Applied AI: Computer Vision and Speech Recognition

Artificial intelligence is transforming how computers see the world and understand human speech, but getting started with these technologies can feel overwhelming. This text-based course demystifies the core concepts of computer vision and speech analysis, giving you a clear path to understanding modern AI workflows. By reading through structured explanations and analyzing real-world code snippets, you will learn how computers process images, detect objects, transcribe audio, and extract meaning from spoken language. What you will learn: Understand the fundamental terminology of digital image processing, audio signals, and neural networks; Apply computer vision techniques for image classification, object detection, and semantic segmentation; Explore speech recognition workflows, including acoustic modeling, feature extraction, and text-to-speech synthesis; Analyze modern transformer-based architectures used in state-of-the-art vision and speech applications; Implement practical AI pipelines using popular open-source libraries and API integrations; Practice writing and debugging Python-based code snippets for preprocessing media data. The course begins with essential definitions and foundational mathematical concepts before guiding you through step-by-step written tutorials on building computer vision and speech pipelines. You will study practical scenarios that show how these technologies solve real-world problems. This course is designed for beginners, aspiring data scientists, and software developers who want a solid foundation in AI applications without needing prior advanced mathematical training. Start reading today to unlock the potential of computer vision and speech recognition in your projects.