INTERNET OF THINGS (IoT) WITH ARTIFICIAL INTELLIGENCE

Being a successful student requires understanding how you learn, identifying your values, and setting clear goals. It also means mastering time and financial management, developing strong note-taking and test-taking skills, collaborating effectively, and leveraging technology to enhance your efficiency. In this course, you will learn essential communication, writing, and presentation skills. Additionally, you will focus on financial literacy through the Enriched Academy program, designed specifically for Oxford College students, to help you confidently manage your finances.

In this module, students will gain foundational knowledge of IoT, its architecture, and applications including its key elements like IT devices and sensors, networking essentials for IoT and explore IoT. They will explore the historical development of cybersecurity and its critical role in today’s IoT business landscape. Furthermore, students will analyze the benefits and challenges of implementing cybersecurity measures, while also examining the latest trends in digital technology that affect organizations worldwide.

In this module, students will dive into the core principles of AI-Driven Insights from IoT Data, Real-Time Data Processing and Embedded AI. This module provides the knowledge and skills for learners to deploy AI models directly on IoT devices with limited computational resources, learning how to optimize AI for constrained environments.

Students will learn how to use platforms like AWS IoT, Azure IoT Hub, or Google Cloud IoT for managing devices, analyzing IoT data and integrating AI services. They will also learn some aspects of machine learning libraries, alongside cloud-based AI services, to train and deploy AI models that interact with IoT systems.

Students will learn the foundational concepts of IoT-specific security challenges and learn to implement encryption, authentication, and access control protocols to secure IoT devices and data. They will explore how AI can be used to detect anomalies and security breaches in IoT systems, helping to secure connected devices from cyber threats.

Students will explore data security controls, with a focus on how to deal with large volumes of data generated by IoT systems, learning to preprocess, clean, and structure data for meaningful analysis or model training. The module covers data handling, explaining the data lifecycle within a typical organization, and discusses how organizations utilize logging and monitoring as key security controls. They may develop and train AI models, such as regression models, classification algorithms, or clustering techniques, to derive insights from IoT data. The course highlights the industry’s best practices in predictive Analysis working on anomaly detection using AI models — an essential control aimed at addressing human errors, often considered the weakest link in cybersecurity.

This course introduces students to the essential components of the end-to-end architecture of IoT systems, from device-level communication to cloud-based data storage and AI-driven insights. Through this comprehensive approach, students will gain the knowledge needed to effectively design high level design architecture to help manage and respond to cybersecurity demands of today and future.

Students will learn and participate in testing IoT systems, ensuring that data collection, communication, and AI integration areis functioning as intended. They will learn work optimizing AI algorithms to be more efficient on IoT devices, especially in resource-constrained environments like embedded systems or edge computing devices.

Students will explore Troubleshooting IoT Issues such as connectivity issues, device failures, or data anomalies that are common in IoT systems. Students will also learn on Adaptation to Complex Environments as IoT systems often involve complex, multi-layered architectures, requiring students to adapt quickly to evolving requirements, constraints, and technology.

IoT applications are transforming industries worldwide by enabling smart, connected solutions across various domains. This module will equip students with a foundational understanding of IoT and practical skills to apply IoT technology in real-world contexts, preparing them for entry-level roles or further study in the field.

In this capstone module, students will apply knowledge from IoT, AI, and cloud integration to design and implement a smart system. Drawing from skills developed in earlier courses, students will collect sensor data, analyze it using AI algorithms, and automate intelligent responses. The capstone emphasizes real-world applications such as smart homes, industrial monitoring, or connected healthcare solutions.