Jeremy Howard’s Fast.ai & Data Institute Certificates combine deeply practical AI education with a flexible, open-access learning model. Built around the acclaimed fast.ai courses, these certificates focus on teaching modern deep learning and machine learning through a top‑down, code‑first approach. Learners start by building real models for computer vision, NLP, tabular data, and recommender systems, then progressively deepen their understanding of theory and best practices. All course content is available online for free as high‑quality MOOCs, while in‑person certificate programs provide additional structure, mentorship, and peer learning for those who want more guidance and recognition. The curriculum emphasizes real‑world deployment, ethical considerations, and making state‑of‑the‑art AI accessible to developers, analysts, and domain experts—not just researchers. Fast.ai’s teaching philosophy is centered on removing unnecessary complexity, offering clear notebooks, practical case studies, and a strong open‑source ecosystem built around the fastai library and PyTorch. Whether you are transitioning into an AI career, upskilling as a software engineer, or applying machine learning in a specific industry, these certificates help you quickly move from zero to building production‑ready models. With an active global community and continuously updated materials, Fast.ai & Data Institute Certificates are a powerful pathway into applied AI and deep learning.
Career switch into applied AI or machine learning engineering by following the full certificate pathway and building a portfolio of end-to-end projects.
Upskill software engineers and data professionals who need to quickly learn modern deep learning techniques for computer vision, NLP, and tabular data.
Train internal teams in a company using the free MOOCs as a structured curriculum, then validate skills through selected in-person certificate cohorts.
Help domain experts in fields like finance, healthcare, or education prototype practical ML solutions without requiring a heavy math background.
Support educators and mentors who want a proven, open curriculum to teach deep learning with notebooks, assignments, and community resources.