Artificial Intelligence Foundation
(HQ7H8S)
Artificial Intelligence (AI) is a methodology for using a non human system to learn from experience and imitate human intelligent behavior. This training covers the potential benefits and challenges of ethical and sustainable robust Artificial Intelligence (AI); the basic process of Machine Learning (ML) – Building a Machine Learning (ML) Toolkit; the challenges and risks associated with an AI project, and the future of AI and Humans in work.
This course prepares for the EXIN BCS Artificial Intelligence Foundation certification
Audience
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.
Course objectives
In this course, students will learn 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 artificialintelligence (AI) (in particular, machine learning—ML) will drive humans and machines to work together
- Describe a ‘learning from experience’ Agileapproach to projects
Certifications and related examinations
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.
Detailed course outline
Introduction and Course Outline
- Course overview and structure
- Exam information
- Daily schedule
Human and Artificial Intelligence—Part 1
- General definition of AI
- Ethics
- Sustainability
- AI as part of Universal Design and The Fourth Industrial Revolution
- Challenges and risks
Exercise 1
- Opportunities for AI
Human and Artificial Intelligence—Part 2
- Learning from experience
- Applying the benefits of AI
- Opportunities
Ethics and Sustainability – Trustworthy AI—Part 1
- Roles and responsibilities of humans and machines
Ethics and Sustainability – Trustworthy AI—Part 2
- Trustworthy AI
Sustainability, Universal Design, Fourth Industrial Revolution and Machine Learning
- Learning from data, functionality, software and hardware
Exercise Two
- Ethics and sustainability
Artificial Intelligent Agents and Robotics
- AI intelligent agent description
- What a robot is
- What an intelligent robot is
Being Human, Conscious, Competent and Adaptable
- AI project teams
- Modelling humans
Exercise Three
- Human plus machine mindmap
What is a Robot?
- Definition of a robot
- Robot paradigm
Applying the Benefits of AI
- Benefits, challenges and risks
Applying the Benefits of AI
- Opportunities and funding
Building a Machine Learning Toolbox
- How do we learn from data?
Building a Machine Learning Toolbox
- Types of machine learning
Exercise Four
- Define a simple ML problem
Building a Machine Learning Toolbox – Two Case Studies
Building a Machine Learning Toolbox
- Introduction to probability and statistics
Building a Machine Learning Toolbox
- Introduction to linear algebra and vector calculus
Building a Machine Learning Toolbox
- Visualising data
A Simple Neural Network Schematic
- Introduction to neural networks
Exercise Five
- Maturity and funding of an AI system
Open Source ML and Robotic Systems
- Open source software for AI and robotics
Machine Learning and Consciousness
- Introduction to machine learning and consciousness
The Future of Artificial Intelligence
- The human + machine
- What will drive humans and machines to work together
Exercise Six
- Explore the future opportunities for AI and human systems
Learning from Experience
- Agile projects
Conclusion
Exam Practice and Preparation
Examination