FAQ

Start with Foundations of Neural Networks if you want a conceptual base (matrices, gradients, loss functions). If you already know Python and linear algebra, jump into the PyTorch Bootcamp and build working models from day one.

Yes. Completion certificates become available after you pass the final assessment and meet the minimum project requirements. Certificates are downloadable as a PDF and include your name and course title.

We offer a 14-day refund window if you haven’t completed more than 20% of the course content. Refunds are processed to the original payment method and typically settle in 3–10 business days depending on your bank.

Yes. We support team enrollments with group dashboards, progress tracking, and invoice-based billing for 5+ seats. Use the “Ask a question” form to request a quote and include your team size and goals.

Examples use Python + PyTorch, with practical patterns you can transfer to other frameworks. For deployment modules we cover fundamentals (export, batching, latency, monitoring) without locking you into a single platform.

You get 12 months of access by default, including updates released during your access window. If a course becomes significantly expanded, enrolled learners receive the updated modules automatically.

Not for the fundamentals. Most labs run on CPU with small datasets. For advanced projects (vision and transformer fine-tuning), we provide guidance for using common cloud GPU options and optimizing batch sizes to fit your hardware.

Use this page’s “Ask a question” form and include: course name, lesson name, error message, and what you tried. If you share code, paste the smallest reproducible snippet (removing keys/secrets).