Aspiring data scientists have a new opportunity opening up to them as the UC Berkeley School of Information launches the country’s first fully online Master of Information and Data Science (MIDS) degree program.

“This new degree program is in response to a dramatically growing need for professionals who can organize, analyze and interpret the deluge of often messy and unorganized data available from the web, sensor networks, mobile devices and elsewhere,” said AnnaLee Saxenian, dean of the I School.

A 2011 report by the McKinsey Global Institute estimated that by 2018 the United States could be short up to 190,000 people with the analytical skills — and another 1.5 million managers/analysts with the know-how — to make wise use of virtual mountain ranges of data for critical decisions in business, energy, intelligence, health care, finance, and other fields.

These new professionals, said Saxenian, need an assortment of skills ranging from math, programming, and communication to management, statistics, engineering, and social sciences, not to mention a deep curiosity and an ability to translate technical jargon into everyday English. A few of the emerging data scientist job titles are data engineer, data architect, data and analytics officer, financial analyst, and director of health analytics.

The term “data scientist” was coined just four years ago by DJ Patil, then with LinkedIn, and Jeff Hammerbacher of Facebook. Patil is now a “data scientist in residence” at the Greylock venture capital firm and was the I School’s 2013 commencement speaker.

–Hal Varian, chief economist, Google “We are awash with data. But the expertise to analyze and exploit that data is in short supply. The mission of the MIDS degree is to provide that expertise.”

The I School is staking out new master’s degree territory in educating data scientists. While other institutions provide individual classes, certificates, or associate master’s degrees in data science, the I School has designed a comprehensive and integrated suite of courses that culminate in a capstone course designed to solidify a student’s knowledge of the breadth of data science concepts and skills.

The rigorous new 27-unit MIDS program officially begins in January 2014. Aimed at the working professional, the program will be offered online — except for a required, one-week immersion program at the I School’s home at South Hall, to meet in person and explore the Bay Area tech environment.

Students will interact with professors and other students via the web. They will be expected to attend small, weekly face-to-face classes with a student-to-faculty ratio of no more than 15:1, and the coursework will include lectures, interactive case studies, and collaborative assignments. Classes will use 2U Inc.’s online platform that features high-quality video and a state-of-the-art learning management system.

Saxenian, author of “The New Argonauts: Regional Advantage in a Global Economy” and other books about Silicon Valley, said the online MIDS program is ideal for today’s students, who are likely to have jobs working on globally-distributed teams.

The I School faculty designed the curriculum and they will teach alongside experienced data science professionals. Classes will range from an introduction to machine learning — the intersection of computer science and statistics that focuses on finding patterns in data — and how to store and retrieve data, to experimenting with big data and the privacy, security and ethics of data.

The program will cost $60,000, which school officials said compares favorably with other professional degree programs. Entry-level data scientists in the San Francisco area can command salaries in the $110,000 to $130,000 range.

The I School currently offers a professional master’s degree (MIMS) that prepares students for careers as information professionals and a Ph.D. program for scholars interested in developing information management solutions and shaping information policy.

The school is home to the annual DataEDGE Conference, held on campus each May. This year’s program addressed big data mythologies, data scientists as detectives and artists, what happens to your data when you die, data and the humanities, and the current skills and tools used in data analysis.