The Computer Vision Lab is an advanced specialization designed for learners and practitioners who have a foundation in deep learning and neural networks and are ready to apply their existing knowledge to complex, real-world problems involving image and video data. Applicants are expected to have the following prerequisite skills:
Intermediate-level Python programming
Ability to manipulate basic data structures like lists and dictionaries, and write definitions for functions and classes
Familiarity with essential machine learning concepts, including supervised and unsupervised learning, overfitting and regularization, and training, validation, and test sets
Before you attempt the Admissions Assessment, 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 Computer Vision Lab.
Deep Learning Fundamentals Lab: WQU’s free Deep Learning Fundamentals Lab equips you with the core deep learning skills needed to progress into AI specializations such as Computer Vision. It is highly recommended for anyone looking to build a strong foundation in deep learning before advancing to more specialized applications.
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.
Practical 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.