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Courses - Spring 2019
BSOS
Behavioral and Social Sciences
BSOS331
Python Programming for the Social Sciences
Credits: 1
Grad Meth: Reg, P-F, Aud
Prerequisite: Students must have completed a least one college-level statistics course.
Restriction: Must be enrolled in a BSOS major; or permission of instructor.
Python has become the most powerful programming language in advanced statistics and data analytics. It includes expansive packages for data handling and processing, including the latest developments in machine learning, and offers Integrated Development Environments (IDE) for code development, testing, debugging, and graphical representation. In addition, python is deployed on virtually all high performance computing clusters, taking advantage of multi-processing, large memory, and GPU enhanced computing environments. This course offers a thorough introduction to python and those packages that are fundamental to data processing and analysis, image processing, natural language processing, machine learning.
BSOS355
(Perm Req)
Social Sciences Internship Practicum
Credits: 3
Grad Meth: Reg
GenEd: DSSP
Restriction: Must have earned a minimum of 60 credits; and minimum cumulative GPA of 2.5; and must have completed at least 1 semester at UMD.
Credit only granted for: BSOS388I or BSOS355.
Formerly: BSOS388I.
BSOS 355 is an internship course open to all majors. It will enable students to articulate and apply the scholarship from the discipline related to their specific internship placement into a real-work environment.
BSOS388B
Behavioral and Social Sciences Special Topics; Innovation and Social Change: Do Good Now
Credits: 3
Grad Meth: Reg, P-F, Aud
GenEd: DSSP, SCIS
For BSOS majors only. Also offered as HONR348D and PUAF388D. Credit will be granted for BSOS388B, HONR348D or PUAF388D.

This is a BSOS Solutions Lab and a Fearless Ideas course offered in collaboration with PUAF388D and HONR348D. Explore the many mechanisms for achieving social impact through social innovation. This is team-based, highly interactive and dynamic course, that provides an opportunity for students to generate solutions to a wide range of problems facing many communities today. This course deepens the students understanding of entrepreneurship and innovation practices by guiding them through the creation and implementation process as applied to a project idea of their choice. These projects serve as the laboratory to implement topics such as design systems thinking, developing and communicating a strategy and goals, project management and implementation skills, teamwork and talent management, fundraising and revenue generation, marketing and partner development, leadership skills and project sustainability. For more information, visit dogood.umd.edu.

A Fearless Ideas Course from the Academy for Innovation & Entrepreneurship (AIE): http://ter.ps/iamFEARLESS Click here for more information on the Fearless Ideas Courses.

Click here for more course information on the BSOS Solutions Lab.
BSOS388X
(Perm Req)
Behavioral and Social Sciences Special Topics; Innovation in the Public Sector II
Credits: 3
Grad Meth: Reg, P-F, Aud
Prerequisites: BSOS388F or GVPT388B

For permission to register, email bsos-ugdean@umd.edu. with your name, UID, and brief statement of why this course is of interest to you.
BSOS631
(Perm Req)
Python Programming for the Social Sciences
Credits: 1
Grad Meth: Reg, P-F, Aud
Prerequisite: Students must have completed a least one college-level statistics course.
Restriction: Must be enrolled in a BSOS major; or permission of instructor.
Also offered as: BSOS331.
Credit only granted for: BSOS331, BSOS631.
Python has become the most powerful programming language in advanced statistics and data analytics. It includes expansive packages for data handling and processing, including the latest developments in machine learning, and offers Integrated Development Environments (IDE) for code development, testing, debugging, and graphical representation. In addition, python is deployed on virtually all high performance computing clusters, taking advantage of multi-processing, large memory, and GPU enhanced computing environments. This course offers a thorough introduction to python and those packages that are fundamental to data processing and analysis, image processing, natural language processing, machine learning.