Introduction of the Course

The rise of IoT, autonomous systems, smart devices, and real-time analytics has created a massive demand for Edge AI — AI processing done directly on edge hardware without relying on cloud servers. Edge AI enables faster decisions, lower latency, improved security, and cost efficiency.

Netskill’s Edge AI Development Training equips professionals with the skills to build lightweight machine learning models, optimize them for edge devices, and deploy them on hardware like NVIDIA Jetson, ARM microcontrollers, mobile processors, and IoT gateways. As a leading corporate Edge AI training company, Netskill ensures a hands-on, industry-focused program designed for cutting-edge product development.

All modules are accessible on the Netskill LMS with videos, gamified checkpoints, quizzes, assessments, and certification.

Courses: Instructor-Led, In-Person, or Self-Paced

Online Instructor-Led Edge AI Training

Live demonstrations, coding sessions, device-level optimization practice, and expert-led Q&A.

In-Person Edge AI Development Workshops

Hardware-based labs, real-time model deployments, microcontroller programming, and device testing sessions.

Self-Paced Edge AI Program on Netskill LMS

Video content, coding exercises, IoT/AI demos, gamified learning, quizzes, assessments, and certification — accessible anytime.

Target Audience for Corporate Edge AI Development Training

Ideal for:

• AI/ML engineers
• IoT developers
• Embedded systems engineers
• Cloud & DevOps teams exploring edge-to-cloud frameworks
• Product and R&D engineers
• Robotics and automation professionals
• Smart manufacturing and Industry 4.0 teams
• Technical architects

What Are the Modules Covered?

Module 1: Introduction to Edge AI

• What is Edge AI?
• Edge vs. cloud vs. hybrid AI deployment
• Real-world use cases: autonomous vehicles, smart factories, healthcare devices, robotics

Module 2: Edge Hardware & Architectures

• NVIDIA Jetson family
• ARM Cortex processors
• Coral TPU & Movidius Myriad
• IoT gateways and microcontrollers
• Hardware selection criteria

Module 3: Edge AI Frameworks & Tools

• TensorFlow Lite
• PyTorch Mobile
• OpenVINO
• ONNX Runtime
• Edge ML toolchains overview

Module 4: Model Optimization for Edge Devices

• Quantization, pruning & weight sharing
• Knowledge distillation
• Reducing model size and inference time
• Converting models to TFLite, ONNX, and other edge formats

Module 5: Embedded AI Development

• ML on microcontrollers (TinyML)
• Sensor data processing
• Real-time inference constraints
• Ultra-low-power model design

Module 6: Deploying AI Models on Edge Devices

• Deployment pipeline
• Setting up inference engines
• Runtime testing, benchmarking & validation
• Integrating models with sensors, actuators, and IoT systems

Module 7: Edge Connectivity & Cloud Integration

• MQTT, REST, WebSockets
• Edge-to-cloud architecture design
• Data streaming, event processing, and device orchestration

Module 8: Security & Optimization for Edge AI

• Securing models on-device
• Data privacy and encryption
• Hardware-level security features
• Performance optimization in constrained environments

Module 9: Real-World Edge AI Projects & Certification

• Hands-on implementation
• Industry case studies
• Final assessments and certification on Netskill LMS

(All modules include videos, content files, quizzes, and gamified activities on the Netskill LMS.)

Importance of Edge AI Development Training

Edge AI is transforming the future of digital systems. This training helps organizations:

• Reduce latency, data transfer cost & cloud dependency
• Improve security through on-device processing
• Build highly scalable real-time solutions
• Empower teams with AI-driven IoT capabilities
• Enhance innovation in robotics, manufacturing, healthcare & automation
• Deploy intelligent features in constrained hardware environments

Training Skills and Competencies for Employees

Employees will gain competencies in:

• Edge AI system architecture
• Model optimization and deployment
• Embedded ML & microcontroller programming
• Hardware-based AI testing
• Edge-to-cloud communication
• Building secure and reliable edge intelligence
• Cross-functional collaboration between AI, IoT & embedded teams

Netskill Approach to Edge AI Development Training

Netskill ensures a highly practical, industry-aligned approach with:

• Real-world hardware-based labs
• Step-by-step AI deployment demos
• Hands-on optimization & TinyML exercises
• Gamified learning outcomes for better retention
• High-quality videos, quizzes, assessments, and certification
• Continuous access to modules on Netskill LMS
• Customizable training for enterprise needs

Why Choose Netskill as Your Edge AI Development Training Partner?

Organizations trust Netskill because:

• We are a leading corporate Edge AI development training company
• Offer Online, In-Person & Self-Paced training formats
• Delivered by Edge AI, ML, embedded & IoT experts
• Includes industry-oriented labs, demos & case studies
• Netskill LMS includes video content, quizzes, assessments & certification
• Gamified learning ensures engaging and measurable progress
• Training can be tailored to your hardware, architecture, and industry