Image Processing in AI
INTERMEDIATE COURSE
Introducing the newest feature of our AI and
Image Processing course for teens, Deep Learning!
Learn the foundations of artificial neural networks and how to apply them in image processing. Build a deep learning model that you can use to filter and denoise images.
đź’° Price: ÂŁ120
🚀 Age: 13 – 19
⏰ Duration: 12 Hours
đź’» 100% online
📆  Flexible, self-paced learning
🎯 Practical challenges and quizzes
🎓 Certificate included
đź”’Access to community and limited events
Learning grants available
We are committed to widening access to tech and AI. If course funding is difficult please complete the form below and we will be in touch soon.
Course Overview
Tools You Need
Notebook Environment
Laptop/Computer
Internet Connection
STAY AHEAD OF THE CURVE
What you will learn
Image Filtering
Learn Deeper concepts of Fourier Transform and how to filter images using Fourier Transform
Image Classification
Use deep learning for Image Classification using Convolutional Neural Networks
Image Denoising
Get introduced to various methods
for image de-noising. Learn how to use basic de-noising filters and apply Encoder-Decoders
How to solve real world problems using AI
Use applied mathematics skills such as probability and statistics to solve real problems.
Critical thinking and problem solving skills
Develop critical thinking and problem-solving skills.
Deep Learning Principles
Concept of Deep Learning for image processing: Convolutional Neural Networks, Multi-Layer Perceptron, Recurrent Neural Networks
Meet Your Instructor
Piero Paialunga
Machine Learning Engineer, Gen Nine Inc.
Artificial Intelligence and Climate Change Writer
Machine Learning + Python | Aerospace Engineering | Climate Change
A PhD student in Aerospace Engineering at the University of Cincinnati with a Master’s Degree in Physics and Data Scientist, Piero Paialunga is an expert in his field who now works as a Machine Learning Engineer at Gen Nine Inc.
Skilled in Machine Learning and Data Science, Piero takes complex systems and unpacks them easily. Among his numerous accolades, Piero is one of six students to have been selected as a UC Space Research Institute Fellow.
Course outline
EXPLORE EACH MODULE
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INTRODUCTION
We’ll review what is an image, and a colored image. We’ll also discuss Fourier Transform definitions, and how to use the Fourier Transform to filter images.
IMAGE DENOISING
In this section of the course, we will consider various ways of denoising an image. We will first look at the concept of noise, and then we will learn how to use basic denoising filters and apply encoder-decoders (deep learning) approaches.
DEEP LEARNING FOR IMAGE PROCESSING
Deep learning, a branch of machine learning that involves the use of neural networks, has become a key tool for processing images and other data. We’ll look at how deep learning is used in image processing, including convolutional neural networks (CNNs), multi-layer perceptrons (MLPs), and recurrent neural networks (RNNs).
IMAGE CLASSIFICATION
In the introductory course, we saw the NaĂŻve Bayes Classifier. In this course, we will see a much more powerful one: Image Classification using Convolutional Neural Networks.
Don’t worry, you’ll love it!
PROJECT BUILDING
Imagine taking the amazing concepts you’ve learned in this course and bringing them to life in a thrilling real-world project. You’ll be delving into the fascinating field of Image Processing and using state-of-the-art techniques to transform and analyse images in ways you never thought possible!
Unlock the Power of Deep Learning
MASTER AI SKILLS
Deep learning is revolutionising AI and big data analysis.Â
It can solve complex problems – even ones that seemed impossible just a few years ago, and has great potential to impact most industries. It’s no wonder, deep learning techniques have led to major breakthroughs in computer vision.Â
From image labelling to image denoising and image classification, learn what it how it all works. Additionally, you will also learn the basics of Convolutional Neural Networks (CNNs), and how it can be used to perform these tasks.
“The most valuable thing I learnt was that we can still change the world in a lot of innovative ways if we all try and give our best through AI.”
“I loved the hands-on approach to learning. Through practical exercises and projects, I was able to apply the concepts I learned in a real-world context.”
“This online course was amazing! I learned so much and the instructors were very helpful. I would definitely recommend it to anyone interested in the field!”
Frequently asked questions
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WHAT SKILLS ARE REQUIRED TO START THIS COURSE?
Basic understanding of AI and Machine Learning, some familiarity with Python and working with IDE’s and how to use Python Libraries.
CAN I ATTEND THIS COURSE IF I HAVEN’T COMPLETED IN THE BEGINNER COURSE?
Yes, you can! However, we recommend you start with the Introduction to Image Processing and AI Course as it will give you all the skills you need to comfortably complete the intermediate course.
WHO SHOULD I CONTACT IF I HAVE MORE QUESTIONS
For more information, please contact Alanna at [email protected]
WILL THERE BE ANY PROJECTS OR ASSESSMENTS?
The course will put the theory into practice, and provides various activities to do, including building a image processing project using all the techniques covered in the course.
HOW DO YOUR PAYMENTS AND REFUNDS WORK?
Our payment and refund process is designed to be straightforward and customer-friendly through a secure payment gateway. All payments made are the country specific equivalent of the Great Britain Pound (GBP). For the most accurate and up-to-date details on our refund policy, refer to our “Terms & Conditions of Business.”
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