Data being displayed over an image of an empty subway track, giving the impression that the information is for/from the train

Organize the Chaos.

The Data Science Pathway offers a blend of theoretical and practical knowledge of Statistics and Computer science, with the goal of preparing students for exciting data-oriented career opportunities in a variety of industries.

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Pathway Information

Students will build skills in statistical analysis and software development by carrying out representative workflows of data exploration, visualization, modeling, and model evaluation and interpretation to solve real-world problems.

Students will be exposed to contemporary programming languages and cloud-based technologies that enhance data science and machine learning capabilities.

IDS Majors

Every IDS major, no matter their pathway, has to take:

Discipline 1 - Mathematics

Foundational 1000/2000-level course (counted in area F):

  • Math 2853 (3 credits)
  • Math 2644 (4 credits)

Major Foundation Courses (6 credits):

  • Math 3003 Transition to Advanced Math
  • Math 4203 Mathematical Probability
    • prereq: Math 2644

Major Required Courses (12 credits):

  • Math 4213 Mathematical Statistics
    • prereq: Math 4203
  • Math 4803 Analysis of Variance
    • prereq: Math 4203
  • Math 4813 Regression Analysis
    • prereq: Math 4203
  • Math 4483 Graph Theory
    • prereq: Math 3003

Discipline 2 - Computer Science

Foundational 1000/2000-level course (counted in area F):

  • CS 1301 Computer Science I (4 credits)
    • prereq: Math 1113 (>=C) OR Math 1112 (>= C)
  • CS 1300 Intro to CS in Python (4 credits)
    • no prereqs

Major Foundation Courses (4 credits):

  • CS 1302 Computer Science II (4 credits)
    • prereq: CS 1301, >= B

Major Required Courses (13 credits):

  • CS 3270 Intelligent Systems
    • prereq: CS 1302 (>= B)
  • CS 3280 Systems Programming
    • prereq: CS 1302 (>= B)
  • CS 3151 Data Structures and Discrete Math I
    • prereq: CS 1302 (>= B)
  • CS 4725 Foundations of Machine Learning [New]
    • prereq: CS 3270
    • pre/co-requisites MATH 4203 
       
Courses in red are required for the Data Science Certificate

Suggested Courses

19 credits from other courses (including minors and electives, etc.), but must have at least 9 credits from 3000/4000 levels. Here are some suggestions.

Electives:

  • Math 4013 Numerical Analysis
  • Math 4823 Applied Experimental Design
  • Math 4833 Applied Nonparametric Statistics
  • Math 4843 Introduction to Sampling

Electives:

  • CS 3152 Data Structures and Discrete Math II 
  • CS 3211 Software Engineering I
  • CS 3230 Information Management
  • CS 4225 Distributed and Cloud Computing

Contact

Contact Us

Dr. Andy Walter
Director, Center of Interdisciplinary Studies
(678) 839-4070
awalter@westga.edu