Course Summary
Throughout the Artificial Intelligence (AI) Foundation training course, demonstrations will be presented using standard open-source software and cloud services. You will explore AI and technological requirements to develop a machine learning portfolio
In the coruse you´ll learn to:
1. Ethical And Sustainable Human And Artificial Intelligence
• Recall the general definition of Human Intelligence and Artificial Intelligence
• Make parallels between ‘learning from experience’ and Machine Learning (ML) via Tom Mitchell’s definition
• Understand that ML is a significant contribution to the growth of AI
• Describe how AI is part of Universal Design and The Fourth Industrial Revolution
• Describe a modern approach to human logical levels of thinking using Robert Dilts’ Model.
• Describe the three fundamental areas of sustainability.
2. Applying the Benefits, Challenges, And Risks of Machine Learning
• Explain the benefits of Artificial Intelligence
List advantages of machine and human-machine systems
• Describe the challenges of Artificial Intelligence
• General examples of AI limitations compared to human systems
• General ethical challenges AI raises
• Demonstrate understanding of the risks of • Artificial Intelligence
• Give at least one general example of the risks of AI
• Identify a typical funding source for AI projects
• List opportunities for AI
• Describe how sustainability relates to AI and how our values will drive the use of AI and change our society.
3. An Introduction To Machine Learning Theory And Practice
• Demonstrate an understanding of the AI intelligent agent description
• Identify the differences between AI and ML
• List the four rational agent dependencies
• Describe agents in terms of performance measure, environment, actuators, and sensors
• Describe four types of agent: reflex, model-based reflex, goal-based, and utility-based
• Give typical examples of Machine Learning in the following contexts: Business, Social (Media, Entertainment), Science
• Recall which typical, narrow AI capability is useful in ML and AI agents’ functionality
• Recall the basic theory of ML
• Describe the basic schematic of a neural network
• Know how to build a practical Machine Learning Toolkit
4. The Management, Roles And Responsibilities Of Humans And Machines.
• Demonstrate an understanding that Artificial Intelligence (in particular, Machine Learning) will drive humans and machines to work together
• List future directions of humans and machines working together
• Describe a ‘learning from experience’ Agile approach to projects
• Describe the type of team members needed for an Agile project
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