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UC Berkeley's Master of Information and Data Science (MIDS) online

UC Berkeley's Master of Information and Data Science (MIDS) online

UC Berkeley’s online Master of Information and Data Science program prepares learners to become data-driven leaders.

No. 1

Ranked Online Master's in Data Science by Fortune Magazine.Footnote 1

Complete in 12–32 months

Set a course load that accommodates your professional and personal commitments.

About the program

  • Flexible program paths:

    Designed for working professionals, this 27-unit, online program can be completed on one of three paths: accelerated, standard, or decelerated.

  • No GMAT/GRE required:

    Applicants are reviewed holistically, with consideration given to an individual’s broader characteristics, attributes, and goals.

  • Gain in-demand skills:

    Top companies like Amazon, Apple, Meta, Microsoft, and Google are seeking candidates with data science experience.

About UC Berkeley School of Information      

UC Berkeley School of Information is a vibrant community of scholars, practitioners, and students who are committed to expanding access to information for all. Since 2014, the I School has offered online programs to develop data-driven leaders who want to solve current and emerging information problems.

Tuition and fees

Tuition and feesTuition cost$81,806

Tuition and fees are subject to change and may increase each academic year. Tuition does not include student fees, technology platform licensing, or support services. Learners are also responsible for travel and accommodation costs related to any in-person immersions or residentials.

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Featured courses

Designed to develop forward-thinking leaders in data science, the MIDS program features a multidisciplinary curriculum that prepares you to become a decision-maker with a comprehensive understanding of how to derive insights from real-world data sets. Courses focused on programming, such as those featured below, are completed alongside courses that explore the ethical impact of data science and how to effectively communicate results.

  • Applied Machine Learning:

    Learn how to apply crucial machine learning techniques to solve problems, run evaluations, and interpret results, and understand scaling up from thousands of data points to billions.

  • Behind the Data: Humans and Values:

    Examine the legal, policy, and ethical issues that arise throughout the full life cycle of data science. Case studies will be used to explore these issues across various domains such as criminal justice, national security, health, marketing, politics, education, and employment.

  • Natural Language Processing with Deep Learning:

    Gain a broad introduction to linguistic phenomena and our attempts to analyze them with machine learning. We cover a wide range of concepts, with a focus on practical applications such as information extraction, machine translation, sentiment analysis, and summarization.

Admissions

UC Berkeley seeks candidates who want to make a positive impact on the I School community and the world. In addition to holding a bachelor’s degree, you will need to submit electronic copies of the following as part of your application:

  • Official transcripts

  • Statement of purpose and additional admissions statements

  • Two professional letters of recommendation

  • Current resume

In-person immersions

Frequently asked questions

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