5 Analytics Courses Results
The Biomedical Informatics (BMI) training program encompasses bioinformatics, clinical informatics, and public health informatics. Bioinformatics focuses on methods relevant to basic biology. Clinical informatics focuses on methods relevant to patient care. Public health informatics focuses on methods relevant to entire health systems.
Students in the BMI program may focus on any aspect of information management and analysis relevant to biomedical research. Students are united in their interest in using information technology to analyze and understand biomedical data, and in developing new methods for using information to improve health care.
With the rise of user-web interaction and networking, as well as technological advances in processing power and storage capability, the demand for effective and sophisticated knowledge discovery techniques has grown exponentially. Businesses need to transform large quantities of information into intelligence that can be used to make smart business decisions.
With the Mining Massive Data Sets graduate certificate, you will master efficient, powerful techniques and algorithms for extracting information from large datasets such as the web, social-network graphs, and large document repositories. Take your career to the next level with skills that will give your company the power to gain a competitive advantage.
Earn a Stanford graduate certificate in data mining online. Three certificates are designed to give you the skills you need to gather and analyze massive amounts of information. Pursue the certificate that best matches your skills and career goals and become a master of your data.
Data mining and predictive models are at the heart of successful information and product search, automated merchandizing, smart personalization, dynamic pricing, social network analysis, genetics, proteomics, and many other technology-based solutions to important problems in business.
The Data Mining and Applications graduate certificate introduces many of the important new ideas in data mining and machine learning, explains them in a statistical framework, and describes some of their applications to business, science, and technology.
This focused M.S. track is developed within the structure of the current M.S. in Statistics and the M.S. program in ICME. Students in the program will develop strong mathematical, statistical, computational and programming skills through the M.S. requirements, and they will gain a fundamental data science education by focusing 18 units of elective courses in the area of data science and related courses. Upon the successful completion of the Data Science M.S. degree students will be prepared to continue on to their Ph.D. in Statistics, ICME, MS&E, or Computer Science or as a data science professional in industry. Completing the M.S. degree gives no guarantee or preference for admission to the Ph.D. program.