Learn the fundamentals of artificial intelligence and machine learning.
Build a strong foundation through real-world group projects.
AI Scholars
Learn the fundamentals of Python and key concepts in Machine Learning and Artificial Intelligence. Build a strong foundation to code and create AI models independently!
AI Scholars
Program Structure
Weeks 1 & 2:
Build a foundation in Python applied to AI and understand how to execute a data science project
Weeks 3 & 5:
Receive an introduction to key topics in AI - including regression, neural networks, and natural language processing
Weeks 6 & 10:
Deep dive into some more complex topics which includes:
Image Classification
Neural Networks
Deep Learning
NLP & Language Processing
Sentiment Analysis
Why AI Ethics Matterics Matter
We also give you a chance to explore AI in the fields of academic research and understand how you can use your AI experiences in your college applications.
Program Structure
Weeks 1 to 2:
Build a foundation in python and AI and learn how to execute a data science project.
Weeks 3 to 5:
Receive an introduction to key topics in AI - including regression, neural networks, and natural language processing
Weeks 6 to 10:
Image Classification
Neural Networks
Deep Learning
NLP & Language Processing
Sentiment Analysis
Why AI Ethics Matter
Deep dive into some complex topics including:
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 9-12, with exceptions for students in middle school with a coding background.
-
A group project with 3-4 other students.
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 9-12, with exceptions for students in middle school with a coding background.
-
A group project with 3-5 other students
Here is our program brochure for more details!
AI SCHOLAR PROGRAM
Session 1Session 2Session 3Session 4Session 5Session 6Session 7Session 8Session 9Session 10Lecture 1: TheoryIntro to Data Science & Exploratory Data Analysis (EDA)Linear Regression, Training/ TestingPolynomial Regression, Overfitting, and TuningLogistic RegressionFundamentals in Neural Networks (Regression)Tuning Neural Networks (Classification)Convolutional Neural Networks (CNNs)Tools for Improving CNNs: Regularization and Transfer LearningEthics in AIProject workLecture 2: Code Walk-ThroughIntro to Python & Basic ProgrammingEDA, Train/Test Split, Linear RegressionPolynomial Regression, Tuning a ModelLogistic Regression & Multiple Logistic RegressionIntroduction of Tensorflow Keras and Neural NetworksTuning NNs, Using NNs for classification, Validation SetsImage Classification with CNNsAdvanced Topics in Image Classification: Using VGG16Project workPresentationsHands-on Session: Small GroupHands-on workHands-on workHands-on workHands-on workHands-on workProject: Start Projects with EDA!Project: Baseline ModelProject: Advanced Model (Upgrade from Baseline)Project workClosing Ceremony