UC Berkeley’s Online Master of Information and Data Science (MIDS)
Gain the technical expertise and creative problem-solving skills to drive innovation in an AI-powered world — without leaving the workforce.
- #1-ranked: Earn your degree in an online data science program ranked #1 by Fortune Education in 2025.1
- By leaders, for leaders: Learn from innovators, entrepreneurs, researchers, educators, and technology leaders working at the cutting edge of industry.
- Four optional focus areas: Choose from:
- Applied AI and Advanced Machine Learning Systems
- Data Engineering and Production Systems
- Applied Statistics and Decision Science
- Technology Leadership and Strategy
The Online Master of Information and Data Science (MIDS) curriculum is holistic and interdisciplinary, preparing graduates to integrate perspectives from computer science, artificial intelligence, statistics, the social sciences, and organizational leadership to solve complex, real-world problems.
Which Online Master’s in Data Science Pathway is Right for You?
The 27-unit online program is designed for working professionals and can be completed through one of three flexible pathways.*
| Program Path | Course Load | Time to Complete | Best Suited For |
|---|---|---|---|
Accelerated | 3 courses per semester | As few as 12 months | Students able to manage a rigorous full-time schedule |
Standard | 2 courses per semester | Approximately 20 months | Working professionals balancing career and study |
Decelerated | 1 course per semester (after first term) | Up to 32 months | Students seeking maximum flexibility |
*Students pursuing accelerated or decelerated pathways require approval from UC Berkeley.
How Do MIDS Admissions Work?
We offer three program start dates per year (January, May, and August) with applications reviewed on a rolling basis.
The School of Information seeks MIDS applicants with strong quantitative and analytical skills who are ambitious and enthusiastic about the future of data science.
A complete application must include the following:
- Online application
- Proof of a Bachelor’s degree from an accredited institution
- Transcripts from all educational institutions attended
- A Statement of Purpose and admissions statements (1–2 pages)
- Two professional letters of recommendation
- Current résumé
- Application fee
- GRE/GMAT (optional)
English Language Proficiency:
A TOEFL or IELTS Academic score is required unless you qualify for an exemption.
To learn more about the exemption criteria, visit our Admissions Overview page.
Foundational Technical and Programming Requirements
MIDS applicants should have basic proficiency and knowledge in:
- Object-oriented programming (e.g., Python, Java, C++)
- Data structures
- Algorithms
- Algorithm analysis
- Linear algebra
Applicants lacking these background skills while meeting all other admissions requirements may be asked to either:
- Complete a bridge course before enrolling in DATASCI 207 Applied Machine Learning
- Take DATASCI 200: Introduction to Data Science Programming during their first term.
Those with sufficient prior knowledge may complete a waiver exam to place out of the course.
The final deadline for the May 2027 cohort is February 26, 2027.
A Multidisciplinary Data Science Curriculum
The Berkeley MIDS curriculum prepares graduates to translate complex data into strategic decisions, communicate across technical and business teams, and lead responsible innovation in an AI-driven world.
Drawing from computer science, statistics, social sciences, and management, the program is designed around the belief that effective data leaders need more than technical expertise — they must also understand the human, ethical, and organizational contexts behind data.
As your courses progress, you’ll develop practical experience working with large-scale, unstructured datasets while building skills in AI systems, predictive modeling, data engineering, analytics, and strategic communication.
Core Studies
The curriculum combines technical training with ethical and strategic thinking across the full data science life cycle. As such, all MIDS students complete five foundational courses:
Introduction to Data Science Programming
Research Design and Application for Data Analysis
Statistics for Data Science
Applied Data Engineering
Applied Machine Learning
After the foundational phase, students personalize the remainder of their curriculum by choosing electives that support their interests or professional trajectory. This means choosing one of four optional focus areas or exploring courses across multiple areas of study.
Optional Focus Areas
Built to help graduates specialize in specific, industry-relevant data science fields, the four optional focus areas are:
1. Applied AI & Machine Learning
This pathway is for you if you want to build intelligent models and AI-driven solutions. You’ll learn to design, train, and evaluate models from classical methods through generative AI.
