Introduction To Artificial Intelligence
Course Level: Beginner-Intermediate
Instructor | Teacher Assistant | Google Classroom |
---|---|---|
Dominic Huang | Chenyue Zhou | texa2qu |
Course Description
Even with prior programming experience, it may seem daunting to branch out into the field of artificial intelligence. This course introduces and thoroughly explains these concepts in a completely beginner-friendly fashion without wasting time, via both a visual and programmatic approach. The course covers many applications of AI, from search algorithms, neural networks, and more!
Who Is This Course For?
This course is best suited for 5th-10th grade students. It is targeted towards students with at least beginner-level coding profieincy. See course prerequisites for more information.
Course Prerequisites
- Prior coding experience is strongly recommended, preferably in Python
- You should be able to read Python code. Although you do not necessarily need to know Python to learn the concepts from this course, demonstrations will be done in Python, which will not be covered in this course
Course Dates
This course runs for 5 weeks weekly, starting on Saturday, July 13, and ending on Saturday, August 10. Classes are held online from 9-10am via Zoom.
Class Times (PST)
TBA
Syllabus
Lesson 1: Search Algorithms
In this lesson, we will briefly explain what AI actually is and will cover the basics of search alogorithms. Students will learn how to use AI to navigate mazes, as well as potential challenges the AI might face.
Lesson 2: Classification
Machine learning is one of the most powerful ways to train an AI. Students will learn how to classify given input into various labels through AI.
Lesson 3: Prediction
Students will delve further into the realm of machine learning to tackle problems involving AI predictions. Students will also learn how to measure the effectiveness of their AI algorithms and how to mimimize loss.
Lesson 4: Neural Networks
This lesson introduces one of the most powerful algorithims in AI- the neural network. Students will be introduced to the structure of neural networks and learn how they are trained.
Lesson 5: Optimization
Students will learn the importance of optimizing their AI algorithims and the potential challenges that may come with the risk of overfitting. They will be introduced to convolutional neural networks, a special type of neural network designed for image recognition.