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.