If you fail the Admissions Quiz for the Applied AI Lab, you’ll have a second chance to retake it after a 7-day waiting period. If you do not pass the Quiz on the second attempt, you may reapply to the Lab after a 6-month waiting period.

Please note that the Lab is intended for learners with these 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

The Applied AI Lab is structured around six hands-on projects, each to be completed in sequence. These projects address real-world challenges, such as wildlife conservation, crop disease monitoring, and traffic flow analysis, allowing students to apply their skills in impactful, practical contexts.

The Lab is self-paced, so there’s no fixed deadline to complete it. Most students finish within 100-150 hours. All project work is completed on virtual machines, enabling students to code alongside video lectures and engage with peers in collaborative forums.

The Applied AI Lab is an advanced learning opportunity designed to help you master the core concepts behind neural networks through six hands-on projects ranging from image classification to generative AI. 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

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.
• 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.

For administrative or technical questions about the Applied Data Science Lab at WorldQuant University, please visit our Help Center, where you can search for help articles covering a vast variety of topics. You can also use our chatbot by clicking on the icon in the bottom right corner of ourHelp Center,

The Applied Data Science Lab and the MScFE Program are independent offerings. Admissions for each are processed separately, and admission or completion of either the Lab or the MScFE does not guarantee admission into the other.

You are welcome to apply to the Applied Data Science Lab. For some students, the development of applied Python skills may be a very useful supplement to their MSc studies. Keep in mind that this Lab requires significant time investment in addition to your MScFE work. The Applied Data Science Lab does not award institutional credit.

Upon successful completion of the Applied Data Science Lab, students receive a digital badge via Credly, the digital credentialing leader.

Assignments are automatically evaluated, providing students with instant feedback and a score. Grading is on a pass/fail basis and all assignments must be completed to earn the credential.