The Deep Learning Fundamentals Lab is an advanced learning opportunity designed to help you master the core concepts behind deep learning through two units of six hands-on projects each - ranging from using PyTorch to build models to applying CNNs to real-world problems. Applicants are expected to have the following prerequisite skills:
- Intermediate-level Python programming skills
- Understanding of basic calculus and linear algebra
- Some previous knowledge of Data Science (helpful, not required)
All applicants must pass an Admissions Quiz with a minimum passing score of 66%. Before you attempt the Admissions Quiz, we recommend that you use the following free resources to help you prepare:
- Python at LearnPython.org: Learn the Basics.
- Applied Data Science Lab: WQU’s own Applied Data Science Lab is free and always available. The Applied Data Science Lab teaches you the Python and Machine Learning skills needed to succeed in the Applied AI Lab.
- Linear Algebra from Khan Academy: study the mathematical foundation for key concepts in neural networks, data transformations, and optimization algorithms that power machine learning models.
- College Algebra: A full course with companion python code on YouTube.
- Mathematics for Machine Learning: A free eBook available online and as a PDF.
- Mathematics for Machine LearningPractical Deep Learning for Coders: A free course designed for people with some coding experience, who want to learn how to apply deep learning and machine learning to practical problems.