Credits: 1.5 (1.5-0-0)
Description
Overview to models for Enterprise AI/ML applications and objectives; Different types of intelligent algorithms; managing supervised, semi supervised and unsupervised algorithms; Building enterprise data models for AI/ML applications; Emergence of new intelligent models and their outcome.
Managing Neural Networks based applications, Managing Bio Inspired and swarm based applications; Managing tradeoffs between computational and data challenges; Managing large scale applications like AI Chat-bots, recommender systems, social CRM systems management and policy interventions, Managing adverse outcome in AI/ML applications; mitigation of risk for adverse outcome; Interventions for policy making and governance; Addressing transparency, fairness, explainability and accountability in enterprise applications.