Computer Vision on Raspberry Pi – Beginner to Advanced

Computer Vision on Raspberry Pi – Beginner to Advanced, available at $129.99, has an average rating of 3.7, with 58 lectures, 10 quizzes, based on 638 reviews, and has 5100 subscribers.

You will learn about What is Raspberry Pi? and what are its components? Understand peripherals that need to be connected to Raspberry Pi Wire up your Raspberry Pi to create a fully functional computer Easily learn preparing SD Card to load Operating System for Raspberry Pi Install packages needed to build Computer Vision applications Learn basic programming aspects of Python Create simple Image Processing applications using Python and OpenCV Build real-world Image Processing applications on Raspberry Pi 4/3/2/Zero Learn basics of Neural Network using Google Colab This course is ideal for individuals who are Anyone who wants to explore Raspberry Pi and interested in building Computer Vision applications or Learn basics of Neural Network using Google Colab It is particularly useful for Anyone who wants to explore Raspberry Pi and interested in building Computer Vision applications or Learn basics of Neural Network using Google Colab.

Enroll now: Computer Vision on Raspberry Pi – Beginner to Advanced

Summary

Title: Computer Vision on Raspberry Pi – Beginner to Advanced

Price: $129.99

Average Rating: 3.7

Number of Lectures: 58

Number of Quizzes: 10

Number of Published Lectures: 58

Number of Published Quizzes: 10

Number of Curriculum Items: 69

Number of Published Curriculum Objects: 69

Original Price: $199.99

Quality Status: approved

Status: Live

What You Will Learn

What is Raspberry Pi? and what are its components?
Understand peripherals that need to be connected to Raspberry Pi
Wire up your Raspberry Pi to create a fully functional computer
Easily learn preparing SD Card to load Operating System for Raspberry Pi
Install packages needed to build Computer Vision applications
Learn basic programming aspects of Python
Create simple Image Processing applications using Python and OpenCV
Build real-world Image Processing applications on Raspberry Pi 4/3/2/Zero
Learn basics of Neural Network using Google Colab

Who Should Attend

Anyone who wants to explore Raspberry Pi and interested in building Computer Vision applications
Learn basics of Neural Network using Google Colab

Target Audiences

Anyone who wants to explore Raspberry Pi and interested in building Computer Vision applications
Learn basics of Neural Network using Google Colab

Computer Vision Applications on Raspberry Piis a beginner course on the newly launched Raspberry Pi 4 and is fully compatible with Raspberry Pi 3/2 and Raspberry Pi Zero.

The course is ideal for those new to the Raspberry Pi and who want to explore more about it.

You will learn the components of Raspberry Pi, connecting components to Raspberry Pi, installation of the NOOBS operating system, basic Linux commands, Python programming and building Image Processing applications on Raspberry Pi and the basics of neural networks.

This course will take beginners without coding skills to a level where they can write their own programs.

The basics of Python programming language are well covered in the course.

Building Computer Vision applications are taught in the simplest manner, which is easy to understand.

Users can quickly learn hardware assembly and coding in Python programming for building Computer Vision applications. By the end of this course, users will have enough knowledge about Raspberry Pi, its components, basic Python programming, and execution of Image Processing applications in real-time scenarios.

The course is taught by an expert team of engineers having PhD and Postdoctoral research experience in Computer Vision and Deep Learning.

Anyone can take this course. No engineering knowledge is expected. The tutor has explained all required engineering concepts in the simplest manner.

The course will enable you to independently build Computer Vision applications using Raspberry Pi.

This course is the easiest way to learn and become familiar with the Raspberry Pi platform.

By the end of this course, users will build Image Processing applications which include scaling and flipping images, varying the brightness of images, performing bit-wise operations on images, blurring and sharpening images, thresholding, erosion and dilation, edge detection, and image segmentation. User will also be able to build real-world Image Processing applications, which includes real-time human face eyes nose detection, detecting cars in the video, real-time object detection, human face recognition, convolutional neural network and many more.

The course provides complete code for all Image Processing applications compatible with Raspberry Pi 3/2/Zero.

Course Curriculum

Chapter 1: Introduction

Lecture 1: Components on Raspberry Pi 3

Lecture 2: Components to be connected to Raspberry Pi

Lecture 3: Downloading Software to Format SD Card

Lecture 4: Formatting SD Card

Chapter 2: Setting up Raspberry Pi

Lecture 1: Downloading NOOBS Operating System

Lecture 2: Copying NOOBS Operating System to SD Card

Lecture 3: Flashing NOOBS Operating System to SD Card

Lecture 4: Installing Packages

Lecture 5: Download Course Codes and Images

Chapter 3: Python Basics

Lecture 1: Print

Lecture 2: If Condition

Lecture 3: Making Decisions

Lecture 4: For loop

Lecture 5: While loop

Lecture 6: Functions

Lecture 7: Dictionaries

Lecture 8: Objects

Lecture 9: Class

Lecture 10: Modules

Chapter 4: Computer Vision Applications

Lecture 1: Load Display Save Images

Lecture 2: Scaling

Lecture 3: Flipping

Lecture 4: Varying Brightness

Lecture 5: Bitwise Operations

Lecture 6: Blurring and Sharpening

Lecture 7: Thresholding

Lecture 8: Erosion and Dilation

Lecture 9: Edge Detection

Lecture 10: Image Segmentation

Chapter 5: Real-world Computer Vision Applications

Lecture 1: Real-time Human Face Eyes Nose Detection

Lecture 2: Detecting Cars in Video

Lecture 3: Pedestrian Detection

Lecture 4: Real-time Object Detection

Lecture 5: Human Face Recognition -1

Lecture 6: Human Face Recognition – 2

Chapter 6: Basics of Neural Network on Google Colab

Lecture 1: Introduction to Neural Networks

Lecture 2: Activation Functions

Lecture 3: Neural Networks in Action

Lecture 4: Neural Network Optimization

Lecture 5: Simple Neural Networks

Lecture 6: Multiple Inputs Neural Networks

Lecture 7: Gradient Descent

Lecture 8: Convolutional Neural Networks Operation

Lecture 9: Working of CNNs

Lecture 10: Deep CNN

Lecture 11: CNN on MNIST

Chapter 7: Hands-on Image Processing Assignments

Chapter 8: FREE Learning Resources on Artificial Intelligence

Lecture 1: Deep Learning Resources

Lecture 2: Generative Adversarial Networks Resources

Lecture 3: Deep Reinforcement Learning Resources

Lecture 4: Machine Learning Resources

Lecture 5: Data Science Resources

Lecture 6: TensorFlow Lite Resources

Lecture 7: Movidius Neural Compute Stick Resources

Lecture 8: Quantum Machine Learning Resources

Lecture 9: Artificial Intelligence Resources

Lecture 10: Math for Machine Learning Resources

Lecture 11: Math for Deep Learning Resources

Lecture 12: Theory and Coding Deep Learning Textbooks

Instructors

Dr. Steven Fernandes
Machine Learning, Computer Vision, Data Scientist
Ramesh Nayak
Professor in Information Science & Engineering

Rating Distribution

1 stars: 19 votes
2 stars: 36 votes
3 stars: 89 votes
4 stars: 243 votes
5 stars: 250 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

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