Foundations, real-world use cases, and how AI creates value in products and businesses.

Write clean, efficient code and automate workflows using Python fundamentals and libraries.

Supervised & unsupervised learning, model evaluation, and practical problem framing.

From perceptrons to deep nets: layers, activation functions, and training dynamics.

Prompting, fine-tuning, and building LLM-powered apps with real tools and best practices.

Communication, interviewing, and a clear roadmap to land roles in AI and data.