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This project is a comprehensive educational curriculum designed to teach the fundamental concepts, workflows, and tools of data science. It provides a structured learning path that covers the end-to-end data science lifecycle, including data acquisition, maintenance, processing, and pattern discovery, while grounding theoretical knowledge in practical, real-world applications. The curriculum distinguishes itself through a data-driven pedagogical design that utilizes interactive, notebook-based lessons. By combining narrative text with live code blocks, the platform allows learners to experime

Uses version-controlled hosting to facilitate community contributions and collaborative learning.

Happy-LLM is an open educational resource providing a structured curriculum for artificial intelligence engineering. It serves as a comprehensive tutorial for mastering large language models, focusing on the fundamental principles and practical implementation techniques required to build and deploy generative AI applications. The project is delivered through a series of interactive Jupyter notebooks that combine explanatory text with executable code blocks, allowing for hands-on experimentation. Content is organized into discrete, modular chapters that enable users to navigate specific topics

Uses version control to track updates and facilitate community-driven content contributions.