The equity-centered AI hardware curriculum is designed based on principles of Universal Design for Learning (UDL) and Culturally Responsive Pedagogies (CRP). The curriculum is divided into two parts. During the two modules students are encouraged to participate in various activities to strengthen their understanding of hardware concepts, mainly centered around FPGAs and circuits. During the last two modules, students are encouraged to engage with IoT boards applications and its integration with machine learning algorithms


Module 1

Mathematical models in digital electronics

Learning Objectives: Design combinational and sequential circuits by applying knowledge about the mathematical models used in digital electronics.

  • Illustrate binary and decimal numbers and apply their conversion techniques using push buttons and switches in hardware
  • Apply knowledge about Boolean logic to design combinational circuits using logic gates
  • Design sequential circuits (Finite State Machines) and implement them on a programmable chip in the hardware platform

Module 2

Digital circuit design and implementation

Learning Objectives: Design and implement circuits to perform basic computer operations, sense data, and store information

  • Implement circuits to read and write from memory by differentiating between memory devices 
  • Create a basic model of a computer capable of doing arithmetic and logical operations 
  • Evaluate the uses of sensors by analyzing and modifying software codes that operate them to acquire sensed data

Module 3

IoT applications

Learning Objectives: Experiment with hardware sensors in IoT applications for monitoring and controlling devices in real-time.

  • Create a web server to provide an interface through which a user can send control commands to interact remotely with microcontrollers
  • Extract motion telemetry from an Inertial Measurement Unit (IMU) and relay the information to a visualization panel
  • Measure the temperature and humidity parameters of the environment and visualize the data captured on a dashboard hosted on a server
  • Measure the temperature and humidity parameters in an environment and control connected devices using a smart voice assistant

Module 4

Artificial Intelligence in IoT applications

Learning Objectives: Make predictions using data from sensor hardware modules using AI algorithms

  • Utilize RGB sensor modules to create logic tables that allow making predictions about object characteristics 
  • Utilize different methods to measure distances and apply those methods to appropriate situations