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AWS Certified AI Practitioner Exam — Domain 1: Fundamentals of AI and ML Welcome to Video 1 of our AWS Certified AI Practitioner series! In this foundational video, we explore the core concepts and terminologies that power modern AI and ML systems. Whether you're new to artificial intelligence or preparing for the AWS AI certification, this video will help you build a strong conceptual base. 📚 In this video, you will learn: ✅ Definitions of key terms: AI, ML, Deep Learning, Neural Networks, NLP, Computer Vision 🔍 Differences between AI, ML, and Deep Learning ⏱️ Types of inferencing: Batch vs Real-time 📊 Types of data used in AI models: Structured, Unstructured, Labeled, Unlabeled 🧪 Learning types: Supervised, Unsupervised, Reinforcement Learning 💡 Key Takeaways: Build a solid foundation for understanding AWS AI/ML services and use cases 📺 Watch Next: Video 2 will cover Identifying Practical Use Cases for AI — including automation, decision support, and real-world applications like fraud detection and recommendation systems. 🔔 Subscribe to stay updated with the full guided series and ace your AWS Certified AI Practitioner exam! 👍 Like, Share, and Comment if this video helped you understand AI/ML fundamentals! #AWS #AIPractitioner #MachineLearning #ArtificialIntelligence #AWSCertification #DeepLearning #NLP #ComputerVision #CLFAI01 #CloudComputing
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