Artem Ex Machina™: become AI Arts Artisan from the ground up
What you'll learn
- Generate beautiful AI art with pre-trained models
- Build your own Generative Adversarial Networks (GANs) from scratch
- Train GAN on a selected set of images
- Create pieces of AI art with your own models
- Become AI art artisan (generative artist)
- Understand how Neural Networks and Generative Adversarial Networks (GAN) work
- Work in your own AI workshop locally (CPU training) or remotely (GPU training)
- Start and manage AI painting project
- Basic familiarity with python programming
- Ability to work in a Docker container will be a bonus
Did you know that computers can generate pictorial art? Have you ever wondered how can they do that? Did you know that the art generated by Artificial Intelligence (AI) has been sold on auctions for thousands of $$$?
Welcome to Artem Ex Machina™! Here you will learn how to become Artificial Intelligence (AI) Artisan by building, training and applying Generative Artificial Networks (GANs) - deep learning networks behind AI generated art. What makes this course unique is the combination of three elements:
Building, training and using GANs from scratch
Applying pre-trained GANs for beautiful AI Arts
Starting, maintaining and managing AI Arts projects
By the end of this course you will, therefore, be able to:
Build and train GANs using your own set of training images
Create pieces of AI Arts with publicly available, FREE, and amazing quality pre-trained GANs models
Understand how Neural Networks, in general, and GANs, in particular, work
Effectively manage AI Arts projects
To get a taster on the kind of images you'll be able to generate by completing this course, have a look at the logo of this course, which has 6 examples of images generated with GANs :)
The course uses Python as a programming language upon which you'll be able to build, train and use your own GANs. Not only you’ll gain practical capabilities when it comes to developing and diagnosing these deep learning models but also you'll gain a proper understanding of theory behind them. Since managing and, potentially, sharing your working environment behind GANs is an important part of the workflow of the generative artist, an integral part of the course is provision of AI-Art-compatible Docker containers and teaching you how to effectively use them. Understanding how GANs work combined with the ability to build them, will give you a strong generative artisanship acumen, and hence strong competitive advantage in the world of Data Science. In addition to that you'll learn how to make an effective use of pre-trained models that were trained for thousands of hours, to create high quality art. Therefore, you'll be able to work on your own local computer as well as remote high performance computing service such as Google Colab using Graphic Processing Units!
The course is split into 6 sections culminating with a 3 capstone projects that you can add to your portfolio:
Introduction. Here you'll learn how to setup your local working environment PLUS how to train and diagnose a hand-written digits GAN
What is a Generative Adversarial Network? Here you'll learn how GANs work and how they are trained PLUS how to train and apply GAN of images of clothing
AI Arts projects. Here you'll learn how to work locally vs how to work remotely and principles of AI Arts project management PLUS how to efficiently download bulk of images for your GAN training
GAN architectures. Here you'll learn how to build and train GAN models from scratch to produce complex grayscale and colour images
GAN+CLIP. Here you'll learn how to use pre-trained models for beautiful AI Arts generation
Capstone projects. Here you'll have the chance to complete three capstone projects to consolidate what you've learnt in the course.
Start you Artem Ex Machina™ journey now!
Who this course is for:
- Data scientists and analyst that want to be able to build and apply Generative Adversarial Network models
- Data scientists and analyst that want to learn or enhance their Deep Learning skills
- STEM professionals wanting to expand into emerging word of AI arts
- Anyone who wants to learn how to start AI Arts workshop
- Anyone interested in AI arts and that wants to understand it
My name is Alexander Abdulkader Kheirallah and I am a data scientist with background in bioinformatics.
After graduating with first-class honours in Applied Biomedical Science as well as PhD in Bioinformatics I worked as a bioinformatician at Cambridge university. My research focussed on functional gene studies and hypotheses generation through the application of 'omics' data. Since then I decided to use the quantitative modelling and programming skills I developed over my career to help solve problems in the wider business community.
As an industrial data scientist I've worked on wide range of predictive projects such as customer churn, customer subscription, customer health, natural language processing, article and web engagement. My stack includes R, python and SQL and I've pushed active and live models to production.
Last but not least, I have an interest in the intersection of Artificial Intelligence and Arts, to explore how to former can inspire the latter.