Internet of Things (IoT) Bootcamp

Practical Electronics – Covered AC/DC circuit theory, RLC components, diodes, transistors, breadboarding, power supplies, and building basic IoT-ready circuits.

Microcontrollers Principles & Practice (Arduino, ESP32, Raspberry Pi) – Learned microcontroller architecture, GPIO, timers, interrupts, ADC/DAC, serial communication, and hands-on development using Arduino, ESP32 (ESP-IDF & FreeRTOS), Raspberry Pi (Linux + GPIO), and MicroPython.

C, C++, and Python Programming – Built foundations in C, C++, and Python including variables, data structures, control flow, OOP, functions, and completed practical coding projects like calculators, bank systems, and library management software.

IoT Architecture Fundamentals – Studied IoT reference models, system components, edge–fog–cloud architecture, scalability and reliability patterns, and real-world IoT design case studies.

IoT Hardware Communication Protocols – Learned UART/USART, I2C, SPI, OneWire, and CAN protocols, including implementation and hardware-level selection for IoT devices.

Wireless Communication Protocols – Covered Wi-Fi, Bluetooth/BLE, LoRaWAN, Zigbee, Thread, and RF basics with a focus on range, power efficiency, and deployment scenarios.

Network Protocols – Studied TCP/IP, HTTP/HTTPS, REST APIs, MQTT, CoAP, and WebSockets with emphasis on choosing appropriate protocols for IoT connectivity.

IoT Devices, Sensors & Microcontrollers – Covered sensors, actuators, interfacing, power management, component integration, and microcontroller–sensor communication.

Network Protocols & Connectivity – Practiced implementing connectivity layers, secure communication, API interactions, MQTT brokers, and efficient networking for IoT systems.

Data Management & Analytics – Learned time-series data handling, real-time data streaming, dashboards, visualization tools, machine learning for IoT, and predictive maintenance.

IoT Security & Privacy – Covered JSON, XML, Protocol Buffers, encryption, authentication, secure communication channels, and IoT security best practices.

Edge Computing Implementation – Explored edge processing concepts, running computation near devices, integrating edge–cloud workflows, and deploying lightweight services.

IoT Platforms (AWS, Azure, Google Cloud) – Built expertise in cloud IoT platforms, device provisioning, pipelines, data storage, and designing custom cloud IoT solutions.

AI Integration with IoT Systems – Applied machine learning to IoT data, including anomaly detection, real-time analytics, and integrating ML models into cloud or device workflows.

Smart Applications Development – Developed smart home, industrial, and cloud-connected applications combining sensors, wireless protocols, dashboards, and automation logic.

Capstone Project – Designed and built a complete IoT system including architecture, device programming, cloud integration, testing, debugging, and final project presentation.