This course, “AI Concepts & Intelligent Systems Foundations,” provides a comprehensive introduction to the core building blocks of AI, including Machine Learning, Deep Learning, AI system architecture, and emerging concepts like Quantum AI. It is carefully designed to simplify complex ideas and help you understand how intelligent systems work in real-world scenarios.
You will begin by exploring the fundamentals of Artificial Intelligence—its evolution, types, and how it compares with human intelligence—along with important discussions on ethical and responsible AI. As you progress, you will gain a clear understanding of Machine Learning techniques such as supervised, unsupervised, and reinforcement learning, along with key concepts like model evaluation, overfitting, and classification.
The course then introduces Deep Learning concepts, including neural networks, activation functions, CNNs, RNNs, and transformer architectures that power modern AI systems like large language models (LLMs). You will also learn how AI systems are built and deployed through data pipelines, training vs inference processes, and cloud-based architectures.
