Artificial Intelligence Essentials (AI) including exam

Examples of AI have been in the news a lot lately, it started with chatbots like Google Assistant and now ChatGPT. Of course, AI is much more than just chatbots, yet we will also discuss this to learn the do's and don't of this.

This course will teach you the potential benefits of AI; types of Artificial Intelligence (AI); the basic process of Machine Learning (ML); the challenges and risks associated with an AI project, and the future of AI and Humans in work.

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Target Audience

The Artificial Intelligence Essentials certificate is aimed at individuals with an interest in (or need for) AI in an organisation, particularly those working in areas such as science, engineering, knowledge technology, finance or IT services.

The following job roles are mostly eligible;

Engineers
Scientists
Professional research managers
Chief technical officers
Chief information officers
Organizational change practitioners and managers
Business change practitioners and managers
Service architects and managers
Program and planning managers
Service provider portfolio strategists / leads
Process architects and managers
Business strategists and consultants
Web page developers

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Course Objectives

Recall the general definition of human and Artificial Intelligence (AI).
Describe ‘learning from experience’ and how it relates to Machine Learning (ML) (Tom Mitchell’s explicit definition).
Understand that ML is a significant contribution to the growth of Artificial Intelligence.
Describe how AI is part of ‘Universal Design,’ and ‘The Fourth Industrial Revolution’.
Describe the challenges of Artificial Intelligence, and give general examples of the limitations of AI compared to human systems, general ethical challenges AI raises.
Demonstrate understanding of the risks of Artificial Intelligence, identify a typical funding source for AI projects and list opportunities for AI.
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.

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Course Content

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1. Artificial and Human Intelligence: An Introduction and History

general definition of human and Artificial Intelligence (AI).
‘learning from experience’ and how it relates to Machine Learning (ML) (Tom Mitchell’s explicit definition).
ML is a significant contribution to the growth of Artificial Intelligence.
AI is part of ‘Universal Design,’ and ‘The Fourth Industrial Revolution’.

2. Examples of AI: Benefits, Challenges and Risks

benefits of Artificial Intelligence
advantages of machine and human and machine systems;
challenges of Artificial Intelligence
the limitations of AI compared to human systems
general ethical challenges AI raises
understanding of the risks of Artificial Intelligence
funding source for AI projects
opportunities for AI

3. An introduction to Machine Learning

AI intelligent agent
differences with Machine Learning (ML)
the four rational agent dependencies,
performance measure, environment, actuators and sensors,
reflex, model-based reflex, goal-based and utility-based.
examples of Machine Learning in the following contexts:
- business
- social (media, entertainment)
- science
which typical, narrow AI capability is useful in ML and AI agents’ functionality;
forms of ML:
- supervised
- unsupervised
- reinforcement
the basic schematic of a neutral network.

4. The Future of Artificial Intelligence – Human and Machine Together

Artificial Intelligence (in particular Machine Learning) will drive humans and machines to work together
list future directions of humans and machines working together

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Course Pre-requisites

No specific prior knowledge is required.

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Test Certification

This class comes with an online proctored exam voucher. These will have a validity of 12 months. You will need to schedule and complete your exams within this time frame.

Successful completion of the EXIN BCS Artificial Intelligence Essentials exam:

Examination Details