AI that works on real devices
You move beyond notebooks and see a model actually running on hardware.
Livewire · Special Programs
Edge AI Course in Vellore, Katpadi & Ranipet
Learn to build AI models and run them on small devices like single-board computers and cameras, close to where the data is created.
4 levels10–25 h86 topics3 centresClassroom · Online · Hybrid
01What is Edge AI
What is Edge AI? In plain words.
Edge AI means running artificial intelligence models directly on a device – a camera, a sensor board, a phone or a small computer such as a Raspberry Pi or an NVIDIA Jetson – instead of sending all data to a cloud server. The device makes its decision on the spot, for example spotting a defect, counting people or recognising a gesture. This needs models that are small and fast enough for limited memory and power, plus the skill to set up and test the hardware.
Factories use edge AI for visual inspection on production lines, vehicles use it for driver assistance, and cities and shops use it in smart cameras. Because it works without constant internet and keeps data local, it is growing quickly in manufacturing, automotive, healthcare devices and IoT. Employers want people who understand both the AI side (Python, statistics, vision models) and the practical side of getting a model to run reliably on real hardware.
Vellore district sits on the Chennai–Bengaluru corridor, where electronics, automotive and manufacturing plants use camera-based inspection and smart devices. Edge AI skills give ECE, EEE and CSE students from Vellore, Katpadi and Ranipet a practical route into these fast-growing roles.
What you will be able to do
- Write basic Python programs and use common data libraries
- Apply basic statistics to understand and prepare data
- Explain what edge AI is and how it differs from cloud AI
- Describe how neural networks and CNNs work for image tasks
- Train and test a simple image classification or detection model
- Optimise a trained model for a small device using basic techniques such as quantisation
- Set up an edge device and run a model on it
- Build a simple real-time application using a camera or sensor input
02Why learn it
Why learn Edge AI now?
Six reasons students and professionals in Vellore district pick this skill.
Builds on Python
The foundation course covers Python and statistics, so you do not need to be an AI expert to start.
Vision is in demand
Computer vision for inspection, counting and detection is one of the most used forms of edge AI.
Learn to make models smaller
Optimisation skills such as quantisation help models fit on low-power devices.
Bridges electronics and software
It suits ECE, EEE and CSE students who like both hardware and coding.
Modular short courses
Four focused courses of 10–25 hours let you learn in steps or pick only what you need.
03Who can learn
Who can join this course?
BE/BTech ECE, EEE and CSE students
Combine electronics and programming knowledge in a growing field.
Embedded and IoT learners
Add AI to microcontroller and sensor projects you already build.
AI and data science learners
Take your models from the laptop to real devices.
Final-year project students
Build a smart camera or detection project for your academic work.
Diploma electronics students
Start with the Python and statistics foundation before moving to vision.
Working engineers in automation
Learn how vision-based inspection and edge devices fit into plants.
Before you start: Basic computer skills are needed; some programming experience helps. Start with the Python Statistics and Edge AI Foundations course if you are new to Python.
04Levels & syllabus
Every Edge AI level, topic by topic.
4 programmes on one page. Pick a level to see its modules and every topic covered.
Foundation level
Course on Real-Time Edge AI Application
Learners who can already run a model on a device and want a 10-hour, project-style course on building a working real-time application.
10 hours6 modules · 21 topicsCode LWC206Certificate: Livewire network
These are the core topics this programme always covers. Ask the counsellor on WhatsApp for the detailed, session-wise syllabus.
6 modules · 21 topics
01Real-Time Application Design4 topics
What real-time means on an edge deviceInput, processing and output pipelineLatency and frame-rate targetsChoosing a model for real-time use
02Working with Live Input4 topics
Capturing frames from a cameraReading video files and streamsReading sensor dataPre-processing input for the model
03Running Inference in Real Time3 topics
Running the model frame by frameMeasuring frame rate and latencySimple ways to speed up the processing loop
04Acting on Results4 topics
Displaying predictions on screen with boxes and labelsTriggering simple alerts or outputsLogging results to a fileSending results over a network
05Testing and Reliability3 topics
Testing in different lighting and conditionsHandling errors and restartsStarting the application automatically on boot
06Mini Project3 topics
Building a small real-time detection or classification applicationTesting and demonstrating the applicationDocumenting the application
Foundation level
Course on Edge Deployment Model optimization and Device Setup
Learners who already have basic AI knowledge and want 20 hours on shrinking models and getting them running on edge hardware.
