Master of Information and Cybersecurity - UC Berkeley School of …
WEBThrough a holistic approach to cybersecurity, students develop a thorough understanding of information security technologies as well as the economic, legal, behavioral, and ethical impacts of cybersecurity. Students graduate as competitive candidates in the job market with connections to UC Berkeley alumni and professionals in the San Francisco Bay Area.Request more infoA Leadership-Focused ...
Master of Information and Data Science
WEBThe online master’s program brings UC Berkeley to students, wherever they are. The WASC-accredited program blends a multidisciplinary curriculum, experienced faculty from UC Berkeley and top data-driven companies, an accomplished network of peers, and the flexibility of online learning.Request more infoComplete a Rigorous, Holistic CurriculumThe multidisciplinary online data science master ...
Master of Information Management and Systems
WEBThe Master of Information Management and Systems (MIMS) program is a 48 unit, two-year full time program, designed to train students in the skills needed to succeed as information professionals. Such professionals must be familiar with the theory and practice of storing, organizing, retrieving and analyzing information in a variety of settings in business, the public sector, and the academic ...
Graduate Certificate in Applied Data Science
WEBThe Graduate Certificate in Applied Data Science introduces the tools, methods, and conceptual approaches used to support modern data analysis and decision-making in professional and applied research settings. It exposes students to the challenges of working with data (e.g., asking a good question, inference and causality, decision-making) as well as to the new tools and techniques for data ...
Data Science - UC Berkeley School of Information
WEBAug 21, 2023 · The School of Information offers four degrees: The Master of Information Management and Systems (MIMS) program educates information professionals to provide leadership for an information-driven world.. The Master of Information and Data Science (MIDS) is an online degree preparing data science professionals to solve real-world problems. The 5th Year MIDS program is a streamlined path to a MIDS ...
Ph.D. in Information Science - UC Berkeley School of Information
WEBPh.D. students work closely with faculty recognized as information pioneers. Interdisciplinary thinking and partnership are central to the I School approach, so doctoral research often engages exceptional UC Berkeley schools and departments beyond the I School, from journalism, business, and law to computing, engineering, humanities, and …
Introduction to Data Science Programming - UC Berkeley School …
WEBThe School of Information offers four degrees: The Master of Information Management and Systems (MIMS) program educates information professionals to provide leadership for an information-driven world.. The Master of Information and Data Science (MIDS) is an online degree preparing data science professionals to solve real-world problems. The 5th Year MIDS program is a streamlined path to a MIDS ...
5th Year Master of Information and Data Science
WEBThe School of Information offers four degrees: The Master of Information Management and Systems (MIMS) program educates information professionals to provide leadership for an information-driven world.. The Master of Information and Data Science (MIDS) is an online degree preparing data science professionals to solve real-world problems. The 5th Year MIDS program is a streamlined path to a MIDS ...
Funding Your Ph.D. Education - UC Berkeley School of Information
WEBIn the first year, I School Ph.D. students receive fellowship support to cover all tuition and fees, including Non-Resident Supplemental Tuition and the Student Health Insurance Fee, and a stipend for living expenses. For the academic year 2023–2024, the minimum first-year I School Ph.D. student 12-month stipend is $40,000.
Info 251. Applied Machine Learning - UC Berkeley School of …
WEBInfo. 251. 4 units. Course Description. Provides a theoretical and practical introduction to modern techniques in applied machine learning. Covers key concepts in supervised and unsupervised machine learning, including the design of machine learning experiments, algorithms for prediction and inference, optimization, and evaluation.