Topics include:
- Applied modeling: supervised, unsupervised, and reinforcement learning
- Generative AI and large language models (LLMs)
- Deep learning architectures
- Neural network design
2. Machine Learning Systems and Production AI
This pathway is for you if you want to develop reliable AI systems for real-world environments. You’ll gain the engineering skills to build, scale, and deploy AI systems.
Topics include:
- Data pipelines and infrastructure for ML workloads
- Model deployment, serving APIs, and versioning
- Monitoring, reliability, and MLOps at scale
3. Applied Statistics and Decision Science
This pathway is for you if you want to design rigorous analytical models that drive key decisions while navigating uncertainty. You’ll learn to think rigorously about causation vs. correlation, design valid experiments, and communicate uncertainty to stakeholders.
- Probability theory
- Statistical models and testing of assumptions
- Experimental design and A/B testing
- Causal inference and modern experimentation in information systems
- Time series analysis and forecasting
4. Technology Leadership and Strategy
This pathway is for you if you want to lead technical teams, shape product development, or drive organizational strategy, especially in AI. You’ll build robust technical expertise alongside the leadership skills needed for strategic roles.
Topics include:
- Product strategy for AI and data-driven products
- Technical leadership and organizational decision-making
- Ethics, governance, and AI policy
Want to learn more about which focus area may be right for you?
Featured Courses
The MIDS curriculum features a wide range of courses that provide students with a comprehensive understanding of how data science can be used to inform decision-making in their organizations, including:
Applied Machine Learning
Master end-to-end model development using linear and logistic regression, gradient descent, and advanced neural network architectures. Transition from development to deployment by engineering production-ready systems using Kubernetes, CI/CD pipelines, and API-based model serving to optimize performance and latency. Learn how to apply crucial machine learning techniques to solve problems, run evaluations, interpret results, and understand scaling from thousands of data points to billions.
Behind the Data: Humans and Values
Lead with integrity by evaluating the legal and ethical risks of data science projects. Investigate bias, inclusivity issues, and hallucination risks in GenAI while learning to activate responsible AI principles through human-centered design. Case studies will explore these issues across various domains, including criminal justice, national security, health, marketing, politics, education, and employment.
Generative Artificial Intelligence (AI) & Large Language Models (LLMs)
Gain a deep technical understanding of Transformer architectures and training methodologies. Learn to deploy and optimize large language models through prompt tuning, quantization, and parameter-efficient fine-tuning (PEFT), and improve model alignment using Reinforcement Learning from Human Feedback (RLHF).
Data Engineering & Systems Architecture
Design the scalable infrastructure that underpins modern AI. Build reproducible data pipelines to manage structured and unstructured data from APIs and streaming systems. Leverage Docker and containerization to construct data architectures that support the machine learning lifecycle.
The Capstone Experience
The MIDS capstone project serves as the culmination of all the skills students have acquired throughout the program and actively prepares them for success in the field.
Student teams have two group-based capstone options:
Synthetic Capstone
Transform an original idea into a data-driven product.
Client-Based Capstone
Use your expertise to solve a real-world business challenge and engage in real-world consulting experiences.
For both options, students will:
- Create and propose a data science project idea (often an AI/LLM)
- Conduct and communicate their work
- Receive and provide feedback (in informal group discussions and formal class presentations)
- Deliver compelling presentations
- Deliver a web-based final deliverable that can be used in their portfolio
Each semester, the top MIDS capstone projects are honored with the Hal R. Varian MIDS Capstone Award and are also eligible for the Sarukkai Social Impact Award.
Learn more about the capstone experience by visiting our MIDS Capstone Projects page.
Immersion Experiences
Held three times a year, UC Berkeley MIDS immersions connect online learning with enhanced peer engagement. Students must attend at least one immersion throughout the program, either on campus or online.
Through hands-on workshops, case studies, career programming, and opportunities to engage with faculty, alumni, peers, and industry leaders from the Bay Area and Silicon Valley, immersions help students:
- Apply their knowledge to real-world data science challenges
- Build meaningful connections across the Berkeley community
- Expand their professional network and career opportunities
- Strengthen communication, collaboration, and leadership skills
- Explore emerging opportunities in data science, AI, cybersecurity, and beyond.
