Modern Computer Vision & Generative AI with Machine Learning

Modern Computer Vision & Generative AI with Machine Learning

Modern Computer Vision & Generative AI with Machine Learning is the study of how computers can not only interpret images and videos but also generate new ones using advanced AI methods. Computer vision enables machines to identify and understand objects, actions, or patterns in visual input, while generative AI uses data to create new content that feels real. With the help of machine learning, these technologies power innovations like medical image diagnosis, driverless cars, face recognition, smart surveillance, and even digital art creation.

This certification helps learners gain a clear understanding of these fast-growing technologies, along with practical experience in building AI systems that see and create. By combining machine learning with vision and generative tools, participants learn to design solutions that can solve real-world problems and open new possibilities in both technical and creative industries.

Who should take the Exam?

This exam is ideal for:

• AI/ML Engineers
• Data Scientists
• Software Developers
• Robotics Engineers
• Healthcare Professionals (Tech-focused)
• Creative Professionals
• Researchers & Academics

Skills Required

• Knowledge of Python programming.
• Basics of machine learning and neural networks.
• Familiarity with deep learning frameworks (TensorFlow/PyTorch).
• Understanding of data preprocessing for images and videos.
• Analytical and problem-solving skills.

Course Outline

Domain 1 - Introduction to Computer Vision

Domain 2 - Machine Learning Foundations for Vision

Domain 3 - Deep Learning in Computer Vision

Domain 4 - Generative AI Fundamentals

Domain 5 - Practical Applications of Generative AI

Domain 6 - Vision & Generative AI Integration

Domain 7 - Deployment of Vision & Generative Models

Domain 8 - Ethics, Challenges & Future of Vision & Generative AI