DATA STRATEGY
Research Program

​COURSE OVERVIEW

Data science is an interdisciplinary field that uses scientific methods, processes, algorithms, and systems to extract knowledge or insights from data in various forms. Data science is an extension of data analysis fields like data mining, statistics, and predictive analysis. Data science uses theories and techniques that are part of other fields, such as information science, mathematics, statics, and computer science. Some methods used in data science include probability models, machine learning, signal processing, data mining, statistical learning, database, data engineering, visualization, pattern recognition and learning, uncertainty modeling, computer programming among others.

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This program offered by UC Berkeley professor Greg L. aims to provide an understanding of the role of data and statistical analysis in managerial decision-making. We focus on the role of managers as both consumers and producers of information, illustrating how finding and/or developing the right data and applying appropriate statistical methods can help solve problems in business. With a highly experiential curriculum that combines lectures, case discussions, and team projects, this program will equip students with a competitive edge in their professional and academic careers by mastering one of the hottest topics of technology.

WHY DATA SCIENCE?

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Data and information have become the key resources in a wide range of industries. Data is so important to all organizations and at all levels. It’s not just big IT and software companies: data experts are needed in banking and finance, automotive, energy, healthcare, transport, retail, and virtually every domain you can think of. The job titles you will encounter are as diverse as the responsibilities you will have. If you are a specialist who knows how to “crunch the numbers”, you will be a valuable team member in many parts of an organization.

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Data scientists are in high demand - and employers don’t find enough graduates to fill their openings. To address the demand, universities have been increasing the number of bachelors and masters in data engineering and data analytics. With potential employers fighting over them, university graduates are now in a comfortable position and can demand high salaries.

Example Jobs (See Diagram Below for More Details):

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✦ Analytics Engineer 
✦ Analytics Manager 
✦ Big Data Engineer 
✦ Business Analyst 
✦ Data Architect
✦ Data Analyst
✦ Data Engineer
✦ Data Scientist
✦ Data Visualization Specialist
✦ Business Intelligence (BI) Architect 
✦ Business Intelligence Engineer
✦ Statistician

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"Data scientists are becoming the most respected professionals of the 21st century."

-- Tom Davenport & DJ Patil

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