on. Everything — the intake, the batch size, the optional lab week — is dedicated to AI applied to robotics.
Merit-based selection
Seats are given on your application and a call with our admissions team — not first-come, first-served. Your cohort is people who earned their seat.
30 seats. Four batches a year.
Intake is deliberately capped in proportion to what our direct hiring partners actually need — so we are not flooding a market we then cannot place you into.
Freshers and early professionals only
One cohort, one starting point. The pace, the projects and the placement support are all tuned for people entering the field — not a mixed room.
Optional 5-day physical robotics lab
On campus at TIH, IIT Palakkad, with real robots. The week where simulation stops being enough and you learn what actually breaks.
Weekly 1:1 mentorship
A recurring session with a practitioner from companies like Google, Meta and Netflix — someone who reviews your actual work, every week.
Global cohort network
You graduate into a community spanning India, UAE and Singapore — three markets hiring for the same scarce skill set.
Optional lab week · on campus
This part does not happen on a video call.
An optional five days at TIH, IIT Palakkad with real hardware, real mentors and your cohort in the room. Drones you assemble yourself, machines you print, rigs you calibrate — the work simulation cannot teach you.
Four projects that become your portfolio — each one shaped like a problem a real team would hand you in your first year on the job.
01Machine learning
ML Pipeline for Predictive Analytics
Take raw, imperfect data through cleaning, feature engineering, training and evaluation into a pipeline that can be re-run and trusted — the workflow every ML role is built on.
PythonPandasscikit-learnPipelines
02Computer vision
Smart City Traffic Monitoring System
Detect, classify and track vehicles from live video, then turn that into flow metrics. Vision under real conditions — occlusion, weather, changing light and a camera that never sits still.
PyTorchObject detectionTrackingOpenCV
03NLP
Building an Intelligent Text Summarizer
Work with transformer models to condense long documents without losing meaning — and build the evaluation that tells you honestly whether the summary is any good.
TransformersHugging FaceEvaluation
04Robotics
Voice-to-Robot Command Simulation
Turn spoken instructions into robot actions — speech to intent to motion — and see what happens when a language model has to drive something physical that can actually get it wrong.
Speech-to-textROS 2SimulationControl
Teachers & mentors
Taught by people who put robots into production.
The programme is run with the team at IIT Palakkad Technology iHub Foundation — the people behind the lab you build in, and the credential you leave with.
Shivam Dutta
Founder & AI Researcher at Edzor
10 years across EdTech & AI
Sabyasachi Behera
Staff Software Engineer at Uber
IIT Kharagpur
Manthan Patel
AI Solutions & Data Science at Hansa Cequity
Associate Consultant
Arshyan Mohd.
AI · Product · Growth at Edzor
IIT Kharagpur
Gaurav Payal
Machine Learning Engineer at CodeUpKid
Bengaluru
Take a Quick Break
Can you outfly burnout?
Too much to read through? Take a break. Here’s a fun game section for you. Catch the skills that keep you moving, dodge the setbacks that stall you, and see how far you get.
No. The program is built for science graduates from any domain — B.Tech, B.Sc, M.Tech, M.Sc, BCA or MCA, whether you have finished or are still studying. Module 01 starts at Python and the maths you actually need, then builds up. What you do need is comfort with problem-solving and the time to keep pace.
How are learners selected?
Through your application. You answer a few questions about your background and what you want from the course, then talk to our admissions team. Seats are given on fit — not first-come, first-served.
Is the 5-day robotics lab compulsory, and is travel included?
No — the lab week at TIH, IIT Palakkad is optional. It is the part of the program that cannot be replicated online, so we strongly recommend it, but you can complete the program without it. The lab sessions themselves are included in the fee. Travel and accommodation are arranged separately — the admissions team will walk you through the options on your counselling call.
Why are there only 30 seats?
Because intake is sized against what our direct hiring partners actually need. Four batches a year at 30 seats keeps the ratio of graduates to genuine openings sensible — and keeps 1:1 mentorship and lab time real rather than nominal.
What if I join and decide it is not for me?
Your full fee is refunded if you withdraw within the first 15 days of the batch commencing. No conditions attached to that window — it exists so you can judge the program from the inside before committing.
Will I be chased with calls and messages after applying?
No. You get one confirmation email as soon as you submit the form, and our team calls you to answer your questions and confirm your place. Beyond that we do not cold call, and we do not send marketing emails or WhatsApp broadcasts.
Can I do this alongside a full-time job or final-year studies?
Yes — sessions run in the evening in your region's timezone (8:00 PM IST, 7:30 PM GST, 9:00 PM SGT) and every session is recorded. The one block that needs planning, if you take it, is the optional five-day lab week on campus.
What certificate do I graduate with?
A Certificate of Completion issued by the Edzor Centre of AI & Technological Excellence in collaboration with IIT Palakkad Technology iHub Foundation, plus four portfolio projects and an optional physical lab week you can actually talk about in an interview — which, in this field, tends to carry more weight than the certificate itself.
30 seats a batch
With TIH at IIT Palakkad
Optional 5-day robotics lab
Get started
The robots are coming. Be the one building them.
Merit-based admission, 30 seats, and a full refund window if it is not for you. Apply, talk to our admissions team, and find out where you stand.
India
UAEStarts 22 Dec 2026
SingaporeStarts 22 Dec 2026
Fabrication Lab
3D printing and CNC — parts you design, then hold
Motion Capture Lab
Ground-truth data for perception
Battery Testing Lab
Power budgets that decide range