A conference-style format means students can attend multiple immersions and gain new insights and connections each time. In addition, longitudinal student satisfaction data show that immersions are highly valued, with more than 90% of attendees rating them as excellent across three core areas: advanced learning, community and connection, and career acceleration.
Hear From a Former Student
“To say that this program has changed my life is an understatement. It has been a fantastic journey that has given me a comprehensive understanding of how data science can be used to inform decision making and to create responsible solutions guided by ethics. I am looking forward to the next stage of my professional career by using my degree, experience and passion to create a positive impact in my local community.“
– Autumn R., Principal Data Scientist and Founder at Heights Technology House
Want to learn more about the MIDS curriculum?
Who Will You Learn From?
MIDS faculty are UC Berkeley faculty and industry leaders with extensive expertise in machine learning, AI ethics, public policy, research design, and applied data science. The UC Berkeley School of Information faculty combines academic research with industry insight to prepare students for the rapidly evolving demands of data science and AI-driven industries.
Visit the detailed faculty profile pages below to learn more about some of the faculty who’ll serve as your mentors throughout the program.
Faculty Spotlights
Assistant Professor of Practice, UC Berkeley School of Information
Associate Adjunct Professor, UC Berkeley School of Information
Lecturer, UC Berkeley School of Information
Lecturer, UC Berkeley School of Information
Careers in Data Science
As organizations across industries continue to generate and rely on increasing volumes of data, the demand for professionals who can analyze information, build AI-driven systems, and translate insights into strategic decisions continues to grow.
Employers are seeking data science professionals who can combine technical expertise with critical thinking, communication, and ethical decision-making in a rapidly evolving technology landscape.2
Roles
MIDS program graduates can pursue opportunities across fields including technology, healthcare, finance, consulting, government, and research — where data-informed decision-making and AI capabilities are becoming increasingly essential.
Graduates of the MIDS program often go on to accept the following roles:
- Analytics engineer
- Consultant
- Data analyst
- Data engineer
- DataOps lead
- Data scientist
- Data strategist
- Decision scientist
- Emerging “AI-” job titles, e.g. chief AI officer
- Machine learning engineer
- Manager/director of data/engineering teams and products
- MLOps strategist
- Product manager
- Software engineer
- Solutions engineer
Alumni Network and Industry Connections
MIDS graduates work around the world to address social, economic, and health problems, and put their skills to work at top companies, including Amazon, Apple, Facebook, Microsoft,and Google.
Students and alumni can connect with the I School community through the I School Slack workspace, the official I School professional networking platform.
Visit our Alumni Profiles page to learn more about how MIDS graduates have used our network to advance their careers.
Take Your Place in the UC Berkeley Community
When you become a MIDS student, you become part of a thriving online and in-person community ready to enhance your learning and keep you connected to your peers through a wide range of resources including:
- Research centers, groups, and initiatives, including the Berkeley Institute for Data Science (BIDS), the Berkeley Artificial Intelligence Research (BAIR) Lab, Digital Humanities at Berkeley, the D-Lab and more.
- Events, programs, and students at other schools and colleges, including the College of Engineering, Haas School of Business, College of Chemistry, Goldman School of Public Policy, and more.
- Entrepreneurship and startup opportunities, including campus incubators, groups, associations, and competitions, the LAUNCH startup accelerator, and Berkeley SkyDeck.
Comprehensive Support
You will receive comprehensive support that begins the moment you request information about the Online MIDS program.
- Enrollment Specialist: During the admissions process, you will work with a dedicated Enrollment Specialist, available to answer questions about the program and the application process.
- Adviser: Upon admission, you will be assigned an adviser who can meet with you face-to-face via the online platform throughout the program. They will serve as your guide through the academic environment, so you can focus on your professional career and classes.
- 1:1 Career Support: Throughout the program, you will have access to personalized career support to help you stay on track and work toward your career goals. Your career adviser will guide you beyond résumé reviews, making direct introductions to industry recruiters so you can connect with hiring managers rather than get lost in an application queue.
