Our Labs are flexible, and you can take them in any order based on your prior knowledge and goals.

That said, we recommend starting with the Applied Data Science Lab to build a strong foundation in working with data, learning how to clean, analyze, and model it to solve real-world problems. From there, the Deep Learning Fundamentals Lab helps you move beyond traditional machine learning and understand how neural networks uncover more complex patterns automatically. The Computer Vision Lab is best approached as a final step, where you apply those deep learning techniques to image and video data in more advanced, real-world scenarios.

While each Lab can be taken on its own, following this sequence offers a clearer and more cohesive progression from core data skills to more advanced AI applications.

No, our Labs are not-for-credit, but you will receive shareable Credly badges and certificates upon successful completion.

No, our Labs are hands-on continuing education opportunities that do not require a prior degree.

Students are automatically withdrawn from their Lab if they are inactive for 120 consecutive days.

If you have been withdrawn from the Lab, you can reactivate your enrollment by navigating to your My Courses page and clicking "REACTIVATE YOUR ENROLLMENT".

Once reactivated, you'll be able to continue from where you had left off. 
 

While it is possible to take more than one Lab at the same time, it is not generally recommended.

Our Labs are designed as a flexible, project-based pathway that supports learners at different stages of technical maturity. For most learners, it is more effective to focus on one Lab at a time, starting with the one that best aligns with their current skills and professional goals before moving on to the next.

Many learners begin with the Applied Data Science Lab, where they build a strong foundation in working with structured data, learning how to access, clean, and analyze datasets, develop machine learning models, and communicate insights that drive real-world decisions. From there, the Deep Learning Fundamentals Lab helps learners move beyond traditional machine learning into neural networks, where models automatically learn complex patterns from data. The Computer Vision Lab is typically the most advanced step, applying deep learning techniques to image and video data in more sophisticated, real-world scenarios.

The Lab projects build on one another and were designed to be completed one project at a time in a prescribed sequence. Once you reach the passing threshold the “Complete Course” button will be enabled in the left navigation of your course. You can either select “Complete Course” and move on to the next project, or continue completing more tasks until you are ready to move on or reach 100% completion.

Upon successful Project completion, you will be eligible to register for the following Project in the sequence.
Registration does not occur automatically. Rather, you are expected to navigate to My Courses > Register after each successful project completion.

Congratulations! You are ready to dive into your first Lab Project. To get started, log into the WQU Learning Platform, navigate to My Courses via the top navigation, and click on "Register".

From here, you'll be able to enroll in Project 1. After completing your first Project, you'll follow this same process to register for each subsequent Project.

Great work! You're just a few steps away from diving into your first project in the Lab:

• Complete your Student Profile;
• Sign the User Agreement;
• Take the mandatory Orientation Course;
• Register for Project 1.

Once you have completed your profile and signed the User Agreement, you will be automatically enrolled in a mandatory Orientation Course, which can be accessed via My Courses in the top navigation of the WQU Learning Platform.

From walking you through the Lab’s structure to helping you navigate our Learning Platform and virtual machines, the Orientation Course takes about 1 hour to complete and covers everything you need to know to set you up for success.

Upon successful completion of the Orientation Course, course registration will NOT occur automatically. Instead, you are responsible to register for each of your Projects by navigating to My Courses and "Register".

Before you can start your Lab, you will need to take an Admissions Assessment. We want to make sure you have a solid foundation on which you can build the skills we teach in our program. Information on the number of questions in the Assessment, the time to completion, and the passing grade will be provided within the Admissions Assessment page.

We ask that you not use supplementary materials to ensure you are measuring your actual individual skills. You will need to close your textbooks and any other browser windows. We recommend that you have a pencil and paper ready in case you want to write out a problem.

To prepare for the Admissions Assessment, and/or to build your skills and knowledge to successfully complete the lab you chose, use the study materials suggested below:

Data Science Lab Admissions Assessment Study materials
Deep Learning Fundamentals Lab Admissions Assessment Study materials
Computer Vision Lab Admissions Assessment Study materials