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AI Explorers: Middle School Edition

Hey Middle Schoolers! Are you ready to become a tech wizard? Join our thrilling AI Explorers course, where you'll unlock the mysteries of Artificial Intelligence (AI) and learn how it's changing the world around us!

Why Join AI Explorers?

Super Fun Learning: Say goodbye to boring lectures! Our classes are jam-packed with cool activities, games, and challenges.

Learn the Jargon: We explain tricky AI concepts in a way that's super easy to understand.

Create Your Own AI: Build and train your own models - it's like having a robot friend who learns from you!

Be a Game Maker: Use your AI models to create awesome games that you can play and share with friends.

Your Mission, Should You Choose to Accept It:

Decode the Language of AI: Learn what AI is, how it works, and why it's super important.

Meet the AI Family: Discover different types of AI, from chatbots to self-driving cars.

Become an AI Inventor: Get hands-on with tools that let you train AI models without writing any code.

Showcase Your Creations: Impress your friends and family by showcasing the AI projects and games you've created.

Course Details:

Duration: 12 weeks, 1 session per week
Skill Level: Beginners - no prior experience necessary!
Tools: Safe, student-friendly AI platforms

The class is structured into twelve lessons.

Lesson 1 - Introduction to AI and Ethical Considerations provides an overview of artificial intelligence (AI) and its practical applications. It explains that AI is about making machines think and act like humans and gives examples such as voice recognition and self-driving cars. The lesson also explores the benefits and drawbacks of AI. It emphasizes the need for responsible AI usage, as AI lacks human emotions and common sense. The lesson highlights the advantages of AI, such as increased efficiency and personalized services, but also acknowledges concerns like job automation and privacy. Students learn about the importance of ethical considerations when using AI.

Lesson 2 - Using AI - Language Model introduces generative AI and AI language models. These models learn from large amounts of text data and can generate new text based on what they have learned. An example is GPT-3, which can create original stories based on given prompts. Students learn about the capabilities and applications of AI language models in generating text.

Lesson 3 - Using AI - Image Model explores AI image generation models and their applications. These models learn to create new images by training on examples and can also transform images. They have various uses, such as creating characters for entertainment, aiding architects, and assisting doctors. However, the lesson also addresses the potential misuse of this technology, such as in deepfakes, emphasizing the importance of responsible usage and ethical considerations.

Lesson 4 - Prompt Engineering introduces the concept of prompts in AI. Similar to asking a question or giving instructions to a friend, prompts are used to communicate with AI and guide its actions or responses. Students learn how to effectively use prompts to achieve desired outcomes when interacting with AI systems.

Lesson 5 - Creating Images with AI.Artificial Intelligence (AI) has made it easier than ever to create images that are stunning and visually compelling. By using AI tools, it's possible to generate images without the need for any artistic skill and in a fraction of the time that it would take to produce them manually.

Lesson 6 - Supervised Learning vs. Unsupervised Learning Supervised Learning is a type of machine learning that is a subset of AI. This is the process of teaching the AI model a new skill. It is supervised because a human is involved in the process: they label the dataset. The model then learns from the labels and eventually can identify the data without the label. Unsupervised Learning is another way to train a model using datasets. However, this method does not involve labeling of datasets. Instead, the model tries to organize and find patterns in the data by itself. It looks for similarities and other relationships between the data.

Lesson 7 - Reinforcement Learning. Reinforcement Learning is a training method that provides feedback to the AI model to encourage or discourage its actions. For this method, the AI model is called an agent, and the system providing feedback is the environment. The environment rewards the agent with positive points when it performs well and negative points when the agent performs poorly.

Lesson 8 - Neural Networks. Neural Networks are made of layers of nodes, which are processing blocks inspired by the neurons in the human brain. Like our brains, the layers of nodes process information by finding patterns and connections in the data.

Lesson 9 – How Generative AI Works. Generative AI is the field of AI that builds models that will generate creative output, such as stories, music, or art. There are two common techniques used in Generative AI systems: GANs and VAEs. Generative AI is used in the creative fields as inspiration or a starting point in a longer process.

Lesson 10 - Training a Model. In this lesson, the students will get to train a model themselves. First, we’ll go over datasets, and then we’ll explain how the training application works. The training application will use images of objects or poses to train the model on how to identify those objects or poses. Later in the project lessons, lessons 14- 16, students will learn how to use their models with CodeMonkey to create games.

Lessons 11 and 12 - AI Game Project. Students learn how to use an image model that they train in a game. The lesson steps them through the process of invoking the training application from within CodeMonkey’s Create Games activity. Once they train their model, they use the model in a game that they create.

Enrichment and tutoring in Math and Computing for any student who wants to learn.
Led by Ana Nora Evans in Charlottesville, Virginia.

Blue Ridge Boost
2171 Ivy Road
Charlottesville, Virginia 22902
Email: nora@blueridgeboost.com
Phone: ‪(434) 260-0636