Daniel Bourke
Also known as Zero to Mastery, machine learning education
Daniel Bourke teaches machine learning through courses, public videos, notebooks, and projects. He also helps evaluate models as a Member of Technical Staff at Artificial Analysis. He began a self-directed AI study programme in 2017 and later worked as an ML engineer at Max Kelsen. In 2019, he started working for himself. His Zero to Mastery courses cover several model libraries, including PyTorch and Hugging Face. The open PyTorch course includes exercises and worked notebooks, while his Hugging Face site covers later lessons on classification, detection, and language model fine-tuning. His teaching centres on code, experiments, and complete application tasks.
- Now at
- Artificial Analysis
Timeline
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2017
Beginning a self-directed AI course
Bourke began teaching himself to code in 2017 with a focus on AI and machine learning. He created his own study programme, which was not a university degree.
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Before independent teaching
Working as an ML engineer
Bourke worked as a machine learning engineer at Max Kelsen after jobs in fitness, Apple support, and driving. He says he left the workforce to work for himself in 2019. His path moved from learning to professional practice and public teaching.
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Independent course work
Teaching through full projects
At Zero to Mastery, Bourke teaches machine learning, TensorFlow, PyTorch, and Hugging Face. The material uses code and practical projects. It connects a learner’s first model with the work required to inspect data, train a system, and examine the result.
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By April 2023
An open PyTorch learning resource
Learn PyTorch for Deep Learning supplies an online book, notebooks, exercises, and long videos. The course received an April 2023 update for PyTorch 2.0. The course moves through model construction, training, experiments, and deployment, giving learners material they can read and run.
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2024–2026
Extending lessons to Hugging Face
His Hugging Face learning site added text classification lessons in 2024 and object detection work in 2025. Videos for an LLM fine-tuning course became available in June 2026. His teaching expands from basic model work into modern model libraries and adaptation.
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Current public work
Teaching and model evaluation
Bourke currently works as a Member of Technical Staff at Artificial Analysis, helping evaluate models. His projects include Nutrify and his continuing courses. His work combines learner material, applied software, and model evaluation.
Sources and credits
Photo: Daniel Bourke / GitHub profile. License: Not stated by source. Source: github.com. Cropped to a square and resized. Ask us to remove or replace this photo.