Embedded Systems & Edge AI Online Live Class by Experts
Our Training/Internship Process
Embedded Systems & Edge AI - Syllabus, Fees & Duration
Introduction
The Embedded Systems & Edge AI course is a 6-month comprehensive program designed to provide practical knowledge in embedded programming, microcontrollers, IoT, Artificial Intelligence, Machine Learning, and Edge Computing. Students will learn to design and develop intelligent devices using hardware and AI technologies through real-world projects.
Course Syllabus
Month 1: Embedded Systems Fundamentals
Introduction to Embedded Systems
- Introduction to Embedded Systems
- Applications of Embedded Systems
- Embedded Systems Architecture
- Embedded Systems Design Process
- Real-Time Embedded Systems Overview
- Embedded Systems vs General Computing
Electronics Fundamentals
- Basic Electronics Concepts
- Analog and Digital Signals
- Electronic Components
- Resistors, Capacitors, and Diodes
- Integrated Circuits
- Circuit Design Basics
Microcontrollers
- Introduction to Microcontrollers
- Microcontroller Architecture
- Arduino Platform
- ESP32 Introduction
- Raspberry Pi Overview
- GPIO Programming
Month 2: Embedded Programming & Hardware Interfacing
Embedded C Programming
- Introduction to Embedded C
- Variables and Data Types
- Operators and Expressions
- Conditional Statements
- Loops and Functions
- Arrays and Pointers
- Memory Management
- Interrupt Programming
Hardware Interfacing
- LED Interfacing
- LCD Display Integration
- Motor Control
- Servo Motor Programming
- Relay Modules
- Sensor Integration
- Camera and Display Modules
Communication Protocols
- UART Communication
- SPI Protocol
- I2C Communication
- CAN Protocol Basics
- Bluetooth Communication
Month 3: IoT & Edge Computing
Internet of Things (IoT)
- Introduction to IoT
- IoT Architecture
- IoT Devices and Applications
- Sensor Networks
- IoT Communication Models
- IoT Security Basics
Edge Computing Fundamentals
- Introduction to Edge Computing
- Cloud Computing vs Edge Computing
- Edge Device Architecture
- Real-Time Data Processing
- Edge AI Concepts
IoT Development
- ESP32 IoT Applications
- MQTT Protocol
- IoT Cloud Platforms
- Device Monitoring Systems
- Remote Control Applications
Month 4: Artificial Intelligence & Machine Learning
AI and Machine Learning Basics
- Introduction to Artificial Intelligence
- Machine Learning Fundamentals
- Supervised Learning
- Unsupervised Learning
- Data Collection and Processing
- Model Training and Evaluation
Computer Vision
- Introduction to Computer Vision
- Image Processing Basics
- OpenCV Fundamentals
- Image Classification
- Object Detection
- Face Recognition
AI Model Deployment
- Introduction to TensorFlow Lite
- TinyML Basics
- AI Model Optimization
- Model Conversion for Edge Devices
Month 5: Advanced Edge AI & Robotics
TinyML Development
- Introduction to Tiny Machine Learning
- Machine Learning on Microcontrollers
- Neural Networks for Edge Devices
- Model Compression
- Quantization Techniques
Edge AI Hardware Platforms
- NVIDIA Jetson Platform Overview
- Raspberry Pi AI Projects
- Google Coral Edge TPU
- AI Accelerator Concepts
Robotics Integration
- Robot Control Systems
- AI-Based Robotics
- Sensor-Based Automation
- Autonomous Systems
Month 6: Industry Projects & Applications
Real World Applications
- Smart Home Automation
- Industrial IoT Applications
- Smart Agriculture Systems
- Healthcare Monitoring Devices
- AI Surveillance Systems
Final Projects
- AI-Based Object Detection System
- Face Recognition Attendance Device
- Smart IoT Monitoring System
- Voice Controlled AI Assistant
- Autonomous Robot Using AI
- Edge AI Smart Device Project
Tools and Technologies
- Embedded C
- Python
- Arduino
- ESP32
- Raspberry Pi
- TensorFlow Lite
- TinyML
- OpenCV
- Machine Learning
- IoT Platforms
- MQTT
- Linux
- Git & GitHub
This syllabus is not final and can be customized as per needs/updates
- Since 2001, Making IT Experts by Experts
- Duration: 1000 Hours (Vary as per your skill)
- Course Fees
- Individual Live Classes (1:1)
- Batch Classes @ Low Fees
- Training on Your Time, Any Where
- Access to Recorded Videos
- Practical Internship on Projects
- 100% Placement Support by our jobsHybrid.com
- Training/Internship Certificate
- Abbotsford
- Alberta
- Barrie
- Brampton
- British Columbia
- Burlington
- Calgary
- Charlottetown
- Delta
- Edmonton
- Gatineau
- Guelph
- Halifax
- Hamilton
- Kamloops
- Kelowna
- Kingston
- Kitchener
- Manitoba
- Mississauga
- Moncton
- Montreal
- Nanaimo
- New Brunswick
- Niagara Falls
- Nova Scotia
- Ontario
- Oshawa
- Ottawa
- Peterborough
- Prince George
- Quebec
- Regina
- Saint John
- Saskatoon
- Sherbrooke
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- Thunder Bay
- Toronto
- Vancouver
- Victoria
- Waterloo
- Whitehorse
- Windsor
- Winnipeg
Course Highlights
Our Locations
Students will learn to develop intelligent devices using microcontrollers, sensors, AI models, and real-time processing technologies.
. **Course Description (Use British Columbia)**
Our **Embedded Systems & Edge AI Course in British Columbia** is a 6-month advanced training program designed to provide practical knowledge in embedded systems, IoT, Artificial Intelligence, Machine Learning, and Edge Computing. Join our **Embedded Systems & Edge AI Training in British Columbia** to build industry-ready skills and prepare for careers in embedded development, IoT, robotics, and AI-based technology solutions.
The course covers embedded programming, hardware interfacing, computer vision, TinyML, robotics, and AI deployment on edge devices through hands-on projects. 