20 hours6 modules · 22 topicsCode LWC205Certificate: Livewire network
These are the core topics this programme always covers. Ask the counsellor on WhatsApp for the detailed, session-wise syllabus.
6 modules · 22 topics
01Edge Deployment Basics4 topics
Cloud versus edge inferenceTypical edge AI use casesCommon edge hardware typesLimits of memory, compute and power
02Device Setup4 topics
Preparing the operating system and environmentInstalling required librariesConnecting a camera or sensorRemote access to the device
03Model Optimisation4 topics
Why models need optimisingModel conversion to lightweight formatsQuantisation basicsMeasuring model size and speed
04Running Inference on the Device3 topics
Loading and running a model on the deviceInference with a lightweight runtime such as TensorFlow Lite or ONNX RuntimePre- and post-processing on the device
05Testing and Maintenance4 topics
Checking accuracy after optimisationMeasuring latency, frame rate and resource useBasic troubleshootingUpdating the model on a deployed device
06Practice Project3 topics
Practice deployment exerciseComparing the original and optimised modelDocumenting the deployment steps
Foundation level
Course on Computer Vision and Deep Learning for Edge Applications
Learners comfortable with Python who want 25 hours on image processing, neural networks and vision models suited to edge devices.
25 hours6 modules · 21 topicsCode LWC204Certificate: Livewire network
These are the core topics this programme always covers. Ask the counsellor on WhatsApp for the detailed, session-wise syllabus.
6 modules · 21 topics
01Image Processing Basics4 topics
How images are stored as pixelsReading, resizing and converting images with OpenCVColour spaces and thresholdingFiltering and edge detection basics
02Deep Learning Fundamentals4 topics
Setting up a deep learning framework such as TensorFlow or PyTorchNeurons, layers and activation functionsTraining, loss and accuracyOverfitting and validation
03Convolutional Neural Networks4 topics
Convolution and poolingBuilding a simple CNNImage classificationData augmentation basics
04Transfer Learning and Object Detection3 topics
Pre-trained models and transfer learningIntroduction to object detectionBounding boxes and confidence scores
05Preparing Vision Models for Edge3 topics
Choosing lightweight models for edge devicesExporting a trained model for deploymentTesting model speed on an edge device
06Practice Project3 topics
Collecting and labelling a small datasetPractice: train and test an image modelRunning the model on live camera input
Foundation level
Course on Python Statistics and Edge AI Foundations
Beginners who need a 25-hour base in Python, basic statistics and AI concepts before the vision and deployment courses.
25 hours5 modules · 22 topicsCode LWC203Certificate: Livewire network
These are the core topics this programme always covers. Ask the counsellor on WhatsApp for the detailed, session-wise syllabus.
5 modules · 22 topics
01Python Basics5 topics
Setting up PythonVariables, data types and operatorsConditions and loopsFunctionsLists, tuples and dictionaries
02Working with Data in Python4 topics
NumPy arraysPandas DataFramesReading and cleaning simple datasetsBasic plotting with Matplotlib
03Statistics Essentials5 topics
Mean, median and modeVariance and standard deviationProbability basicsDistributions and correlationDescriptive statistics with Python
04Machine Learning Basics4 topics
Supervised and unsupervised learningTraining and test dataSimple regression and classification with scikit-learnMeasuring model accuracy
05AI and Edge AI Foundations4 topics
What AI and machine learning areTraining versus inferenceWhat edge AI is and where it is usedSimple machine learning practice exercise
05Choose your level
Which level is right for me?
