Thank you for sending your enquiry! One of our team members will contact you shortly.
Thank you for sending your booking! One of our team members will contact you shortly.
Course Outline
Introduction to Edge and Agentic AI
- Exploring the fundamentals of agentic AI and edge computing
- Evaluating latency, privacy, and bandwidth constraints
- Comparing cloud-based and edge-based agent architectures
Designing Lightweight Agent Architectures
- Refining agent loops for constrained systems
- Implementing asynchronous designs for computational efficiency
- Striking a balance between autonomy and network connectivity
Configuring the Development Environment
- Installing Python frameworks suited for edge AI
- Setting up TensorFlow Lite and PyTorch Mobile
- Deploying test environments on Raspberry Pi or comparable hardware
Implementing On-Device Inference
- Converting and quantizing models for edge deployment
- Executing inference via TensorFlow Lite and ONNX Runtime
- Integrating inference outputs into agent decision-making loops
Integrating Agents with Hardware and IoT
- Connecting sensors, actuators, and IoT modules
- Building local data collection and processing pipelines
- Ensuring offline functionality and event-driven behaviors
Optimization and Monitoring
- Tuning performance for low power consumption and high speed
- Applying edge caching and model compression techniques
- Monitoring and debugging edge agents
Practical Project: Deploying a Lightweight Agent on Edge Hardware
- Designing a compact autonomous agent for IoT or robotics applications
- Implementing model inference and local logic
- Testing and optimizing for latency and system reliability
Summary and Next Steps
Requirements
- Proficiency in Python programming
- Foundational knowledge of machine learning workflows
- Basic familiarity with embedded or edge computing principles
Target Audience
- Embedded developers integrating AI capabilities into hardware systems
- Edge ML engineers specializing in on-device inference solutions
- Robotics teams deploying agentic AI for autonomous operations
21 Hours
