Faculty Recruiting Support CICS

Informatics Data Science Track

From economics to voting, from astronomy to epidemiology, the analysis of massive quantities of relevant data has become a distinguishing feature of modern life. The Informatics / Data Science track is designed to teach students about the alternative ways to analyze, visualize, and reason about enormous quantities of information.

Core Requirements:

  • INFO 101:Introduction to Informatics*
  • INFO 150:A Mathematical Foundation of Informatics
  • COMPSCI 121: Problem Solving with Computers
  • COMPSCI 186: Using Data Structures
  • INFO 203: Networked World
  • COMPSCI 325: Human Computer Interaction
  • COMPSCI 326: Web Programming (IE)

*credit given for a score of 4 or 5 on the CSP AP exam

Data Science Concentration Specific Requirements:

  • STAT 240 (or equivalent):  Intro to Statistics
  • INFO 248: Intro to Data Science
  • COMPSCI 345: Practical Applications of Data Management
  • Data Science Concentration Elective (pick one of the following): STAT 501, STAT 515, PUBHLTH 460, JOURNAL 397DJ, OIM 350

Electives

Choose 6 courses* from the preapproved list below and/or propose your own

      COMPSCI 328: Mobile Health Sensing and Monitoring

      COMPSCI 365: Digital Forensics (requires CS 230)

      ENGLISH 391C: Web Design

      JOURNAL 397DJ: Data Driven Storytelling

      Marketing 455: Internet Marketing (requires Marketing 301) 

      OIM 350: Business Intelligence and Analytics

      OIM 454: Advanced Business Analytics

      PUBHLTH 460: Telling stories with data: statistics, modeling, and visualization

      STATS 501: Methods of Applied Statistics  

      STATS 515: Statistics I (requires MA 233; STATS 240 or equiv.)

      STATS 516: Statistics II (requires STATS 515)

      SUSTCOMM 297L: Visual Design

      

*courses may only satisfy one major requirement (i.e. an individual course can satisfy a concentration elective or a major elective, not both)

Current proposed Electives that are Pending Final Approval: 

           BIO 379: Genomics and Bioinformatics

BIO 383: Gene and Genome Analysis

CICS 397A - 01 ST-Predictive Analytics/Python   

ECON 309: Game Theory

ECON 452: Econometrics

Marketing 497T: Special Topics- Text Mining & Analytics for Marketing and Business Practice (requires Marketing 301)

Descriptions for CS Courses.

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