Frequently Asked Questions
What are the prerequisites?
Comfort with Python, basic linear algebra, and experience training a model with a deep learning framework (PyTorch or TensorFlow). Beginners can start with our Foundations track.
How much time should I budget?
Most courses require 5–8 hours weekly. Live cohorts include optional office hours and peer review time.
Do I need a GPU?
A GPU accelerates training, but we provide CPU-friendly exercises and hosted notebooks where relevant. For advanced vision or transformer modules, a mid-range GPU is recommended.
Are there certificates?
Yes. We issue verifiable certificates upon successful completion of projects and reviews. Certificates reflect demonstrated skills, not mere attendance.
What support will I receive?
You get Q&A forums, curated references, mentor office hours, and structured feedback on projects. Our editorial edits improve your reasoning memos.
Can my company sponsor a team?
Yes. We run enterprise cohorts with custom evaluation datasets and internal review processes. Contact us to design a program.
What is your refund policy?
If you withdraw within the first 7 days of a course, we issue a full refund. After that window, partial refunds are considered for special circumstances.
Which tools and frameworks are used?
Primarily PyTorch, with tooling around Weights & Biases or MLflow, and standard libraries for data processing and evaluation. We favor open-source, reproducible stacks.