Practical Python for Data & AI

Learn the fundamentals of Python programming, including syntax, data types, control flow, functions, and writing clean, readable code. This category builds the foundation needed for data processing and machine learning.

Learn core algorithms through practical Python examples, focusing on problem-solving, efficiency, and real-world applications.

Learn how to work with data using Python, including reading files, handling sensor data, preprocessing, normalization, and basic feature extraction. Focused on preparing real-world data for machine learning.

Learn core machine learning concepts and algorithms using Python. Covers model training, evaluation, and lightweight models suitable for deployment on resource-constrained devices.

Learn the fundamentals of TinyML and how machine learning runs on microcontrollers. Covers constraints, workflows, model optimization, and the transition from Python-trained models to embedded systems.

Hands-on, end-to-end projects that combine Python, data processing, machine learning, and TinyML. Learn by building real examples from data collection to on-device inference.