AI Powered Computer Vision is a comprehensive 3-day course that prepares students for obtaining and organizing data for fine-tuning a pre-trained ViT (Vision Transformer)! Select your own ViT Image Classification model, and fine-tune it with datasets you’ve prepared, or gathered. This course offers a combination of lectures and hands-on labs, providing participants with a solid understanding of AI concepts and the skills to design and implement AI solutions.

Throughout the course, you will learn about ViT transformer-based architectures, the fundamentals of Python programming for AI models, and the deployment of open source Transformer models. You will begin with data preparation by gathering, cleaning, labeling, and organizing data for the purpose of fine-tuning a ViT.

You will gain practical experience through hands-on exercises with open source ViT frameworks, allowing you to work with fine-tuned models and run workloads on different models to understand their strengths and weaknesses. Additionally, the course covers model formats and provides in-depth exploration of AI programming environments like PyTorch.

Towards the end of the course, you will delve into advanced topics such as context extension through fine-tuning and quantization for a specific application target environment: Road Surface Image Classification. By the completion of the course, you will have the opportunity to earn an AI certification from Alta3 Research, further enhancing your credentials in the field of Artificial Intelligence. This course is ideal for Python Developers, DevSecOps Engineers, and Managers or Directors seeking a overview of AI and its practical application in the enterprise.