Advanced Algorithms: Random Forest and Text Classification (M4/H3)
This course is for anyone who is in 8th grade or higher, who is familiar with AI basics and python or has taken AI basics (M1), Build and Tune AI Algorithms (M2) and Python with AI (PA1). AI Basics shows students what AI is and how to use it, while M2 introduces students to KNN and Linear Regression. In this class, students learn the internals of powerful AI algorithms in Decision Trees and Natural Language Processing (NLP). They learn how to tune these algorithms.
Suitable for:
• Students in grade 8 and above who are familiar with AI Basics.
• Or those who have taken AI Basics (M1) and Build and Tune AI Algorithms (M2).
Learn Artificial Intelligence - a new technology that is shaping our world!
Help your student discover a fascinating new world of technology - Artificial Intelligence (AI)! AI is changing the way we interact with the world, from virtual assistants like Siri and Alexa, to self-driving cars, to face recognition software.
Why learn AI?
AI is all around us! From self driving cars, to movie recommendations on Netflix, to Alexa, Siri or Google homes, we interact with AIs every day. Learn how they work, how they “think” and how you can build one of your own!
Parents - AI is a technology that is changing our lives and future careers. It is a great time to introduce your child to the field of Artificial Intelligence! In our innovative classes and camps - students learn the powerful technologies of Artificial Intelligence and Machine Learning in a fun and accessible way, and build working projects immediately. Most of our students want to learn more AI, programming and math even after finishing a class! Some have gone forward to win competitions! Spark a love of technology that will stay with them through college, powered by our comprehensive Elementary, Middle School and High School programs where they can continue to learn AI and Programming!
Kids - Would you like to teach an AI to play games like shooting targets or tic-tac-toe? Build fun AI apps that can predict your favorite book, favorite Pokemon, or sport? Are you passionate about solving problems in your community like improving recycling, helping the blind, or helping reduce bullying? All of these projects have been done by students who have learned AI! AI is powerful and easy to learn and can be used for all sorts of projects.
Why choose AIClub?
• Designed by AI experts with PhDs in Computer Science!
• These classes are the only ones where students get to build AIs from the very first class, which is precisely why they are so popular among students who love the opportunity to learn about and create these technologies!
We have no math or programming requirement. If they would like to code, they can do that also! Kids get interested and start building fun AI applications and also get motivated to learn programming, math and more STEM topics.
Please see our brochure for more info about our programs!
Description
This course enables students to learn an advanced Machine Learning algorithm called Random Forests, based on decision trees. AI Basics (M1) covered conceptual understanding and intuition behind regression and classification, while M2 introduces students to KNN and Linear Regression.
In this course we will extend to learning the Random Forest algorithm and exploring Text Classification using the TF-IDF Model, a subset of Natural language processing! We will learn how these algorithms work internally [their parameters], their advantages/disadvantages, and how to tune them to best adapt to the problem at hand. A final interesting aspect of this class is the topic of algorithmic fairness and bias we will discuss--important to be aware of in data ethics.
Topics, Tools, and Modules:
• Learn the concepts of decision trees
• Learn how Random Forest works and build it. Gain expertise on tuning the parameters that are used to deploy random forest models, i.e. number of trees and maximum depth.
• Learn the TF-IDF technique in Text Classification, a subset of NLP
• Learn more in depth how sentiment analysis works [i.e. decision boundary in classification]. This was first introduced in AI Basics (M1) as an introductory project.
• Discover what algorithmic fairness means.
• How can we quantify fairness? [Is it even possible to “measure” a term that is an ethics based concept]
• Understand the types of bias that can result when automated decision making is applied to real world data.
• As a culminating project + presentation, the students will build a custom project of their choice with their deeper level of understanding on algorithms! (*note - if they are interested in participating in a competition, they are welcome to bring their project in for this class)*
What Students Take Away
A working AI project (running application) that you can showcase and share.
• Training and AI and usage of advanced machine learning algorithms using powerful cloud tools.
• A cloud account that they can use to build new ML and AI applications using their laptops, tablets or other devices.
• An AIClub membership where they can access new projects, showcase their code, and participate in competitions. Completing the advanced course will equip them with the skills they need to develop and showcase more advanced projects, and compete in advanced competitions.
• Opportunities to compete and win in AI competitions. For more information on this, visit our Research Program.
• Certificate of Completion
Prerequisites
• Bring your own Laptop to class (online)
• AI basics class (M1) and Build and Tune AI Algorithms class (M2) (or) familiarity with AI Basics
• Basic python programming knowledge (or) Python with AI class (PA1)
Schedule
Duration: 6 weeks / 1.5 hours per session
We offer a range of dates and times to accommodate busy schedules.
Also - note that since we use entirely online tools, if a student must miss a class, it is easy for them to do the required work at home. We provide materials for missed classes and drop in times for students to come in for personal assistance on material covered in a missed class. We do ask however that the student attend the first and last class since this is needed for them to get oriented and also complete their custom project.