Essentials Certificate in Artificial Intelligence (ECIA)

The essential first steps in AI training is to understand the principles of AI, its benefits and risks, and the processes behind machine learning. The BCS artificial intelligence experience and imitate the human system to learn and support resources. The AI is a methodology which imitates human intelligent and other preparation materials to work as a non-human system. The methodology for using artificial intelligence AI is to learn from experience and events. The foundation certification is an add on for IT professionals who want to excel in their work using a non-human partner. The additional qualifications along with foundation certificate increases AI skills and career options.

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Course Style

Live Instructor led. Face-to-face or attend from anywhere.

Skill up and get certified, guaranteed

Exam Pass Guarantee

Exam Pass Guarantee

If you don’t pass your exam on the first attempt, You get to re-sit the course for free.

100% Satisfaction Guarantee

100% Satisfaction Guarantee

If you’re not 100% satisfied with your training at the end of the first day, you may withdraw and enroll in a different Classroom course.
Knowledge Transfer Guarantee

Knowledge Transfer Guarantee

High Impact Learning Solutions Designed for students to acquire skills and obtain certification.

What is included?

    • 1 day of ECIA training training.
    • Course material/Slides.
    • Examination Fees.
    • 98.7% Certification Success in First Attempt.
    • Classroom training or attend from anywhere.
    • Training delivered by Professionals with enormous industry experience. 
    • Total comprehensive exam preparation.

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What you will Learn?

Develop your knowledge and understanding of:

  • the terminology and general principles, including benefits and types of AI.
  • the basic process of artificial intelligence AI via (ML).
  • the challenges and risks associated with an AI project.
  • the future of artificial intelligence AI and humans in work.

Award-winning training that you can trust

Who should attend?

Individuals with an interest in (or a need to implement) AI in an organisation, especially those working in areas such as science, engineering, knowledge engineering, finance, or IT services.

Middle and senior managers running or assembling teams to create AI dependent applications and services, that need to understand the context of AI in an industrial setting.

Course Dates

29 Mar, 2021

20 Sept, 2021

Course Outline

1.1 Recall the general definition of human and Artificial Intelligence (AI);

1.2 Describe ‘learning from experience’ and how it relates to (ML) (Tom Mitchell’s explicit definition);

1.3 Understand that ML is a significant contribution to the growth of Artificial Intelligence information;

1.4 Describe how AI is part of ‘Universal Design,’ and ‘The Fourth Industrial Revolution’.

2. Artificial and Human Intelligence: An Introduction and History (25%)

2. Examples of AI: Benefits, Challenges and Risks (30%)

Candidates will be able to:

2.1 Explain the benefits of Artificial Intelligence, and

2.1.1 list advantages of machine and human and machine systems;

2.2 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 raises.

2.3 Demonstrate understanding of the risks of Artificial Intelligence, and

2.3.1 give at least one a general example of the risks of AI;

2.4 Identify a typical funding source for AI projects;

2.5 List opportunities for AI.

3. An introduction to Machine Learning (35%)

Candidates will be able to:

3.1 Demonstrate understanding of the AI intelligent agent description, and:

3.1.1 identify the differences with Machine Learning (ML), and:

3.1.2 list the four rational agent dependencies,

3.1.3 describe agents in terms of performance measure, environment, actuators and sensors, BCS Essentials Certificate in Artificial Intelligence Syllabus V1.0 ©BCS 2018 Page 9 of 16.

3.1.4 describe four types of agent: reflex, model-based reflex, goal-based and utility-based.

3.2 Give typical examples of Machine Learning in the following contexts:

3.2.1 business,

3.2.2 social (media, entertainment),

3.3.3 science.

3.3 Recall which typical, narrow AI capability is useful in ML and AI agents’ functionality;

3.4 Describe and give examples of the following forms of ML:

3.4.1 supervised,

3.4.2 unsupervised,

3.4.3 reinforcement.

3.5 Describe the basic schematic of a neutral network.

4. The Future of Artificial Intelligence – Human and Machine Together (10%)

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.

The exams will increase the career scope of people who want to access machine learning and drive workable results. This is the best course for a high paying job opportunity.

Prerequisites

None.

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