"Data is the ultimate roadmap, and job candidates who can navigate it are poised for success.”

-Mark Bregman, Chief Technology Officer, Neustar Inc.

 

Major Requirements

Tapping the economic and social potential of big data requires overcoming two challenges. The first is understanding how to handle and analyze large bodies of raw information. The second is knowing how to apply these data in research, problem solving and decision making without compromising values like individual privacy. Data science provides tools for exploring data but it doesn’t tell us what to look for or whether what we think we find is really there. Penn State’s Social Data Analytics Program gives students both the technical skills of a data science degree -- developing computational skills to collect and manage the data, get it in the right form and identify useful patterns -- and knowledge of social context and social science methods to apply those skills to real problems effectively and ethically.

What are the requirements for a major in Social Data Analytics?

Admission to the major requires a grade of C or better in MATH 110/140, MATH 111/141, and CMPSC 122, and a grade of B or better in PL SC 309. These courses must be completed by the end of the semester during which the admission to major process is carried out. 

For the B.S. degree in Social Data Analytics, a minimum of 121 credits is required.  These credit requirements are described below.


GENERAL EDUCATION: 45 credits

Of these 45 credits, 15 are included in the requirements for the major.  See the University Bulletin for information on the general education requirements: http://bulletins.psu.edu/undergrad/generaleducation/generalEd2

REQUIREMENTS FOR THE MAJOR: 91 credits

The 91 major credits include 15 credits of General Education courses: 6 credits of GQ courses and 6 credits of GS courses, and 3 credits of GH courses.

Majors must receive a grade of C or better in their required courses, as specified in Senate Policy 82-44.

SoDA CORE CURRICULUM (61 credits)

  • PL SC 010 The Scientific Study of Politics, GS(3)
  • PL SC 001 Introduction to American National Government, GS(3)
  • PL SC 309 Quantitative Political Analysis
  • SODA 308 Data and Design
  • SODA 496 Capstone Experience (6 credits)
  • MATH 110 or 140 Calculus I, GQ(3)
  • MATH 111 or 141 Calculus II, GQ(3)
  • MATH 220 Linear Algebra
  • CMPSC 121 Introduction to Programming
  • CMPSC 122 Intermediate Programming
  • CMPSC 221 Object Oriented Programming
  • CMPSC 360 Discrete Math for Computing
  • IST 210 Organization of Data
  • STAT 318 Probability Theory
  • STAT 380 Data Science through Statistical Reasoning and Computation
  • DS 220 Data Management for Data Sciences
  • DS 300 Data Privacy and Security
  • DS 310 Machine Learning and Data Mining
  • DS 330 Visual Analytics and Visualization

ADDITIONAL COURSES (30 credits)

Foundational & Advanced Political Science Courses, 18 credits:

Select 3 credits:

  • PL SC 003 Introduction to Comparative Politics
  • PL SC 007 Political Ideologies
  • PL SC 014 Introduction to International Relations
  • PL SC 017 Introduction to Political Theory

Select 15 credits of PL SC courses; at least 12 credits must be at the 400 level and at least 9 credits must be data intensive courses from a department list, including but not limited to:

  • PL SC 404 Analysis of Public Policy in the American States
  • PL SC 429 Analysis of Elections
  • PL SC 447 Analysis of Public Opinion and Political Attitudes
  • PL SC 476 Empirical Legal Studies

Ethics Courses, select 3 credits: 

  • PHIL 106 Introduction to Business Ethics, GH (3)
  • PHIL 107 Introduction to Philosophy of Technology, GH (3)
  • PHIL 233 Ethics and the Design of Technology, GH (3)
  • PHIL 406 Business Ethics
  • PHIL 407 Technology and Human Values
  • STS 101 Modern Science, Technology, and Human Values, GH (3)

Advanced Analytics Courses, select 9 credits (initial list, other courses will be added):

  • CMPSC 431W Database Management
  • CMPSC 448 Machine Learning
  • CMPSC 465 Data Structures and Algorithms
  • STAT 319 Mathematical Statistics
  • STAT 440 Statistical Computing
  • STAT 464 Nonparametric Statistics
  • DS 320 Data Integration and Fusion
  • DS 402 Emerging Trends in Data Science
  • DS 410 Analytics at Scale

Recommended Curricular Plan for SoDA Majors Not Studying Abroad

Recommended Curricular Plan for SoDA Majors Studying Abroad

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