Come Join us for our 2-day virtual workshop titled Friendly Bots: Exploring Machine Learning on Saturday, October 19th and October 26th, 2024, for girls (ages 8 – 12 & 13-17).
This workshop is designed to guide learners through the fascinating world of machine learning, with a focus on how bots and algorithms can help solve problems by learning from data. Throughout this session, learners will engage with interactive activities, practical coding exercises, and collaborative projects to gain a foundational understanding of machine learning. By the end of the workshop, participants will have learned how to apply these concepts to create their own friendly bots using machine learning.
Materials Required
- Computing Device: A laptop or desktop computer with internet access.
- Code.org Accounts: Instructors will create and manage accounts on Code.org for learners to engage with interactive coding exercises.
- Learning Resources: All necessary learning resources, including instructional materials, sample datasets, and coding templates, will be provided during the workshop.
Learning Outcomes
1.Understand the Basics of Machine Learning:
-Define what machine learning is and how it is used in creating bots.
-Differentiate between various types of machine learning: supervised, unsupervised, and reinforcement learning.
2.Engage in Practical Coding Exercises:
-Create simple algorithms to train bots using Code.org.
-Explore how datasets are used to improve bot decision-making.
3.Apply Machine Learning to Real-World Problems:
-Identify potential uses of friendly bots across different industries and scenarios.
-Develop small projects that utilize machine learning to solve real-world challenges through friendly bots.
4.Collaborate and Share Learning:
-Work in groups to create and improve machine learning-based bots.
-Present the friendly bot projects to peers and share insights gained through collaboration.
Advanced Path
This path is for our returning coders or those looking for a challenge. In this advanced section, we will dive deeper into machine learning by focusing on building more complex models. It is perfect for those ready to expand their machine learning skills and apply them to more sophisticated real-world problems.
