Embedded Electronics Bootcamp From Bit to Deep Learning
What you’ll learn
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
Requirements
No Prior Knowledge
Description
No other E-learning content tried linking all digital sciences with embedded systems like we did with this 17 hours content.Starting with FPGA and the VHDL hardware design programming language. specifically from the smallest signal which we call the bit, to building simplified calculation and registration units used in microcontrollers from scratch! And what I mean by scratch is, building it out of basic Logic gates and registers.Then Moving to AVR uC and the famous Arduino, and building it up to run The famous Realtime operating system (RTOS) in order to run Multi-threading based application. Then dialing it up a notch and introducing ESP boards to run IoT applications, establishing communication to Node-red, android devices and learning about remote access control. Closing the whole thing by introducing raspberry pi and Linux. And building up with a basic Python introduction, Neural Networks, before building Embedded Deep learning image processing based models. And all of that is hands on! No plain theory, no philosophical block of texts explaining useless concepts. Getting your hands dirty, is the my main drive here.Hardware Technologies to be taught:FPGARaspberry PIArduinoESP32 (Node MCU)Programming Languages to be taught:C PythonVHDLCommunication and Cloud Technologies to be taught:UARTSPIMQTTNode-RedHivemqTechniques to be taught:Combinational Logic DesignSequential Logic DesignFSMControl UnitsTinker CADDigital and Analog SignalsInterruptsAndroid ControlRemote ControlRTOSSemaphoresMutexesSharing ResourcesQueuesParametrized TasksStructuresLinuxBasics of Artificial IntelligenceNeural Networks Deep Neural NetworksCNN
Overview
Section 1: The Story Of The Bit
Lecture 1 The Story Of The Bit
Lecture 2 Transistor Logic Gates
Lecture 3 Before we go further
Lecture 4 The Binary System
Lecture 5 Storage Circuits
Lecture 6 5.The Basis of GPU Circuits
Lecture 7 The Display Hardware
Lecture 8 Understanding The Differences
Section 2: VHDL Resource Files
Lecture 9 Get All The Source Files
Section 3: Combinational Logic Design
Lecture 10 Combinational Logic
Lecture 11 Combinational Logic Design P1
Lecture 12 Combinational Logic Design P2
Lecture 13 Complex Gates
Lecture 14 Quick VHDL Intro
Lecture 15 Downloading Software
Lecture 16 Complex Gates Example
Lecture 17 Combinational Logic-Programming AND Gate
Lecture 18 Combinational Logic-Programming OR Gate
Lecture 19 Combinational Logic-Programming XOR Gate
Section 4: Multiplexer Circuits
Lecture 20 Multiplexers
Lecture 21 Multiplexer Building by Basic Gates
Lecture 22 Multiplexer using VHDL
Section 5: Binary Representation
Lecture 23 Binary Representation
Lecture 24 Binary Operations P1
Lecture 25 Binary Operations P2
Section 6: Adder Circuits
Lecture 26 Adders Introduction
Lecture 27 Half Adder Implementation
Lecture 28 1 Bit Adder Implementation
Lecture 29 Grounding Inputs
Lecture 30 Combining IO Buses
Lecture 31 Extending 1-bit Adder to multi-bit
Lecture 32 Signed Numbers Subtraction
Section 7: Design Techniques
Lecture 33 Dataflow vs Behavioral vs Structural
Lecture 34 Casting
Section 8: Arithmetic Logic Unit Design ( ALU)
Lecture 35 ALU
Lecture 36 Behavioral ALU
Lecture 37 ALU Overflow handling
Lecture 38 ALU Logic Operations
Lecture 39 ALU Integer Multiplication and Division
Section 9: Sequential Design
Lecture 40 Proccess
Lecture 41 Combinational Vs Sequential
Lecture 42 RS Latch
Lecture 43 RS Latch Operation
Lecture 44 RS Latch Demo
Lecture 45 D latch
Lecture 46 D Flip Flop
Lecture 47 Clock and Data
Lecture 48 D Flip Flop Behavioral
Lecture 49 Finite State Machine
Section 10: VHDL Project – Data path and Controller
Lecture 50 Project Introduction
Lecture 51 Project Implementation Part 1
Lecture 52 Project Implementation Part 2
Lecture 53 Project Implementation Part 3
Lecture 54 Project Implementation Part 4
Lecture 55 Project Implementation Part 5
Lecture 56 Project Implementation Part 6
Lecture 57 Project Implementation Part 7
Lecture 58 Project Implementation Part 8
Lecture 59 Project Implementation Part 9
Section 11: Arduino IO, Power and Interconnections
Lecture 60 Digital Input
Lecture 61 Digital Output
Lecture 62 Internal Pull Up and Noise
Lecture 63 Arduino Boards
Lecture 64 Bread Board Basics
Lecture 65 Powering Arduino
Section 12: Arduino Programming and Digital Simulation
Lecture 66 Sketch
Lecture 67 The Meaning Behind Loops
Lecture 68 Conditional Statements
Lecture 69 TinkerCAD Introduction
Lecture 70 TinkerCAD Simulation Part 1
Lecture 71 TinkerCAD Simulation Part 2
Lecture 72 UART
Lecture 73 Motor Status Over UART