If you are new to Python, start with Python Statistics and Edge AI Foundations, then take Computer Vision and Deep Learning for Edge Applications. Next, learn Edge Deployment Model Optimization and Device Setup, and finish with Real-Time Edge AI Application to build a working project. If you already know AI, you can start at the deployment course.
| Programme | Level | Hours | Best for |
|---|---|---|---|
| Course on Real-Time Edge AI Application Code LWC206 | Foundation | 10 h | Learners who can already run a model on a device and want a 10-hour, project-style course on building a working real-time application. |
| Course on Edge Deployment Model optimization and Device Setup Code LWC205 | Foundation | 20 h | Learners who already have basic AI knowledge and want 20 hours on shrinking models and getting them running on edge hardware. |
| Course on Computer Vision and Deep Learning for Edge Applications Code LWC204 | Foundation | 25 h | Learners comfortable with Python who want 25 hours on image processing, neural networks and vision models suited to edge devices. |
| Course on Python Statistics and Edge AI Foundations Code LWC203 | Foundation | 25 h | Beginners who need a 25-hour base in Python, basic statistics and AI concepts before the vision and deployment courses. |
Foundation
Course on · Essential · Certificate · SKEP · Executive DiplomaStart here. Core tools, workflow and a practice project.
Professional
Proficient · ProfessionalIndustry-style exercises, advanced features and a portfolio project.
Master
Advanced · Expert · MastersComplete programmes that combine several tools and a capstone project.
06Hands-on
Projects you will build
You learn by making real deliverables – reviewed by your trainer before certification.
Data exploration notebook
Load a simple dataset in Python, clean it and summarise it with basic statistics and charts.
Image classifier
Train a small CNN to classify images into a few categories and check its accuracy.
Optimised model on a device
Convert and quantise a trained model, deploy it on an edge board and compare speed before and after.
Real-time camera application
Build a small application that reads live camera frames and shows predictions on screen.
Tools & features covered
PythonNumPy and PandasMatplotlibOpenCVA deep learning frameworkLightweight model formats for edge inferenceSingle-board computers / edge development boardsUSB or board cameras
Talk to a counsellor about Edge AI
Get the full syllabus PDF, current fee, offers and the next batch date on WhatsApp – usually within minutes during centre hours.
07Careers
Jobs you can apply for after Edge AI
Roles that list this skill in Indian job postings.
Edge AI Engineer (Junior)
Prepares, optimises and deploys AI models on embedded and edge devices.
Computer Vision Engineer (Junior)
Builds and tests image-based models for detection, inspection or counting.
Embedded AI Developer
Integrates AI models with embedded hardware, sensors and cameras.
IoT Developer
Builds connected device solutions that can include on-device intelligence.
AI/ML Intern or Trainee
Supports data preparation, model training and testing in AI teams.
Machine Vision Technician
Sets up and maintains camera-based inspection systems on production lines.
Salary you can expect
Fresher0–2 years₹3–5 LPA
Experienced3–5 years₹6–12 LPA
Senior6+ years₹14–25 LPA
Indicative ranges for India; pay varies by company, city, skills and experience. Edge AI roles are concentrated in Bengaluru, Chennai and Hyderabad. Figures in lakh per annum (LPA).
Industries that use it
Manufacturing and quality inspectionAutomotive and driver assistanceConsumer electronicsSmart cities and surveillanceHealthcare devicesRetail analyticsAgriculture technologyIndustrial IoT
Companies that use these skills
NVIDIAQualcommIntelBoschContinentalTata ElxsiL&T Technology ServicesKPIT TechnologiesWiproHCLTechSiemensHoneywellSamsung R&D Institute India
Examples of well-known companies and sectors in India that use these skills. They are not CareerKraft partners or recruiters.
Your career path
1
AI/Embedded Trainee
Supports data preparation, testing and device setup under guidance.
2
Junior Edge AI / Vision Engineer
Trains, optimises and deploys models for defined use cases.
3
Edge AI Engineer
Owns end-to-end pipelines from model to device and improves performance.
4
Senior Engineer / Solution Architect
Designs edge AI systems and chooses hardware and model strategies for products.
Placements
Students placed from our centres
Vignesh K
Service Lab Assistant
Metric Measurement Technologies
Proficient in AutoCAD Electrical
AJ
Aminudeen J
Intern
Aptagrim Consulting Pvt. Ltd, Hyderabad
Master Program in Software Development
AC
Ashwini C
Teacher
Springdays CBSE School, Vellore
Course on Python
SB
Shilpa B
Associate Networker, Intern
Selfmade Ecom Pvt. Ltd, Rinex
08How you learn
Classroom, online or both.
Same syllabus and certificate in every mode. Your counsellor confirms the mode based on trainer availability for your batch.
Classroom
Learn in our labs at Katpadi, Vellore or Ranipet with your trainer beside you and classmates to build with.
