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

There are no prerequisites for attending our Artificial Intelligence (AI) Foundation training course.

Exam details: Duration: 60 Minutes Format: Closed Book, 40 Multiple Choice Questions Delivery: Online, Webcam Proctored Pass Mark: 26 out of 40

Following your booking, a confirmation message will be sent to all participants, ensuring you're well-informed of your successful enrollment. Calendar placeholders will also be dispatched to assist you in scheduling your commitments around the course. Rest assured, all course materials and access to necessary labs or platforms will be provided no later than one week before the course begins, allowing you ample time to prepare and engage fully with the learning experience ahead.

Our comprehensive training package includes all the necessary materials and resources to facilitate a full learning experience. Enrollees will be provided with detailed course content, encompassing a wide array of topics to ensure a thorough understanding of the subject matter. Additionally, participants will receive a certificate of completion to recognize their dedication and hard work. It's important to note that while the course fee covers all training materials and experiences, the examination fee for certification is not included but can be purchased separately.

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