Work through 24 structured lessons to understand how neural networks and deep learning actually work.
Run Jupyter Notebook experiments to see AI concepts in action with real Python code.
Build foundational knowledge in classical AI, CNNs for images, RNNs for text, and generative models.
Learn TensorFlow and PyTorch by implementing algorithms hands-on rather than reading theory alone.
AI for Beginners is a free, structured 12-week curriculum produced by Microsoft that teaches the foundations of artificial intelligence from the ground up. The problem it solves is accessibility: AI and machine learning have become essential skills, but most learning resources either assume a mathematics PhD or stop at a very shallow overview. This course aims to be genuinely beginner-friendly while still covering real technical content. The curriculum is divided into 24 lessons covering the broad landscape of AI approaches. It begins with classical symbolic AI, the rule-based systems from the early days of the field where knowledge was explicitly programmed in, then moves into the modern deep learning era: neural networks, convolutional neural networks for image recognition, recurrent networks for text, and generative models. It also touches on less common approaches like genetic algorithms and multi-agent systems. Each lesson comes with a Jupyter Notebook (an interactive document format where you write and run Python code in a web browser), quizzes, and lab exercises. The two main machine learning frameworks used throughout are TensorFlow and PyTorch, which are the industry-standard Python libraries for building and training neural networks. The curriculum is available in dozens of translated languages. You would use this if you are a developer, student, or curious non-specialist who wants to genuinely understand how AI systems are built rather than just use pre-built APIs. It is designed as a self-paced course you can follow over several weeks, working through the notebooks to run experiments and observe results directly. It intentionally omits Azure-specific cloud services and focuses on conceptual and coding foundations, so it complements more application-focused courses rather than duplicating them.
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