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Courses

Sometimes you need a helping hand when navigating through a topic as large and complex as AI. At SAILea, we offer live courses over Zoom through our partnership with the East AI-CS Club to advance your knowledge on both computer science and artificial intelligence. You must be a member of SAILea or a SAILea club to participate in our courses. If you are not yet a member, it's easy and free to join. Just visit the "Join Us" page and fill out the form at the bottom.

PROGRAMMING COURSES

We know that a certain level of fluency in a programming langauge is necessary to learn AI or ML effectively and that there are many students who did not yet have an opportunity to learn a programming language. Here are a list of live courses on programming languages we offer:

Python

Python is a popular programming language with a heavy emphasis on the readability of the code. Because of python's extensive built-in library, it is perfect for any newcomers to coding. Python is one of the most commonly used programing languages for creating AI. Our course will take you from little Python knowledge to being ready to code your own AI.

Java

Java is also one of the most popular general-purpose programming language that is built to be object oriented. Applications of Java not only includes machine learning, but also perfect for coding robots and programming games. Our Java course will cover data types, iteration, conditionals, arrays, objects, methods, recursion, and more.

ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING COURSES

Mathematics Behind Deep Learning

This course is part 1 in the deep learning series. You will be focusing on mathematics behind deep learning. You will be taught conceptual models of deep learning and learn what is going behind the scene by learning the necessary linear algebra and calculus.

Principles of Machine Learning and Deep Learning

Our curriculum starts with an immersive dive into supervised, unsupervised, and reinforcement learning techniques. You'll develop a comprehensive understanding of regression, classification, and practical machine-learning applications. Hands-on learning with tools like sklearn, numpy, and pandas brings concepts to life. Topics include decision trees, random forests, linear and logistic regression models, and K-means clustering.

Current course schedule:

January 20th, 7-8 p.m. EST

February 10th, 7-8 p.m. EST

February 24th, 7-8 p.m. EST

March 16th, 7-8 p.m. EDT

March 23rd, 7-8 p.m. EDT

April 6, 7-8 p.m. EDT

April 20, 7-8 p.m. EDT

To sign up for upcoming live courses or videos of those courses, please fill out this form:

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