Via this course, the students will have a grasp on the ML system development pipeline and by the successful completion thereof, the students will be able to:

• compare and contrast ML system design with traditional software design
• create and manage training dataset
• effectively develop and train models
• scale-up training for large models
• evaluate and calibrate models and debug ML systems
• track experiments and handle model versioning
• compress and optimize the models and deploy them on various platforms