Online
Live sessions from home with the same syllabus, projects and certificate. Good if you cannot travel every day.
Hybrid
Lab days plus online sessions around college or work. The mode depends on trainer availability for your batch.
Certificate
On completing a level and its project assessment, you receive the course certificate of the Livewire network, issued through CareerKraft as the authorised training partner.
Batches & timings
Weekday, weekend and fast-track batches within centre hours (Mon–Sat 9:30 AM – 6:30 PM · Sun 9:00 AM – 2:00 PM). Ask for the next start date at your centre.
Fees & EMI
The fee depends on the level and mode. Your counsellor shares the current fee, offers and EMI options on WhatsApp.
Why learn at CareerKraft
Authorised partner training
Structured syllabi and certificates from the CADD Centre, Livewire and SynergySBS networks.
Learn by doing
Hands-on lab work and a project assessed before you are certified.
Personal attention
Industry-experienced trainers and batches small enough to ask questions.
Placement support
Resume help, mock interviews and job leads when you are ready – no false promises.
11Where to learn
Learn Edge AI at any of 3 centres
Same syllabus, trainer standard and certificate at every centre. Tap the centre you want.
Edge AI in Katpadi
Near Aascars Cinemas, Katpadi
Livewire Katpadi
Edge AI in Vellore
Near Raja Theatre, Vellore
Livewire Vellore
Edge AI in Ranipet
Near SBI, Muthukadai, Ranipet
Livewire Ranipet
09FAQ
Edge AI course – your questions answered
12 answers about levels, duration, eligibility, certificate, placement support and fees.
Still have a question? The counsellor at the centre you prefer replies on WhatsApp.
Ask on WhatsAppWhat is Edge AI?
Edge AI means running AI models directly on devices like cameras, sensor boards or small computers instead of in the cloud. The device makes decisions locally and quickly. It is used in inspection, driver assistance, smart cameras and IoT.
Who can join the Edge AI courses?
ECE, EEE, CSE and IT students, diploma electronics students, embedded and IoT learners and working engineers can join. Basic computer skills are needed. Beginners should start with the Python and statistics foundation course.
How long is each course?
Python Statistics and Edge AI Foundations is 25 hours, Computer Vision and Deep Learning for Edge Applications is 25 hours, Edge Deployment Model Optimization and Device Setup is 20 hours, and Real-Time Edge AI Application is 10 hours.
Which course should I start with?
Start with the Python foundation course if you are new to Python or AI. Then take computer vision, followed by deployment and the real-time application course. If you already know deep learning, you can go straight to deployment.
Are classes available online?
Classes can be taken in Classroom, Online or Hybrid mode, depending on trainer availability. Hardware practice is easier at the centre, so the counsellor will suggest the best mode for each course.
Can I attend a demo class?
Please ask the counsellor at your chosen centre on WhatsApp or phone about a demo or counselling session. They can explain each course and help you plan the order.
Will I get a certificate?
Yes. You receive a course completion certificate from Livewire, our training partner, for each course you complete.
Do you offer placement support?
Yes, we offer placement support such as resume guidance, mock interviews and job leads. We do not guarantee jobs; your projects and skills make the biggest difference.
What is the fee?
Fees depend on which courses you take. The counsellor at your chosen centre will share the current fee, offers and EMI options on WhatsApp.
Do I need my own laptop or hardware?
You can practise on centre computers and lab hardware during class. A laptop is useful for home practice and online classes. Buying your own board is optional.
What are the job prospects and salary?
Edge AI and computer vision roles are growing in automotive, electronics and manufacturing. Freshers typically start around ₹3–5 LPA, with higher pay in Bengaluru and Chennai. Pay varies by company, city, skills and experience.
Which centre can I join and what are the timings?
The courses run at all three centres: Katpadi, Vellore and Ranipet. Centres are open Monday to Saturday 9:30 am–6:30 pm and Sunday 9:00 am–2:00 pm.
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Start today
Get the Edge AI syllabus, fees & batch dates
Fill this in and WhatsApp opens with your details, addressed to the centre you choose. The counsellor replies with the full syllabus, current fee, offers and the next batch.
- Free counselling and demo class
- Real projects and placement support
- Classroom, online or hybrid batches
- Replies Mon–Sat 9:30 AM – 6:30 PM · Sun 9:00 AM – 2:00 PM