Course Overview
rtificial Intelligence (AI) is a methodology for using a nonhuman 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 What is a Robot?
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.
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 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
- Introduction and Course Outline
- Human and Artificial Intelligence—Part 1
- Exercise 1
- Human and Artificial Intelligence—Part 2
- Ethics and Sustainability – Trustworthy AI—Part 1
- Ethics and Sustainability – Trustworthy AI—Part 2
- Sustainability, Universal Design, Fourth Industrial Revolution and Machine Learning
- Exercise Two
- Being Human, Conscious, Competent and Adaptable
- Exercise Three
- Applying the Benefits of AI
- Applying the Benefits of AI
- Building a Machine Learning Toolbox
- Building a Machine Learning Toolbox
- Exercise Four
- Building a Machine Learning Toolbox – Two Case Studies
- Building a Machine Learning Toolbox
- Building a Machine Learning Toolbox
- Building a Machine Learning Toolbox
- A Simple Neural Network Schematic
- Exercise Five
- Machine Learning and Consciousness
- The Future of Artificial Intelligence
- Exercise Six
- Learning from Experience
- Conclusion
- Exam Practice and Preparation
- Examination
Englisch