The Online Learning Experience
The Online MIDS program combines advanced technology and in-person experiences to ensure you benefit from the full I School experience. All of the online tools you need to succeed are hosted in the virtual campus, where you can:
- Access your weekly Zoom classes to engage in meaningful discussions.
- Complete coding work through seamless GitHub integration.
- View upcoming coursework and deadlines on your dashboard.
- Attend class or complete course work from anywhere using the mobile app.
Tuition and Financial Information
Tuition is charged on a per-unit basis, and the program requires 27 total units for completion.
Estimated Tuition (2026-2027)
| Tuition Component | Estimated Cost |
|---|---|
Cost Per Unit | $2,850 |
Total Units Required | 27 Units |
Estimated Total Tuition | Approximately $76,950 |
*Estimated tuition is based on current published program fees and does not include campus fees, document management fees, health insurance, immersion-related expenses, textbooks, or personal costs. Tuition and fees are subject to change.
Additional University Fees
| Per-Semester Fees | Estimated Cost |
|---|---|
Berkeley Campus Fee | $904.75 (spring/fall) |
UC Graduate and Professional Council (UCGPC) Fee* | |
Instructional Resilience and Enhancement Fee | $141 per semester |
Student Health Insurance Plan (SHIP)** | $4,103.00 |
* Students may opt out of the UCGPC fee.
** Students have the option to waive the Student Health Insurance Plan (SHIP) if they have other major medical health insurance that meet the SHIP waiver criteria and don’t wish to have dual coverage. For waiver qualifications, instructions, forms, and FAQs, please see Waiving SHIP.
| One-Time Fees | Estimated Cost |
|---|---|
Document Management Fee (A one-time fee charged in the student’s first semester) | $113 |
Immersion program fee(Students attend at least one in-person or virtual Immersion Program. Students are responsible for their own lodging and travel.) | $500.00 |
The tuition, fees, and charges displayed here reflect the currently approved amounts. These figures may not be final. Actual tuition, fees, and charges are subject to change by the Regents of the University of California and could be affected by State funding reductions. Accordingly, final approved levels (and thus a student’s final balance due) may differ from the amounts shown. Students should expect fees to increase moderately each fall term.
If you are or will be utilizing veterans’ educational benefits to fund your degree, contact UC Berkeley’s Veterans Benefits Unit at veteransbenefits@berkeley.edu for information regarding whether the overall program fee is covered or includes fees that are not covered.
For additional information on the cost of attendance, please visit Financial Aid and Scholarships Office Cost of Attendance.
Choose a Program That Transforms Students into Data Science Leaders
Talk to your Enrollment Specialist about potential application fee waivers.
FAQs About UC Berkeley’s Online Master of Information and Data Science (MIDS)
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No, the UC Berkeley MIDS diploma and transcript make no distinction between online and on-campus graduate programs. Both documents are identical to those received by students who attended in person.
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The MIDS program is a high-value investment defined by its high-touch, synchronous model, which distinguishes it from lower-cost programs that rely on massive asynchronous lectures (which also have a much higher dropout rate). Rather than being an anonymous face in a sea of students, UC Berkeley students learn in intimate classes of only 15–20 people, ensuring you are personally known by faculty and peers.
MIDS attracts high-calibre working professionals embedded in data science, engineering, policy, and beyond, which means the classroom provides a high level of peer-to-peer engagement and is as much a source of real-world insight as the curriculum itself.
That environment makes possible what large programs cannot offer:
- Real-time access: Live sessions featuring genuine, faculty-led dialogue are a key part of the student experience and replace forum queues.
- Personalized mentorship: Small classes mean tailored feedback, meaningful relationships, and a professional network built through actual collaboration.
- Two capstone options: A group-based synthetic capstone course and final project, or a client-based capstone course working with client partners to solve real business challenges.
- Immersion experiences: Held three times a year, each three-day conference-style event includes keynote addresses and concurrent breakout sessions, alumni-, faculty-, and career-oriented panels, and opportunities to attend student-run social events.
