I’m putting together a one-time project to craft a full AI training curriculum aimed squarely at students who already have basic programming literacy and now want to see how AI comes alive in the real world. Every module must stay grounded in practical applications rather than abstract theory, constantly showing where and how the technology is deployed today. Here is what I need from you: • A complete course map that flows from foundational AI concepts through machine-learning algorithms, natural language processing, computer vision, and the newest wave of large-language-model techniques. • Industry-ready use-case libraries: concrete examples drawn from manufacturing, finance, healthcare, retail, and more—each tied to the OEM platforms and SaaS tools actually delivering value (think AWS SageMaker, Google Vertex AI, Azure OpenAI, Hugging Face, NVIDIA, etc.). • Slide decks, lab guides, and assessment questions for each topic, all written with students in mind and tested against current best practices in Python, TensorFlow, PyTorch, scikit-learn, and prompt-engineering workflows. • A succinct instructor handbook explaining learning objectives, class timing, and suggested demos so any trainer can pick it up and run. I’ll review your first-draft outline to confirm the learning path; once approved, you’ll flesh out the content and provide the final files in editable formats (Google Docs or Word for text, PowerPoint or Google Slides for visuals, plus any Jupyter notebooks). The project wraps once the full package meets the outline, aligns with the practical-application focus, and includes at least three end-to-end capstone projects that showcase real-world problem solving with AI.