Embedded Electronics Bootcamp: From Bit to Deep Learning

Embedded Electronics Bootcamp: From Bit to Deep Learning paid course free. You will Learn Embedded Systems, IoT, RTOS, Deep Learning, Linux and Raspberry PI, ESP32, Arduino

  • Hardware Design Using FPGA by Learning VHDL
  • Raspberry Pi, Arduino and ESP32
  • Microcontroller Programming and Simulation
  • Multi-Threading For Embedded Systems and RTOS
  • IoT, Remote Control and Monitoring for Embedded Systems
  • Linux Based Embedded Systems
  • Python
  • Deep Learning and Image Processing

Embedded Electronics Bootcamp: From Bit to Deep Learning Course Requirements

  • Windows Machine
  • Node MCU
  • Arduino
  • Raspberry PI 3 or Higher


Hardware Technologies to be taught:

  • FPGA
  • Raspberry PI
  • Arduino
  • ESP32 (Node MCU)

Programming Languages to be taught:

  • C
  • Python
  • VHDL

Communication and Cloud Technologies to be taught:

  • UART
  • SPI
  • MQTT
  • Node-Red
  • Hivemq

Techniques to be taught:

  • Combinational Logic Design
  • Sequential Logic Design
  • FSM
  • Control Units
  • Tinker CAD
  • Digital and Analog Signals
  • Interrupts
  • Android Control
  • Remote Control
  • RTOS
  • Semaphores
  • Mutexes
  • Sharing Resources
  • Queues
  • Parametrized Tasks
  • Structures
  • Linux
  • Basics of Artificial Intelligence
  • Neural Networks
  • Deep Neural Network

No other e-learning content tries to connect all digital science with embedded systems like we do, starting with FPGA and VHDL hardware design programming languages. Especially from the smallest signal, we call a bit, to the simplified calculation and register unit used in building microcontrollers from scratch! And what I mean by zero is to build it from basic logic gates and registers, then turn to AVR uC and the famous Arduino, and build it to run the famous real-time operating system (RTOS) to run based on it.

Then, mark it a little bit and introduce The ESP board is used to run IoT applications, establish communication with Node-red and Android devices, and learn remote access control.

End everything by introducing raspberry pi and Linux. And before building a model based on integrated deep learning image processing, a basic introduction to Python and neural networks is given. There is no simple theory, no philosophical text block explaining useless concepts. Getting your hands dirty is my main motivation here.

Who this course is for:

  • Anyone who want to learn about Embedded Systems from Scratch
  • Electronics Hobbyists
  • Robotics Hobbyists
  • Computer Engineers
  • Electrical and Electronics Engineers

Source: https://www.udemy.com/course/embedded-electronics-bootcamp-from-bit-to-deep-learning/

Embedded Electronics Bootcamp: From Bit to Deep Learning

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