Face Analysis with Python: MediaPipe, Dlib, and DeepFace

Computer vision is transforming how we interact with technology, and face analysis is at the heart of this revolution. Understanding how to detect faces, identify landmarks, and analyze facial attributes opens up endless possibilities for modern software development. This text-based course guides you through the foundational concepts of face analysis using Python. You will progress from basic terminology to reading and writing clean code that leverages powerful libraries, all while implementing modern Python programming best practices like type hints and structured data. What you'll learn: • Learn the core concepts of computer vision, image coordinates, and facial landmarks • Build face detection and tracking scripts using the lightweight MediaPipe library • Extract facial landmark points with precision using Dlib and shape predictors • Analyze facial attributes such as age, gender, and emotion using DeepFace • Apply modern Python programming conventions including type hints and structured data • Understand ethical considerations, bias, and privacy standards in facial analysis systems. The course starts with essential terminology and setup before moving systematically through each major library, showing you how to read, write, and debug face analysis scripts. Designed for beginners with a basic understanding of Python programming, this course requires no prior experience with computer vision or machine learning. Start reading today to build your foundation in facial analysis and computer vision.