3.0

Average Course Rating

This course goes beyond theory, offering hands-on experience in building AI systems with the mindset and pace of a modern AI startup. Using a project-driven approach, students learn to architect, develop, and deploy real-world AI solutions entirely in the cloud, leveraging tools like Microsoft Azure, Terraform, and other cutting-edge technologies central to today’s AI ecosystems. Students will incrementally build a production-grade, cloud-deployed AI system—individually and in teams—mirroring the end-to-end process of launching an AI startup. The course emphasizes not just tools, but the engineering mindset needed for building scalable, adaptable, and reliable AI systems. Key focus areas include: 1.) Data and Model Optimization – Streamlining data pipelines, adapting existing models, and using ensembles for efficiency and performance. 2.) System Integration – Developing distributed systems with messaging, NoSQL persistence, and robust monitoring. 3.) Cloud Deployment – Live updating through containerization and orchestration in a 100% cloud-based environment. By the end of the course, students will have built a portfolio-ready AI product and gained a deep, practical foundation in modern AI engineering for production.