Candidates will be able to:1.1 Recall the general definition of human and Artificial Intelligence (AI)1.2 Describe ‘Learning from experience’ and how it relates to Machine Learning (ML) (Tom Mitchell’s explicit definition)1.3 Understand that ML is a significant contribution to the growth of Artificial Intelligence1.4 Describe how AI is part of ‘Universal Design’ and The Fourth Industrial Revolution
Candidates will be able to:3.1 Demonstrate an understanding of the AI intelligent agent description, and: 3.1.1 Identify the differences between Machine Learning (ML) 3.1.2 List the four rational agent dependencies 3.1.3 Describe agents in terms of the performance measure, environment, actuators and sensors 3.1.4 Describe four types of agent: reflex, model-based reflex, goal-based and utility-based3.2 Give typical examples of Machine Learning in the following contexts: 3.2.1 Business 3.2.2 Social (media, entertainment) 3.3.3 Science3.3 Recall which typical, narrow AI capability is useful in ML and AI agents functionality3.4 Describe and give examples of the following forms of ML: 3.4.1 Supervised 3.4.2 Unsupervised 3.4.3 Reinforcement3.5 Describe the basic schematic of a neutral network
Candidates will be able to:2.1 Explain the benefits of Artificial Intelligence, and 2.1.1 list advantages of the machine and human and machine systems2.2 Describe the challenges of Artificial Intelligence, and give: 2.2.1 general examples of the limitations of AI compared to human systems 2.2.2 general ethical challenges AI raises2.3 Demonstrate an understanding of the risks of Artificial Intelligence, and 2.3.1 give at least one a general example of the risks of AI2.4 Identify a typical funding source for AI projects2.5 List opportunities for AI
Candidates will be able to: 4.1 Demonstrate an understanding that Artificial Intelligence (in particular, Machine Learning) will drive humans and machines to work together 4.2 List future directions of humans and machines working together
Venkadesh Narayanan is the Principal Consultant at Fhyzics Business Consultants Private Limited and President at Product Development and Management Association (India) - An Indian affiliate of PDMA, USA. He is a Mechanical Engineer and an MBA with over 25 years of experience in Consulting, Business Analysis, Supply Chain Management, New Product Development and Process Improvement. Narayanan is a former member of Indian Civil Services [IRAS 2000 Batch] and served at Indian Railways, Larsen & Toubro – ECC, Siemens (USA), Euro-Pro LLC (USA) and Latex International (USA) prior to joining Fhyzics.
Venkadesh Narayanan is the Recognized Instructor from APICS, USA and represents APICS, USA in India as an International Channel Partner. He is also functioning as an Approved WAREX Assessor for Confederation of Indian Industry (CII) – Institute of Logistics. He pioneered the application of business analysis in movie industry for the first-time in India through Thani Oruvan in 2015 and subsequently consulted for 5 other movies such as Mersal 2017 and Velaikkaran 2017.
Narayanan is also a member of several professional bodies and holds the below certifications: Certified Business Analysis Professional (CBAP®), IIBA®, Canada Certified PMI - Professional in Business Analysis (PMI-PBA®), USA Certified Professional in Requirements Engineering (CPRE-FL), IREB®, Germany Certified Supply Chain Professional (CSCP), APICS, USA New Product Development Professional (NPDP), PDMA, USA Certified Packaging Professional (CPP), IoPP, USA Certified Business Process Professional (CBPP), ABPMP, USA Certified in Production and Inventory Management (BSCM), APICS, USA Certified in Lean from Society of Manufacturing Engineers, USA Certified in Six Sigma from Motorola University, USA.