Data Analytics (Digital Agriculture) - Master of Data Analytics (Online)

The admission requirements for the degree program requires incoming students to have a bachelor degree and a minimum mathematical preparation at the level of Linear Algebra (MATH 2415 Introduction to Linear Algebra or equivalent course, such as E E 200 Linear Algebra, Probability and Statistics Applications).

The curriculum for the degree program is composed of 30 graduate credits.

Prefix Title Credits
C S 453Python Programming I3
or C S 454 Python Programming II
A ST 511Statistical Methods for Data Analytics3
Select one of the following courses3
R Programming I3
Statistical Analysis with R3
C S 508Introduction to Data Mining3
C S 519Applied Machine Learning I3
or E E 565 Machine Learning I
Select one of the following courses3
Database Management Systems I3
Database Management Systems3
Web Development and Database Applications3
Advanced Topics and Applications
Choose nine credits from the following:9
Applied Multivariate Analysis3
Computational Statistics3
Advanced Methods in Astrophysics3
Business Analytics II3
Advanced Bioinformatics and NCBI Database3
Computer Graphics I3
Advanced Software Development Concepts
Bioinformatics Programming3
Database Management Systems II3
Digital Image Processing3
Characterizing Time-Dependent Engineering Data3
Business Analytics I
Stochastic Processes Modeling3
Queuing Systems
Design and Implementation of Discrete-Event Simulation3
Multimedia Theory and Production3
Seminar in Communication Technologies
Fourier Series and Boundary Value Problems3
Elementary Stochastic Processes
Seminar in Social Networks3
Seminar in Text Analysis for the Social Sciences3
Seminar in Data Visualization3
Instrumentation in Agronomy3
Advanced Agricultural Mechanization3
Advanced Soil Physics3
Capstone Experience
Select one of the following courses3
Master's Project3
Master's Thesis1-15
Special Research Problems3
Master's Technical Report3
Master's Thesis3
Specific Requirement for Digital Agriculture Concentration
Introduction to Data Mining3
Advanced Soil Physics3
Advanced Agricultural Mechanization3
Instrumentation in Agronomy3
Total Credits30

A Suggested Plan of Study

Additional classes may be needed based on placement test results and course prerequisites. Visit with an advisor for help with creating a customized plan.

Plan of Study Grid
First Year
A ST 511 Statistical Methods for Data Analytics 3
C S 453 Python Programming I 3
C S 508 Introduction to Data Mining 3
C S 519 Applied Machine Learning I 3
C S 458 R Programming I 3
Take one of the following 3
Advanced Agricultural Mechanization
Advanced Soil Physics
Instrumentation in Agronomy
Second Year
Two remaining Digital Agriculture Courses 6
C S 502
Database Management Systems I
or Web Development and Database Applications
Choose onf from the following 3
Master's Project
Master's Thesis
Special Research Problems
Master's Technical Report
Master's Thesis
 Total Credits30