UC Berkeley launches new AI master’s program in fall 2027

Starting in fall 2027, the University of California, Berkeley will welcome the first students into its new Master of Artificial Intelligence and Machine Learning program. The full-time degree, completed over two semesters on the Berkeley campus, integrates core coursework with a Silicon Valley immersion experience designed to bridge theory and practice.

Jennifer Chayes, dean of the UC Berkeley College of Computing, Data Science, and Society, stated that the Master’s in Artificial Intelligence and Machine Learning degree creates an opportunity for students to receive rigorous AI training in an ecosystem that supports innovation. Applications for the program open September 24, 2026.

MAIML Program Details: Curriculum, Faculty, and Completion Requirements

This intensive program, delivered entirely on the UC Berkeley campus, requires completion of core courses spanning data science, probability, and AI ethics, alongside specialized electives chosen by each student. To earn the degree, candidates must also pass a comprehensive examination designed to assess mastery of the field’s statistical and computational foundations.

With the introduction of the Master’s in Artificial Intelligence and Machine Learning degree, UC Berkeley is creating a unique opportunity for students to receive rigorous AI training in an ecosystem that champions transformation.

Jennifer Chayes, CDSS dean
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With a keen intuition for emerging technologies, The Neuron brings over 5 years of deep expertise to the AI conversation. Coming from roots in software engineering, they've witnessed firsthand the transformation from traditional computing paradigms to today's ML-powered landscape. Their hands-on experience implementing neural networks and deep learning systems for Fortune 500 companies has provided unique insights that few tech writers possess. From developing recommendation engines that drive billions in revenue to optimizing computer vision systems for manufacturing giants, The Neuron doesn't just write about machine learning—they've shaped its real-world applications across industries. Having built real systems that are used across the globe by millions of users, that deep technological bases helps me write about the technologies of the future and current. Whether that is AI or Quantum Computing.

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