📢 Calling all student leaders fascinated by the power of artificial intelligence
We are looking for student leaders interested in starting an AI club at their school. Club leadership is the perfect way to explore the exciting world of AI and machine learning (and boost your resume ☺️). With Strive’s support, you'll have access to all the resources you need to get started. Our team can provide curriculum to enable you to go deeper into your interests, make connections to industry professionals, and help to organize events.
Whether you're a coding newbie or a seasoned programmer, an AI club can be a space to help you discover the endless possibilities of AI. We believe in you and want to support your dreams to start the AI Club at your school!
Here are some resources you can use to get started:
Here is a starter pitch deck you can use to get buy-in to bring the AI club to your campus. (click on the link to edit for your campus).
Use this link to customize the Club Description for your campus including your own contact info and meeting times in Canva.
Session 1: Introduction to AI and Generative Art
- Define AI and its various applications, with a focus on generative AI tools
- Discuss the history of generative AI and its evolution over time
- Introduce basic AI concepts such as machine learning, neural networks, and deep learning in the context of generative AI art
- Show examples of generative art created using AI
Session 2: Machine Learning Basics for Generative AI Art
- Define machine learning and its types, with a focus on generative models
- Explain the difference between supervised, unsupervised, and reinforcement learning for generative AI
- Introduce basic machine learning algorithms such as decision trees and k-means clustering for generative AI art
- Show examples of generative art created using decision trees and k-means clustering
Session 3: Pixel Art with Neural Style Transfer
- Introduce the concept of neural style transfer for generative AI art
- Teach students how to use a pre-trained neural style transfer model to create pixel art
- Have students create their own pixel art using neural style transfer
Session 4: Artistic Style Transfer with GANs
- Define GANs and their basic structure
- Discuss the concept of generator and discriminator networks in GANs
- Introduce GAN training techniques and applications for generative AI art
- Have students use a pre-trained GAN model to create their own art using artistic style transfer
Session 5: Chatbots with NLG
- Define natural language generation (NLG) and its applications in chatbots
- Introduce the concept of transformers for NLG
- Teach students how to use a pre-trained transformer model to create a chatbot
- Have students create their own chatbot using NLG
Session 6: Storytelling with RNNs
- Define RNNs and their basic structure
- Discuss the concept of recurrent connections in RNNs
- Introduce RNN training techniques and applications for generative AI storytelling
- Have students use a pre-trained RNN model to create their own stories
Session 7: Music Generation with VAEs
- Define VAEs and their basic structure
- Discuss the concept of encoder and decoder networks in VAEs
- Introduce VAE training techniques and applications for generative AI music
- Have students use a pre-trained VAE model to create their own music
Session 8: Generative AI Applications in Games
- Discuss the various types of games that use generative AI, such as procedural content generation and AI opponents
- Introduce real-world generative AI applications in games
- Have students brainstorm and design their own game that uses generative AI
Session 9: Generative AI Development Tools and Resources
- Introduce the various tools and resources available for generative AI development, such as libraries and pre-trained models
- Discuss how to access and use these tools
- Have students explore and experiment with different generative AI development tools
Session 10: Final Project and Showcase
- Students will work on a final generative AI project of their choice using the skills and knowledge they have gained throughout the program
- Have students showcase their projects to the group and discuss what they have learned
- Wrap-up the program with a discussion of future opportunities in generative AI and potential career paths in the field