AI for Beginners: A Comprehensive 12-Week Curriculum

The 'AI for Beginners' curriculum is structured over 12 weeks, encompassing 24 detailed lessons. Each lesson is designed to build upon the previous one, creating a logical flow of learning. The curriculum is divided into several key sections, including an introduction to AI, symbolic AI, neural networks, computer vision, natural language processing, and other AI techniques. It also dedicates a crucial section to AI ethics and responsible AI. For each topic, you'll find pre-reading materials, executable Jupyter Notebooks (available in PyTorch or TensorFlow), and practical labs to reinforce your understanding. The curriculum is hosted on GitHub and boasts extensive multi-language support, with over 50 translations available, ensuring accessibility for a global audience. Instructions for cloning the repository locally, with or without translations, are provided for a streamlined experience.

While this curriculum provides a strong foundation in AI for beginners, it's important to note what is intentionally excluded to maintain focus and manage scope. The curriculum does not cover business cases of using AI in business; for this, learners are directed to Microsoft Learn's 'Introduction to AI for business users' or the AI Business School. Classic Machine Learning is also not a primary focus, with a recommendation to refer to the 'Machine Learning for Beginners Curriculum'. Practical AI applications built using Cognitive Services are also outside its scope, with guidance towards specific Microsoft Learn modules for vision, NLP, and Azure OpenAI Service. Specific ML Cloud Frameworks like Azure Machine Learning, Microsoft Fabric, or Azure Databricks, and Conversational AI and Chat Bots are also not covered in depth, with pointers to dedicated learning paths. Finally, the deep mathematics behind deep learning is not a focus, with a recommendation for advanced texts like 'Deep Learning' by Goodfellow et al.

This curriculum leverages powerful and widely-used tools in the AI landscape. You will gain practical experience with TensorFlow and PyTorch, two of the leading frameworks for deep learning. The lessons are accompanied by executable Jupyter Notebooks, which serve as both theoretical guides and practical coding environments. For many topics, hands-on labs are available, allowing you to apply learned concepts to solve specific problems. Additionally, the curriculum integrates links to Microsoft Learn modules for related topics, providing a pathway to deeper exploration of areas like Computer Vision and Natural Language Processing on Microsoft Azure. The use of these industry-standard tools ensures that the skills acquired are directly transferable to real-world AI development.

Learning AI can be a collaborative journey, and this curriculum encourages community engagement. Learners are invited to join the official AI Discord server to connect with fellow students and experienced developers, share insights, and receive support. For product feedback or specific questions encountered during development, the Azure AI Foundry Developer Forum is available. The 'Help Wanted' section also encourages contributions, inviting users to suggest improvements or report errors by raising an issue or creating a pull request on the GitHub repository. This supportive ecosystem ensures that learners have access to assistance and can contribute to the ongoing improvement of the curriculum.