Lecture 74 Debouncing
Lecture 75 Variables
Lecture 76 Switch Statement
Lecture 77 Arrays
Section 13: Arduino Programming and Analog Simulation
Lecture 78 ADC
Lecture 79 TMP36 Connection
Lecture 80 TMP36 Interfacing
Lecture 81 DAC
Lecture 82 PWM Vs Analog
Lecture 83 PWM Analog Control
Lecture 84 Functions
Lecture 85 Speed Based Motor Control Part 1
Lecture 86 Speed Based Motor Control Part 2
Lecture 87 Speed Based Motor Control Part 3
Section 14: Arduino Interrupt
Lecture 88 Interrupt Importance
Lecture 89 Buttons and Diodes
Lecture 90 Interrupt Application Part 1
Lecture 91 Interrupt Application Part 2
Section 15: Arduino LCD Interfacing
Lecture 92 LCD Terminal Breakdown
Lecture 93 LCD Application Part 1
Lecture 94 LCD Application Part 2
Section 16: Introduction To IoT
Lecture 95 What is IoT
Lecture 96 Node Red
Lecture 97 MQTT
Section 17: IoT Source Files
Lecture 98 Download IoT Source Files
Section 18: Preparing NodeMCU (ESP32)
Lecture 99 Downloading IDE
Lecture 100 Setting Up The Environment Part
Lecture 101 Connecting To WiFi
Section 19: IoT Android Control
Lecture 102 Android Emulator
Lecture 103 Preparing NodeMCU Android Sketch
Lecture 104 Installing The Android Control App
Lecture 105 Testing Application
Lecture 106 Wiring Analog
Lecture 107 Adding Analog Control
Lecture 108 Testing Analog Over WiFi
Section 20: IoT: MQTT and Node Red
Lecture 109 Preparing NodeJS And NodeRed
Lecture 110 Installing Packages
Lecture 111 Preparing The Broker
Lecture 112 NodeRED Backend Preparation
Lecture 113 MQTT Nodemcu and Callbacks
Lecture 114 Callbacks And ASCII
Lecture 115 Establishing MQTT Connection with NodeMCU
Lecture 116 Testing Application
Section 21: IoT Application Implementation
Lecture 117 Publishing Analog Data UI
Lecture 118 Publishing Analog UI
Lecture 119 Understanding Interval Publishing with NodeMCU
Lecture 120 Programming Interval Publishing
Lecture 121 Node-red Charts
Lecture 122 Node-Red ON-OFF Charts
Lecture 123 Node-Red Gauge
Section 22: RTOS Resource Files
Lecture 124 Download RTOS Resource Files
Section 23: RTOS : Tasks
Lecture 125 Multi Threading Intro
Lecture 126 Multi Tasking
Lecture 127 Scheduler
Lecture 128 Preparing The Tools
Lecture 129 Creating Multiple Tasks P1
Lecture 130 Creating Multiple Task P2
Lecture 131 C Macros
Section 24: RTOS: Semaphore and Mutex
Lecture 132 Binary Semaphore intro
Lecture 133 Task Crashing Demo
Lecture 134 Semaphore Implementation
Lecture 135 Priority Semaphore
Lecture 136 Mutex Demystified
Section 25: RTOS: Queues and Task Data Exchange
Lecture 137 RTOS Queues and Data sharing
Lecture 138 Implementing Queue
Lecture 139 Checking Queue Status
Lecture 140 Sending Text To Queue
Lecture 141 C Struct
Lecture 142 Sending Struct To Queue
Lecture 143 Combining Queues And Semaphore
Section 26: Raspberry Pi
Lecture 144 Burning Raspberry OS
Lecture 145 Raspberry Headless Mode Configuration
Lecture 146 RapberryPi SSH
Lecture 147 Setting Up VNC for Headless Mode
Lecture 148 Setting Up Raspberry PI
Lecture 149 Setting Up The Resolution
Lecture 150 Checking Internet Connection
Lecture 151 What now?
Section 27: Python: What you need to know
Lecture 152 Introduction To Python
Lecture 153 Python Data Types
Lecture 154 Python Lists
Lecture 155 List Operation Functions
Lecture 156 Conditional Statements and Indent
Lecture 157 For Loop
Lecture 158 Functions
Section 28: Neural Networks
Lecture 159 Neural Networks
Lecture 160 Neurons
Lecture 161 The Neuron Calculations
Lecture 162 Training Data
Lecture 163 Multi-Class Training
Section 29: Convolutional Neural Networks (CNN)
Lecture 164 Deep Learning
Lecture 165 Features of an Image
Lecture 166 Convolutional Neural Network
Lecture 167 Convolutional Layer
Lecture 168 Activation Function
Lecture 169 Pooling Layer
Lecture 170 Fully Connected Layer
Lecture 171 CNN Full Model
Lecture 172 What will we do now?
Section 30: Linux Libs Environment Preparation
Lecture 173 Installing with apt-get and pip
Lecture 174 Creating Virtual Environment
Lecture 175 Installing System Dependencies
Lecture 176 Installing Tensorflow and Keras
Lecture 177 Linking Interpreter with Virtual Environment
Section 31: CNN Implementation
Lecture 178 Preparing Dataset
Lecture 179 CNN Part 1
Lecture 180 CNN Part 2
Lecture 181 CNN Part 3
Lecture 182 CNN Part 4
Lecture 183 CNN Part 5
Lecture 184 CNN Part 6
Lecture 185 CNN Part 7
Lecture 186 CNN Part 8
Lecture 187 CNN Part 9
Lecture 188 CNN Part 10
Lecture 189 CNN Part 11
Anyone who want to learn about Embedded Systems from Scratch,Electronics Hobbyists,Robotics Hobbyists,Computer Engineers,Electrical and Electronics Engineers
Course Information:
Udemy | English | 16h 18m | 7.16 GB
Created by: Mouhammad Hamsho
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