Cognitive AI represents a transformative leap in how machines understand and interact with the world. Despite its potential, practical challenges remain in making these systems accessible and applicable across diverse domains. This tutorial addresses how multimodal models, combined with Retrieval-Augmented Generation (RAG) and agentic workflows, can enable cognitive AI systems to deliver personalized, context-aware solutions. With applications ranging from educational tools to assistive technologies for the elderly and disabled, this tutorial focuses on practical strategies for training, optimizing, and deploying these models and pipelines, making them both scalable and accessible to researchers and practitioners.