- Career services: 1:1 career support provides essential guidance and industry access throughout the MIDS experience.
Take your place in the UC Berkeley community. Enhance your learning and connection to your peers with access to a wide range of Berkeley resources including research centers, events, incubators, and more.
- Research centers, groups, and initiatives, including the Berkeley Institute for Data Science (BIDS), the Berkeley Artificial Intelligence Research (BAIR) Lab, Digital Humanities at Berkeley, the D-Lab and more.
- Events, programs, and students at other schools and colleges, including the College of Engineering, Haas School of Business, College of Chemistry, Goldman School of Public Policy, and more.
- Entrepreneurship and startup opportunities, including campus incubators, groups, associations, and competitions, the LAUNCH startup accelerator, and Berkeley SkyDeck.
This overall depth of engagement contributes to a 63% success rate for students securing new roles and a median U.S. alumni salary of approximately $147,800.
For professionals seeking a career in top-tier tech firms, the program investment provides the rigorous, multi-disciplinary education that Berkeley’s reputation is built on, along with access to a global network to help you grow your career in a competitive market.
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No, if anything, a Master of Information and Data Science degree is more essential. Generative AI automates the routine, such as basic data cleaning, boilerplate code, and surface-level analysis. What it cannot replace is the judgment to know when an output is wrong, the rigor to validate it, and the expertise to deploy it responsibly.
MIDS is evolving alongside the field, equipping students not just to use AI tools, but to design, interrogate, and govern them. The data scientist role is shifting toward higher-order work such as strategic deployment, critical interpretation, and navigating the ethical and organizational complexity that AI introduces. That shift does not diminish the degree; it raises the ceiling on what it can do.
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The program’s career support is built around access, not generic advice. MIDS students work 1:1 with career advisers who do more than review résumés. They make direct introductions to recruiters in the industry, ensuring graduates land in front of hiring managers rather than disappearing into an application queue increasingly filtered for AI-generated submissions.
That access extends to the Berkeley network itself. During immersions, students connect in person with alumni who have navigated the same path, gaining candid guidance, mentorship, and relationships that often translate directly into referrals and opportunities.
The outcomes speak for themselves: 63% of students secured new roles (often while still in the program), many at top-tier tech employers and backed by the weight of the UC Berkeley name.
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The MIDS curriculum is updated every term to reflect the latest developments in AI and data science. Courses are taught by top-tier industry practitioners who incorporate recent research into project-based learning. Hands-on coursework spans the full modern stack:
- Generative AI & LLM: Deploy, fine-tune, and build a strategy around Large Language Models.
- Natural Language Processing (NLP) & Deep Learning: Explore transformer architecture and modern NLP approaches.
- Machine Learning at Scale: Design and deploy scalable ML pipelines for structured and unstructured data in the cloud, with a focus on production-ready deep learning systems.
- Computer Vision: Apply face detection, image recognition, and visual processing techniques to real-world problems.
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UC Berkeley MIDS alumni typically experience significant career advancement, with many students realizing a return on investment even while they are still in the program:
- Approximately 50% to 78% of graduates report a salary increase shortly after graduation.
- As of 2024, the median salary for U.S.-based Master of Information and Data Science alumni is approximately $147,800.
- Over 60% of graduates start new jobs or receive promotions, frequently moving into roles at leading organizations such as Google, Meta, and Amazon.
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Three ways: reputation, rigor, and relationships.
UC Berkeley is the #1 ranked public university in the world,3 and so its name carries immense weight in the global security landscape. The curriculum is built to match that reputation: a multidisciplinary, practitioner-led education that balances deep technical execution with high-stakes business strategy.
But the real differentiator is the environment. With 15–20 students per class, you get personalized faculty engagement, close-knit peer relationships, and a direct path to an elite global network of alumni holding senior management and C-suite positions across the industry.
The program also offers immediate benefits, with acurriculum that focuses on real-world security simulations and leadership strategies that you can apply on the job the very next day.
As a result, many students experience a tangible return on investment while they are still actively in the program, leveraging their evolving expertise to earn promotions, lead enterprise defense initiatives, and command authority before completing their degree.
