Rabia Mazhar is an Artificial Intelligence researcher, educator, and computer scientist with specialization in Machine Learning, Deep Learning, Computer Vision, Generative AI, and Explainable AI.

Rabia has one year of hands-on experience developing AI agents for real-world workflows and automation, with a focus on designing agentic systems that can understand goals, reason through multi-step tasks, use external tools, retrieve and process information, and execute actions with minimal human intervention. His experience includes applying LLMs, tool integration, workflow orchestration, memory, and autonomous decision-making to build practical AI solutions that improve efficiency and automate complex processes.

As an instructor, Rabia is passionate about making complex AI concepts accessible to students, researchers, and industry professionals. His courses combine theoretical foundations with hands-on practical implementation, enabling learners to build real-world AI, machine learning, deep learning, and computer vision applications from scratch.

Whether you are a beginner starting your AI journey or an experienced practitioner looking to deepen your expertise, Rabia's courses are designed to provide clear explanations, practical examples, and industry-relevant skills that can be directly applied to research and professional projects.