158.340 kr.
Artificial Intelligence (AI) is a methodology for using a non-human system to learn from experience and imitate human intelligent behaviour.
The BCS Essentials Certificate in Artificial Intelligence tests a candidate’s knowledge and understanding of the terminology and the general principles.
This course covers the potential benefits; types of Artificial Intelligence; 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.
Please note – the exam for this is taken on the last day of the course and the cost is included with the course fee.
There are no specific pre-requisites for the entry to the course or examination, although a good knowledge of computers and a basic understanding of data using computers (e.g. spreadsheets) is highly recommended.
Once registered you will receive a confirmation email directly from the BCS. This email will reference a provisional exam location, date and time and should not be mistaken for a confirmed session.
You will receive a further email from Questionmark (within 48 hours). It is at this stage that you will be provided access to the live calendar to enable you to schedule your exam session.
Examination
All BCS exams are delivered as Remote Proctored. Learners will log into their QuestionMark portal and schedule their exam for any time that suits them at a later date. This must be sat only after 5pm on the final day of the course.
Exam Requirements
If you are taking a BCS exam you must bring photographic identification with you (passport, driving license or student card), as it is a BCS requirement to produce it for the invigilator prior to the exam. Failure to produce a valid form of photographic identification will result in a candidate not being able to sit the exam. For any questions about what form of identification is acceptable please contact your Account Manager or the QA Examination Administration team on 44 (0)1793 696273.
BCS allow additional time for candidates who have a disability or whose native language differs to that of the examination paper. Full details are provided in the BCS Reasonable Adjustments Policy which is available to view on the BCS website. If you believe you qualify for this then please notify the Exam Administration team on the details below as early as possible. At least two weeks' notice will be required for processing this request. Delegates failing to advise QA and provide evidence when requested, may not be allowed the additional support offered via the BCS policy. QA Exam Administration can be contacted by email [email protected] or by phone 44(0) 1793 696162.
Learners will be able to demonstrate a basic knowledge and understanding of general concepts in the following areas:
Human and Artificial Intelligence;
The Machine Learning process;
The benefits, challenges and risks of a Machine Learning project;
The future of humans and machines in Work.
Target Audience
The Artificial Intelligence Essentials course is focussed on individuals with an interest in, (or need to implement) AI in an organisation, especially those working in areas such as science, engineering, knowledge engineering, finance, or IT services.
The following roles could be interested:
Engineers
Scientists
Professional research managers
Chief technical officers
Chief information officers
Organisational 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
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)
ML and Growth of AI
Opportunities for an AI system
Examples of AI – benefits, challenges and risks
Benefits of AI
Challenges of AI
Risks of AI
Funding sources for AI projects
Opportunities for AI
Machine Learning
AI intelligent agent description
Examples of Machine Learning
AI capability useful in ML and AI agents’ functionality
Examples of forms of Machine Learning
Maturity and funding of an AI system
The future of artificial intelligence – human and machine together
AI driving humans and machines to work together
Future directions of humans and machines working together