Module 1: Introduction to Artificial Intelligence

This module provides students with a basic overview and introduction to key concepts related to artificial intelligence. Students will be given a history of AI from the 1950s to today. Next, students will understand what AI is, what robotics is, how the two technologies are different, and how/where they overlap. Students will become familiar with terms such as machine learning, deep learning, and neural networks. The module will discuss The Turing Test and how it relates to AI. Students will also be introduced to theories of singularity. Finally, the module will conclude with an overview of what is to come in the course.

Module 2: Intelligence and Perception

Which is more intelligent, a human or a computer? This is not a new question. This module will explore how and why it is a complicated question. The module begins by exploring machine perception and how it differs from human perception. Next, it will differentiate between human intelligence and machine intelligence. Then students will understand the difference between artificial general intelligence and artificial narrow intelligence. The module will then present some of the limitations of machine perception. Finally, the module will examine the mechanics behind AI implementations such as picture/video recognition, and biometrics analysis.

Module 3: Algorithms in AI

This module provides a closer examination and understanding of algorithms. It begins by defining algorithms and decision tree algorithms. Students will then apply the knowledge to create a basic decision tree algorithm of their own. Next, students will understand how algorithms form the basis of AI. The module will then provide examples of algorithms that students interact with daily. Finally, it will conclude with a look at how AI and algorithms are used in the field of astronomy.

Module 4: Machine Learning

This module will explore the relationship between artificial intelligence and machine learning. First, it will examine what machine learning is. Then it will outline the four drives behind the emergence of machine learning that have enabled it to become a reality in today’s world. Next, the module will discuss machine learning training data and how it is used. Three different types of machine learning- supervised, unsupervised, and reinforcement- will be compared. Finally, the module will evaluate the use of AI and machine learning to generate movie and music recommendations.

Module 5: Deep Learning & Neural Networks

This module takes a closer look at deep learning and neural networks. It starts by defining deep learning. Next, it explains neural networks and what the components of a neural network are. Then the module will examine how deep learning will affect society and the economy. Finally, it evaluates how AI and deep learning create technology for self-driving cars.

Module 6: Humans and AI

We are experiencing a unique time in history. We are experiencing the dawn of an age where AI is all around us. The AI and Humans Module examines the ways humans already interact with AI. It will also explore design thinking and how it relates to AI. Next, the module will provide an overview of how AI can be used for social good. The current limitations of AI will also be discussed. Finally, the module will evaluate common AI uses such as personal assistants, chatbots, and language translators.

Module 7: Ethical AI and Bias

In this module, we explore the ethics and biases in AI creation and application. First, the module introduces the ethical challenges that Ai presents and defines what ethical criteria AI systems should be required to meet. Second, it pinpoints areas where AI can be particularly threatening including loss of privacy and mass surveillance. Next, the module discusses biases in AI systems- what causes them and why this is a problem. Then it examines diversity, why we need it in programming and how lack of diversity perpetuates biases. Finally, it evaluates the uses of AI in the U.S. criminal justice system.

Module 8: Writing a Pitch Deck

News headlines seem to focus on automation, robots, and AI taking away jobs. But is that the only side to the story? True, AI will continue to displace many workers as other technologies, outsourcing, and other trends have done in the past. While this issue should not be forgotten, on the other end there is a tremendous opportunity for young people to educate themselves on AI and prepare for jobs of the future in this dynamic field. This module discusses the skills and qualifications to secure a job in AI. Various career possibilities will be explored, and the module will conclude with an evaluation of AI’s use in healthcare diagnostics.

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Course Description:
This course teaches what every student should know about Artificial Intelligence. AI is a fast-moving technology with impacts and implications for both our individual lives and society as a whole. In this course, students will get a basic introduction to the building blocks and components of artificial intelligence, learning about concepts like algorithms, machine learning, and neural networks. Students will also explore how AI is already being used, and evaluate problem areas of AI, such as bias. The course also contains a balanced look at AI’s impact on existing jobs, as well as its potential to create new and exciting career fields in the future. Students will leave the course with a solid understanding of what AI is, how it works, areas of caution, and what they can do with the technology.