A program curated for middle school students to learn the fundamentals of python and key concepts in machine learning and artificial intelligence. Work on hands-on group projects.
AI Trailblazers
A program curated for middle school students to learn the fundamentals of Python and key concepts in Machine Learning and Artificial Intelligence. Build real world AI models across fields!
AI Trailblazers
Program Structure
Weeks 1 & 2:
Build a foundation in AI & ML and learn about data analysis
Weeks 3 & 5:
Receive an introduction to key topics in AI - including exploratory data analysis, regression, and classification problems
Weeks 6 & 10:
Deep dive into some more complex topics which includes:
Image Classification
Neural Networks
Why AI Ethics Matter
Program Structure
Weeks 1 to 2:
Build a foundation in AI & ML and learn about data analysis
Weeks 3 to 5:
Receive an introduction to key topics in AI - including exploratory data analysis, regression, and classification problems
Weeks 6 to 10:
Image Classification
Neural Networks
Why AI Ethics Matter
Deep dive into some more complex topics which includes:
Program Details
This program is conducted entirely online!
-
25 hours over 10 weeks (weekends) OR 25 hours over 2 weeks (weekdays on summer break).
-
Section lectures for 1.5 hours and group session with a 5:1 student to mentor ratio for 1 hour (total: 2.5 hours per session)
-
None!
-
Grades 6-8
-
A group project with 3-4 other students
Here is the program brochure with more details!
Program Details
This program is conducted entirely online!
-
25 hours over 10 weeks (weekends) OR 25 hours over 2 weeks (weekdays during the summer).
-
Section lectures for 1.5 hours and group session with a 5:1 student to mentor ratio for 1 hour (total: 2.5 hours per session)
-
None!
-
Grades 6-8
-
A group project with 3-5 other students.
Here is the program brochure with more details!
AI Trailblazers Course Syllabus
Session 1Session 2Session 3Session 4Session 5Session 6Session 7Session 8Session 9Session 10Lecture 1: TheoryIntroduction to AI and MLExploratory Data Analysis (EDA)Data, Regression Problems, Linear RegressionMultiple RegressionClassification Problems, Logistic RegressionIntroduction to Neural Networks (NNs)Tuning Neural NetworksIntroduction to Convolutional Neural Networks (CNNs)AI EthicsProject: Presentation PracticeLecture 2: Interactive CodingIntro to Python & Basic ProgrammingIntro to Python & Basic ProgrammingEDALinear Regression and Multiple RegressionLogistic RegressionNeural NetworksMore Practice with Neural NetworksCNNsProject: Model EvaluationPresentation and Closing CeremonyHands-on Session: Small GroupHands-on workHands-on workHands-on workHands-on workHands-on workProject: Research Question and EDA!Project: Model TrainingProject: Model TrainingProject: Presentation PrepFeedback Discussion
