ROBOTICS, AI & IOT CRASH COURSE Specialization.

Module 1: Embedded Systems Foundations

• Architecture & Hardware: Explore Embedded System Architecture, comparing embedded systems versus general-purpose systems.

• System Typologies: Understand Real-Time Systems and essential IoT Fundamentals.

• Source Management: Learn to use modern development tools along with Git & GitHub foundational workflows.

Module 2: Electronics & Embedded C

• Hardware Hardware: Learn physics essentials through Electronics Fundamentals and Digital Electronics.

• Low-Level Code: Write hardware-level code using Embedded C Programming.

• Silicon Control: Manage hardware architectures using Memory Management, Interrupt handling, and Register-Level Programming.

Module 3: Microcontrollers & Development Boards

• Hardware Ecosystems: Get hands-on experience with prototyping platforms including Arduino, ESP32, and Raspberry Pi.

• Industrial Foundations: Study baseline architecture configurations through an introduction to STM32 boards.

• Peripherals & Buses: Drive data lines using General-Purpose Input/Output (GPIO) pins along with UART, SPI, and I2C Communication protocols.

Module 4: Sensors, Actuators & IoT

• Environmental Inputs: Interface microcontrollers with Temperature Sensors, Ultrasonic Sensors, RFID chips, and GPS modules.

• Network Infrastructure: Transfer data packages across distances using the MQTT protocol and Firebase cloud backends.

• Interactivity: Establish stable Smart Device Communication channels.

Module 5: Python for Embedded AI

• Language Training: Master core Python Fundamentals to process complex data arrays.

• Data Processing: Leverage the NumPy library for heavy data cleaning and processing workflows.

• Visual Computing: Connect camera feeds using OpenCV Basics and implement Sensor Data Visualization loops.

Module 6: Artificial Intelligence for Embedded Systems

• Intelligence Ecosystems: Learn foundational AI Fundamentals and Machine Learning Basics.

• Low-Power AI: Explore TinyML and Edge AI Concepts utilizing an overview of TensorFlow Lite.

• AI-Assisted Development: Accelerate hardware engineering tasks using ChatGPT and GitHub Copilot.

Module 7: Computer Vision & Edge AI

• Image Processing: Build visual algorithms using advanced OpenCV scripts.

• Spatial Tracking: Implement structural Face Detection and Object Detection architectures.

• Smart Modules: Build Al Camera Applications by combining software logic with hardware platforms like ESP32-CAM and the Raspberry Pi Camera.

Module 8: Professional Development

• Identity Branding: Build a professional code portfolio on GitHub and write a technical industry resume.

• Career Readiness: Go through interview preparation exercises, document hardware setups, and perfect project presentations