This course is designed to guide participants from foundational concepts to practical applications in deep learning and applied AI. It focuses on enhancing skills in Python, Git, and core machine learning, then progresses to neural networks, advanced architectures, and modern tools like PyTorch, Hugging Face, and LangChain. Through hands-on labs, participants will build and optimize models, explore the role of transformers in natural language processing, and observe AI applications in areas such as image classification and sentiment analysis. The course also emphasizes evaluating models for performance, cost, and bias, and deploying them responsibly with security and fairness in mind, culminating in a capstone project where participants will develop and present a complete AI solution. The goal is to provide practical experience, portfolio-ready work, and confidence in applying AI in professional roles.