EXIN BCS Artificial Intelligence Foundation
Artificial Intelligence (AI) is a methodology for using a non-human system to learn from experience and imitate human intelligent behavior. The EXIN BCS Artificial Intelligence Foundation certification tests a candidate’s knowledge and understanding of the terminology and general principles of AI. This Foundation certificate includes and expands on the knowledge taught in the EXIN BCS Essentials Certificate in Artificial Intelligence.
Exam
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per person
Level
Duration
Training Delivery Format
Face-to-face / Virtual Class
Associated Certification
per person
Level
Duration
Training Delivery Format
Face-to-face (F2F) / Virtual Class
Associated Certification
Class types
Public Class
Private Class
In-House Training
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Who should attend?
The EXIN BCS Artificial Intelligence Foundation certification is focused on individuals with an interest in, (or need to implement) AI in an organization, especially those working in areas such as science, engineering, knowledge engineering, finance, education or IT services.
Learning Outcome
You will be able to
- Describe how Artificial Intelligence (AI) is Part of ‘Universal Design,’ and ‘The Fourth Industrial Revolution’
- Demonstrate Understanding of the Artificial Intelligence (AI) Intelligent Agent Description
- Explain the Benefits of Artificial Intelligence (AI)
- Describe how we Learn from Data – Functionality, Software and Hardware
- Demonstrate an Understanding that Artificial Intelligence (AI) (in Particular, Machine Learning (ML)) will Drive Humans and Machines to Work Together
- Describe a ‘Learning from Experience’ Agile Approach to Projects
Course Content
1. An Introduction to AI and Historical Development
1.1 Identify the key definitions of key AI terms
1.2 Describe key milestones in the development of AI
1.3 Describe different types of AI
1.4 Explain the impact of AI on society
1.5 Describe sustainability measures to help reduce the environmental impact of AI
2. Ethical and Legal Considerations
2.1 Describe ethical concerns, including bias and privacy, in AI
2.2 Describe the importance of guiding principles in ethical AI development
2.3 Explain strategies for addressing ethical challenges in AI projects
2.4 Explain the role of regulation in AI
2.5 Explain the process of risk management in AI
3. Enablers of AI
3.1 List common examples of AI
3.2 Describe the role of robotics in AI
3.3 Describe machine learning
3.4 Identify common machine learning concepts
3.5 Describe supervised and unsupervised learning
4. Finding and Using Data in AI
4.1 Describe key data terms
4.2 Describe the characteristics of data quality and why it is important in AI
4.3 Explain the risks associated with handling data in AI and how to minimize them
4.4 Describe the purpose and use of big data
4.5 Explain data visualization techniques and tools
4.6 Describe key generative AI terms
4.7 Describe the purpose and use of generative AI, including large language models (LLMs)
4.8 Describe how data is used to train AI in the machine learning process
5. Using AI in Your Organization
5.1 Identify opportunities for AI in your organization
5.2 List the contents and structure of a business case
5.3 Identify and categorize stakeholders relevant to an AI project
5.4 Describe project management approaches
5.5 Identify the risks, costs, and benefits associated with a proposed solution
5.6 Describe the ongoing governance activities required when implementing AI
6. Future Planning and Impact – Human Plus Machine
6.1 Describe the roles and career opportunities presented by AI
6.2 Identify AI uses in the real world
6.3 Explain AI’s impact on society, and the future of AI
6.4 Describe consciousness and its impact on ethical AI
Certification
| Duration: | 01 hour |
| Number of Questions: | 40 (Multiple Choice) |
| Pass mark: | 65% |
| Open book: | No |
| Electronic equipment allowed: | No |
| Level: | Foundation |
| ECTS Credits: | 2 |
| Languages: | English, Portuguese, Chinese, Dutch, Japanese |
