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Data Science Recommended Academic Plan

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Data Sciences Statistical Modeling Option (Science)

Recommended Academic Plan

Fall Semester 1            

MATH 140* (GQ) Calculus with Analytic Geometry I

4.0

PSU 16 First-Year Seminar

1.0

CMPSC 121* Introduction Python

3.0

STAT 200* (GQ) Elementary Statistics

4.0

ENGL 015 (GWS) Rhetoric & Composition

3.0

Total Credits: 15.0

Spring Semester 2

MATH 141* (GQ) Calculus with Analytic Geometry II

4.0

IST 210* Organization of Data

3.0

CMPSC 122* Intermediate Programming

3.0

Gen ED (GN)

3.0

Gen ED (GS/IL or US)

3.0

Total Credits: 16.0

Fall Semester 3

STAT 184* Introduction to R

1.0

MATH 220* Matrices (linear equations, matrix algebra)

2.0

MATH 230* Calculus and vector analysis

4.0

DS 220* Data Management for Data Sciences

3.0

Gen ED (GA)

3.0

CAS 100 (GWS) Effective Speech

3.0

Total Credits: 16.0

Spring Semester 4

STAT 380* Data Science through Statistical Reasoning and Computation

3.0

STAT 462* Applied Regression Analysis

3.0

STAT 414* Probability

3.0

ENGL 202C (GWS) Effective Writing

3.0

Gen ED (GH/IL or US)

3.0

Total Credits: 15.0

Fall Semester 5

STAT/MATH 415* Mathematical Statistics

3.0

DS 300*  Privacy & Security for Data Sciences

3.0

DS 310* Machine Learning for Data Analytics

3.0

Gen ED (GN)

3.0

Gen ED (GS)

3.0

 Total Credits: 15.0

Spring Semester 6

DS 330* Visual Analytics for Data Sciences

3.0

STAT 440* Computational Statistics

3.0

LIST A* selection

3.0

Gen ED (GN)

3.0

Elective

3.0

Total Credits: 15.0

Fall: Semester 7

DS 340W* Applied Data Sciences

3.0

LIST A* selection

3.0

LIST B* selection

3.0

Gen ED (GA)

3.0

Gen ED (GHA)

1.5

Elective

3.0

Total Credits: 16.5

Spring:  Semester 8

DS 440* Data Science Capstone Course

3.0

LIST B* selection

3.0

Gen ED (GHA)

1.5

Gen ED (GH)

3.0

Elective

3.0

Elective

3.0

Total Credits: 16.5

*C or better required

 

List A
(6 credits required from this list):
List B
(6 credits required from this list):
MATH 435 Basic Abstract Algebra 3.0 DS 310 Machine Learning for Data Analytics 3.0
MATH 436 Linear Algebra or
MATH 441 Matrix Algebra
3.0 DS 320 Data Integration & Fusion 3.0
MATH 451 Numerical Computations
or MATH 455 Introduction to
Numerical Analysis I
3.0 DS 330 Visualization & Visual Analytics 3.0
MATH 484 Linear Programs and
Related Problems
3.0 DS 410 Analytics at Scale 3.0
STAT/MATH 416 Stochastic Modeling 3.0 DS 402 Emerging Trends in Data Science 3.0
STAT 461 Analysis of Variance 3.0 ST 461 Database Management and Administration 3.0
STAT 463 Applied Time Series Analysis 3.0 CMPSC 441 Artificial Intelligence 3.0
STAT 466 Survey Sampling 3.0 CMPSC 448 Machine Learning and Algorithmic AI 3.0
STAT 483 Statistical Analysis
System Programming
3.0 CMPSC 461 Programming Language Concepts 3.0
CMPSC 465 Data Structures and Algorithms 3.0
CMPSC 440 Big Data Analytics 3.0