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MIDS graduates gain lifelong entry into an elite global network of over 500,000 UC Berkeley alumni, alongside continuous career support and exclusive university privileges. The relationship with the I School does not end at graduation; it scales with your career over time.
As an alumnus, you receive a robust suite of long-term perks, including:
- Lifelong career services: You maintain ongoing access to the I School’s dedicated career advisers for 1:1 consulting, résumé pivots, and salary negotiation strategies as you move into executive tracks.
- The power of the Berkeley network: You unlock access to exclusive, cross-industry alumni directories and regional networking chapters, connecting you directly with senior data-science and AI leaders in Silicon Valley and globally.
- Continuing education: Graduates are invited back to attend exclusive campus workshops, tech conferences, and specialized guest-speaker series to keep their technical toolkits sharp as technology evolves.
- University perks: Alumni retain specific structural benefits, including lifelong Berkeley email forwarding, access to university library databases, invitations to private networking mixers during on-campus immersions, and eligibility for the Cal Alumni Association (CAA) benefits.
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The primary difference lies in scope: Data analytics focuses on interpreting historical data, while data science focuses on building predictive models and new algorithms.
- Data analytics: Emphasizes the use of statistical methods and existing tools to create visualizations that inform present-day decisions.
- Data science: A broader, interdisciplinary field that includes analytics but prioritizes machine learning and the entire data life cycle to predict future outcomes
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Yes, the UC Berkeley Master of Information and Data Science program accepts students from a wide range of professional fields and undergraduate degrees, provided they demonstrate strong quantitative aptitude.
While a computer science degree is not required, successful applicants must demonstrate proficiency in Python programming, as well as an understanding of linear algebra, data structures, and algorithms. Applicants can prove this readiness through academic coursework or relevant professional experience.
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The Master of Information and Data Science program requires a bachelor’s degree, statement of purpose, current résumé, transcripts, and two professional letters of recommendation. GRE/GMAT scores are not required. The program offers three start dates per year — in January, May, and August — with admissions decisions made on a rolling basis.
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Plan for 10-15 hours per week, per course. Most working professionals take one to two courses at a time, which puts the typical weekly commitment somewhere between 15 and 30 hours. A few courses, like Machine Learning at Scale, are more demanding by design. During peak periods, such as major project deadlines, expect that number to climb.
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Live sessions are the heartbeat of the MIDS classroom experience. Held in real time and led by faculty, these synchronous virtual classes are where the learning goes deep, not through recorded lectures watched alone, but through live discussion, collaborative problem-solving, and the back-and-forth that changes how you think about a problem.
In a class of 15–20 students, faculty know who you are, engage directly with your thinking, and push you to defend and refine your ideas on the spot. Your peers, many of them working professionals with firsthand industry experience, bring perspectives that textbooks and tutorials don’t. The result is a classroom dynamic that’s genuinely rare in online education, intellectually rigorous, personally engaged, and immediately applicable to real-world challenges.
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MIDS offers three paths to completion, designed to fit different professional and personal circumstances:
- Standard path (20 months): The most common route for full-time professionals, typically involving two courses per semester.
- Accelerated path (12 months): A demanding track for students not working full time, requiring three courses per semester.
- Decelerated path (32 months): A flexible option allowing students to take only one course per semester.
This program is offered in collaboration with 2U, which is an online program management (OPM) company. The roles and responsibilities of the OPM partner in the offering of the program are to provide marketing support for the program, assistance with student recruitment, and front-line student support. UC Berkeley and UC Berkeley faculty are responsible for the creation of academic content, instruction, grading and assessment, credential and transcript creation and issuance, student services and escalated student support, program admissions, and accessibility accommodation. Click here to learn more about 2U’s roles and responsibilities.
- Best Online Master’s in Data Science Programs. (2025). Fortune Education. Retrieved May 26, 2026. ↩︎
- Data Science Career Paths. (2025). Sprints AI. Retrieved May 21, 2026. ↩︎
- Top Public National Universities. (2026) U.S. World & News Report. Retrieved September 23, 2026. ↩︎