Learning Outcomes:
Understand the language of artificial intelligence, machine learning and analytics;
Appreciate the fundamental concepts of analytics and AI (e.g., distinguish between AI, ML and analytics, supervised versus unsupervised versus reinforcement learning, reasoning, intelligence, etc);
Recognise and analyse the capabilities and limitations of AI and analytics and explore their potential strategic and operational impact;
Appreciate the potential opportunities through exploring a variety of application areas;
Be aware of the benefits of a strategy-driven versus a data-driven approach;
Understand ethics, and the regulatory frameworks governing the use of data and algorithms, as well as legislation coming down the line;
Understand the capabilities organisations require to successfully leverage artificial intelligence and analytics;
Appreciate the challenges organisations face in realising expected outcomes as they look to adopt AI and analytics.
Indicative Module Content:
What is business analytics? What is AI/Machine learning (ML)? What problems can be addressed with analytics, AI, and ML? process mining, privacy, risks, ethics, regulatory environment, requirements for success.