- This course explores how AI can revolutionize the Internet of Things (IoT), enabling smarter devices and systems. Ideal for IoT engineers, this course covers how to enhance IoT workflows and devices with AI, making them more autonomous, responsive, and insightful.
- Level: Intermediate
- Prerequisites: Basic knowledge of IoT and AI fundamentals.
- Assessments: Weekly micro-assessments, final project.
Week 1 - AI in IoT Device Management
Learning OutcomeLearn how to manage IoT devices more efficiently with AI-driven insights
1.1 Using AI to monitor and optimize IoT device performance.
1.2 AI-powered diagnostics and predictive maintenance for IoT devices.
1.3 Automating IoT device provisioning and updates using AI.
Practical Component
Implement AI-driven device management for an IoT network.
Week 2 - Customizing AI Models for IoT Data Processing
Learning OutcomeExplore how to tailor AI models to process specific IoT data types.
2.1 Using AI for real-time processing of sensor data.
2.2 Customizing AI models for different IoT applications (smart homes, healthcare, etc.).
2.3 Using AI for anomaly detection and predictive analytics in IoT systems.
Practical Component
Build a custom AI model for an IoT data stream.
Week 3 - Autonomous IoT Systems with AI Decision Making
Learning OutcomeUnderstand how to create IoT systems that make autonomous decisions using AI.
3.1 AI-powered decision-making in IoT systems.
3.2 Integrating machine learning models with IoT devices for autonomous actions.
3.3 Real-time AI-driven control of smart environments.
Practical Component
Develop an autonomous IoT system with AI decision-making capabilities.
Week 4 - AI-Enabled Edge Computing for IoT
Learning OutcomeLearn how to use edge computing to process AI models locally on IoT devices.
4.1 Introduction to edge AI computing for IoT.
4.2 Benefits of running AI models on the edge for faster decision-making.
4.3 Edge AI for low-latency IoT applications.
Practical Component
Implement an edge AI solution for a time-sensitive IoT application.
Week 5 - AI and Security in IoT Systems
Learning OutcomeLearn how to use AI for enhancing security in IoT networks.
5.1 AI-powered intrusion detection in IoT systems.
5.2 Ensuring secure data transmission and encryption with AI.
5.3 Blockchain and AI for improved IoT security.
Practical Component
Develop an AI-based security solution for IoT systems.
Week 6 - Capstone Project: AI-Driven IoT System Design
Learning OutcomeApply AI techniques to create an intelligent IoT system.
6.1 Design and develop a custom AIoT system for a specific industry use case.
6.2 Peer review and feedback.
6.3 Final project presentation and evaluation.
Practical Component
Present a functional AI-powered IoT system for a real-world application.