AI Model Engineering with SageMaker & Hugging Face

Ready to dive into the world of artificial intelligence but unsure where to start with practical application? This course provides a clear, text-based pathway to understanding and implementing AI models from concept to deployment. By the end of this course, you will possess a solid understanding of the AI model lifecycle and gain hands-on experience using powerful tools to build, train, and deploy your own intelligent applications. What you'll learn: Understand core AI and machine learning concepts and their application in real-world scenarios. Build and train machine learning models using AWS SageMaker's managed services. Fine-tune pre-trained models from the Hugging Face ecosystem for specific tasks. Deploy AI models securely and efficiently for inference using SageMaker endpoints. Apply foundational MLOps principles for model versioning and basic monitoring. Practice evaluating model performance and iterating on your AI solutions. This course begins with essential AI and machine learning terminology, progressing through practical steps for model development, training, and fine-tuning. You will then learn to deploy these models into production environments and manage their lifecycle effectively. This course is designed for absolute beginners with no prior machine learning experience, who are eager to become AI engineers or data scientists. Begin your journey into AI engineering today and transform theoretical knowledge into practical skills.