What are WQU Labs?

WQU Labs are free, self-paced, project-based applied certificates in data science and AI. There are four Labs: the Data Foundations Lab, the Data Science Lab, the Deep Learning Fundamentals Lab, and the Computer Vision Lab. Each stands on its own, and together they form a pathway from applied work with real-world data to specialized AI skills.

How Labs work
Every Lab is self-paced, with no cohorts, deadlines, or scheduled sessions, and free to enroll in and complete. Instead of lectures and exams, you learn through applied projects, each centered on a real dataset and a practical problem. Labs run online on cloud-based virtual machines, so there's nothing to install. You earn a shareable Credly badge as you complete each unit, and a certificate when you complete the full Lab.

Lab	What you'll build	Projects	Badges and certificate
Data Foundations Lab	Reliable data preparation: wrangling messy, real-world data, assessing its quality, and building tested, reproducible data pipelines	8, in two units of 4	A Credly badge for each unit, plus a certificate on completion
Data Science Lab	End-to-end machine learning projects, from accessing data through SQL, NoSQL, and APIs to building regression, classification, and clustering models	8, in two units of 4	Data Science Modeling badge (projects 1 to 4), Data Science Applications badge (projects 5 to 8), plus a certificate
Deep Learning Fundamentals Lab	Neural networks built and trained in PyTorch, including convolutional neural networks, using datasets from health, science, and engineering	12, in two units of 6	A Credly badge for each unit, plus a certificate on completion
Computer Vision Lab	Custom computer vision models for tasks like image classification and object detection, using techniques such as transfer learning	6	Credly badges and a certificate on completion

Independent certificates, connected pathway

Every Lab is a complete applied certificate in its own right, so you can take one to fill a specific skills gap or stop after any Lab and return later. Your badges and certificates are yours to share as soon as you earn them.
Taken in order, the Labs also form WQU's Lab Pathway, with each Lab building on the one before: prepare and validate data in the Data Foundations Lab, model it in the Data Science Lab, build neural networks in the Deep Learning Fundamentals Lab, and apply them to images in the Computer Vision Lab.

Choosing where to start

You can enter the pathway at whichever Lab matches your current skills. If you have foundational Python and statistics knowledge and are ready to apply it to real-world data, start with the Data Foundations Lab. If you can already prepare and validate real-world data and want to build machine learning models, start with the Data Science Lab. Learners with some machine learning experience who want to learn neural networks can begin with the Deep Learning Fundamentals Lab, and those who can already build and train deep learning models in PyTorch are ready for the Computer Vision Lab. If you're unsure, start one step earlier than you think you need.

How Labs differ from Graduate Programs

WQU offers two distinct types of learning. Graduate Programs, including the MSc in Financial Engineering, the MSc in Strategic AI and Innovation, and the Graduate Certificate in Applied AI Fundamentals, are tuition-free, DEAC-accredited, and for credit. They're delivered as cohort-based, structured online programs with a global community of peers and lead to a graduate degree or graduate certificate. Labs are free, not for credit, and you complete them independently to earn Credly badges and a Lab certificate. Labs do not count toward a degree and there is no formal pathway from Labs into a Graduate Program. Admission to each Graduate Program is a separate process with its own requirements.