BCS Foundation Certificate in Artificial Intelligence | Event in undefined | Townscript
BCS Foundation Certificate in Artificial Intelligence | Event in undefined | Townscript

BCS Foundation Certificate in Artificial Intelligence

Nov 16 - 19 '20 | 06:30 PM (IST)
Online Event

Event Information

Why take this course: 
Artificial Intelligence (AI) is a methodology for using a non-human system to learn from experience and imitate human intelligent behavior. The BCS Foundation Certificate in Artificial Intelligence tests a candidate’s knowledge and understanding of the terminology and general principles of AI. This syllabus covers the potential benefits and challenges of Ethical and Sustainable Robust Artificial Intelligence; the basic process of Machine Learning (ML) – Building a Machine Learning Toolkit; the challenges and risks associated with an AI project, and the future of AI and Humans in work.

Program Outline: 

Ethical and Sustainable Human and Artificial Intelligence

  • Recall the general definition of Human and Artificial Intelligence (AI).
  • Describe what are Ethics and Trustworthy AI
  • Describe the three fundamental areas of sustainability and the United Nation’s seventeen sustainability goals.
  • Describe how AI is part of ‘Universal Design,’ and ‘The Fourth Industrial Revolution’.
  • Understand that ML is a significant contribution to the growth of Artificial Intelligence.
  • Describe ‘learning from experience’ and how it relates to Machine Learning (ML) (Tom Mitchell’s explicit definition).

Artificial Intelligence and Robotics

  • Demonstrate understanding of the AI intelligent agent description
  • Describe what a robot is
  • Describe what an intelligent robot is
  • Applying the benefits of AI - challenges and risks
  • Describe how sustainability relates to human-centric ethical AI and how our values will drive our use of AI will change humans, society and organizations.
  • Explain the benefits of Artificial Intelligence by.
  • Describe the challenges of Artificial Intelligence
  • Demonstrate understanding of the risks of AI project
  • List opportunities for AI.
  • Identify a typical funding source for AI projects and relate to the NASA Technology Readiness Levels (TRLs).

Starting AI how to build a Machine Learning Toolbox - Theory and Practice

  • Describe how we learn from data – functionality, software and hardware,
  • Recall which typical, narrow AI capability is useful in ML and AI agents’ functionality.
  • The Management, Roles and Responsibilities of humans and machines
  • Demonstrate an understanding that Artificial Intelligence (in particular, Machine Learning) will drive humans and machines to work together.
  • List future directions of humans and machines working together.
  • Describe a ‘learning from experience’ Agile approach to projects

Venue

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