Difficulty: Intermediate. Categories: Applications and Development.
Software Engineering for AI is a practical course that teaches students essential software development practices and methodologies specifically tailored for building, deploying, and maintaining artificial intelligence systems. The course bridges the gap between machine learning models and production-ready software by covering fundamental concepts such as version control, testing frameworks, and architecture design, alongside AI-specific MLOps practices like model versioning, experiment tracking, and data pipeline management. Through hands-on development projects, students will learn collaborative coding, containerization with Docker, and continuous integration and deployment (CI/CD). By the end of the course, students will be equipped to build reliable AI applications, ensure model reproducibility, and deploy scalable machine learning models to production environments using modern cloud platforms and API frameworks.
Learning objectives
