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Course Description

The ICT Introduction to Artificial Intelligence course provides students with a basic understanding of AI. It allows them to understand the subsets of AI and the different types based on functionality and technology. Students will learn about the development and history of AI and the people who were important pioneers, influencers and creators in this field of computer science. Students will understand the differences between artificial narrow intelligence, artificial general intelligence and artificial super intelligence. They will learn about reactive machines, limited memory, theory of mind and self-awareness. Students will explore the world of machine learning, including AI robots and understand how they function and the purposes they serve. The course provides examples of real-world applications of AI and how it solves problems and benefits society. Considerations about ethics, privacy and security will be explored. Students will gain a practical understanding through many examples of the technology and experiences. They will also learn the implications for the future of AI and how it benefits mankind. Additionally, students will be exposed to the extensive and innovative available careers.

Course Outline

Lesson 1: Describing the Subsets of AI

  • 1.1.1 Define Artificial Intelligence and how it relates to problem solving
  • 1.1.2 Describe how algorithms are used in AI
  • 1.1.3 Explain what an algorithm consists of and how they are used in problem solving
  • 1.1.4 Define “Big Data” and examples of it in today’s world
  • 1.1.5 Describe some everyday examples of AI and their purposes
  • 1.1.6 Describe the significant impact of AI in various areas

Lesson 2: Subsets and History of AI

  • 2.1: DESCRIBING THE SUBSETS OF AI
  • 2.1.2 Describe how these subsets are connected
  • 2.1.3 Explain why machine learning is the most used area of AI
  • 2.1.4 Explain the difference between machine learning and deep learning
  • 2.2: Describe how AI has developed over time
  • 2.2.1 Create a timeline of the development of AI
  • 2.2.2 Identify who first coined the word “Artificial Intelligence” and when
  • 2.2.3 Identify milestones in the development of AI
  • 2.2.4 Describe some examples of how AI has been used over time (product examples)
  • 2.2.5 What are some international laws and ethics regulations regarding the use of AI

Lesson 3: AI Types Based on Technology

  • 3.1: TYPES OF AI ACCORDING TO TECHNOLOGY
  • 3.1.1 Identify the three types of AI that are divided by technology
  • 3.1.2 Explain why narrow AI is the only one achieved so far
  • 3.1.3 Describe some examples of narrow AI
  • 3.1.4 Explain what Natural Language Processing is and how it provides a personalized experience
  • 3.1.5 Explain how narrow AI can be reactive or have limited memory
  • 3.1.6 Describe examples of narrow AI in today’s world
  • 3.1.7 Define what factors make an AI a "deep AI"
  • 3.1.8 Explain how deep AI is different from narrow AI
  • 3.1.8 Define Artificial Super Intelligence

Lesson 4: AI Types Based on Functionality

  • 4.1.1 IDENTIFY THE FOUR TYPES OF AI THAT ARE DIVIDED BY FUNCTIONALITY
  • 4.1.2 Describe what a reactive machine can and cannot do
  • 4.1.4 Explain how reactive machines work
  • 4.1.5 Describe some everyday examples of reactive machines
  • 4.1.6 Define the limited memory class of machines
  • 4.1.7 Explain how the “Theory of Mind” machines for the future are different from reactive and limited memory machines
  • 4.1.8 Explain how machines with self-awareness are the final future step of AI

Lesson 5: Machine Learning in AI

  • 5.1: HOW DOES MACHINE LEARNING FIT INTO AI
  • 5.1.2 Define machine learning
  • 5.1.2 Describe how artificial intelligence applies to machine learning
  • 5.1.3 Identify the four stages of machine learning training
  • 5.1.4 Explain how data collection is the first step in machine learning
  • 5.1.5 Identify examples of machine learning
  • 5.1.6 Identify examples of machine learning
  • 5.1.7 Explain how machine learning works
  • 5.2: DESCRIBE THREE CATEGORIES OF MACHINE LEARNING
  • 5.2.1 Define supervised learning
  • 5.2.2 Define unsupervised learning
  • 5.2.3 Define reinforcement learning
  • 5.2.4 Describe how machines use data differently in each category of machine learning

Lesson 6: AI and Robotics

  • 6.1: AI AND ROBOTICS TOGETHER
  • 6.1.1 Explain how AI and robots work together
  • 6.1.2 Identify examples of robots that use AI
  • 6.1.3 Describe how robots use AI to accomplish tasks
  • 6.1.4 Explain how robots help people in different areas of life
  • 6.1.5 Identify different types of robots

Lesson 7: The Future of AI and Careers

  • 7.1.1 Explain how the “Theory of Mind” AI will apply to the future
  • 7.1.2 Explain how AI will help solve problems
  • 7.1.3 Define deep neural networks
  • 7.2 DESCRIBE SOME CAREERS IN AI
  • 7.2.1. Identify careers that use AI
  • 7.2.2 Explain some soft skills that people in AI careers will need to be successful
  • 7.2.3 Explain ways career fields will be impacted by AI
  • 7.2.4 Describe the skills and background needed to have a career in AI
  • 7.2.5 Describe career paths in AI
  • 7.2.6 Identify some companies that hire AI professionals

Lesson 8: Legal and Ethical Considerations

  • 8.1.1 Identify what ethical considerations will need to continue to be addressed in AI in the future
  • 8.1.2 Explain some security issues that arise with AI
  • 8.1.3 Explain what “algorithmic bias” means
  • 8.1.4 Describe how training data affects the accuracy of supervised machine learning
  • 8.1.5 Identify privacy issues involved with AI
  • 8.1.6 Explain how culture, beliefs and religion can create bias/conflict in AI
  • 8.1.7 Define what ethical guidelines, organizations and principles govern them

Notes

Participants will have 12 months to complete this online, self-paced, self-study course.

All necessary course materials are included.

Computer and internet access required,

 

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Section Title
ICT Introduction to Artificial Intelligence (AI) (Online)
Delivery Options
Online  
Course Fee(s)
Course Fee non-credit $145.00