GDSP - Requirements - Department of Earth, Atmospheric, and Planetary Sciences - Purdue University
Geodata Science for Professionals Master's Program Department of Earth, Atmospheric, and Planetary Sciences


[Financial consideration] The GDSP is a non-thesis Professional Master’s program. Students enrolled in the program can not receive teaching, research, or other graduate assistantships with fee remissions from Purdue by university regulation. Instead, students are anticipated to be supported by their employers, governments, endowed scholarships, or themselves the whole time in the program. We try to match our program fees and tuition to the Purdue standard Graduate/Professional tuition published by the Office of the Bursar, which is subject to change.

[Academic consideration] The program aims to train a highly competitive workforce that can harness geoscience (such as weather, climate, geophysical, and environmental) data for decision-support in public and private sectors. Targeting audience with STEM background, the program offers core courses that teach analysis and computing methods with geoscience data, foundational geoscience content knowledge, and data-driven applications in geoscience applications complementary to the technical areas of data science (statistical theories and models, statistical and machine-learning methods, algorithms for statistical and machine-learning methods as well as optimization, and computational systems for data analysis).

In order to acquire sufficient trainings in these areas while gaining relevant work experience, GDSP students need to complete a minimum total of 31 credit hours, including 27 credits of coursework, 1 credit of seminar, and 3 credits of internship in industry or an applied research experience. The estimated time for completion for the fulltime MS students is 1.5 years. It is possible for Purdue EAPS students with BS degrees to finish this program in 1 year (Fall, Spring, and Summer semesters). The maximum allowable time for completion is four (4) years.

Admission Prerequisites

To be admitted to the program, students must satisfy all current EAPS Graduate Application Requirements. In addition, they are required to show on their transcripts that they have completed coursework equivalent to 3 semesters of calculus up through vector calculus, a class in linear algebra/differential equations, one semester of programming (C,  Java, Python, and/or Fortran), and a class in statistical methods. Students slightly short of pre-requisites can make up for no more than 3 credits in the first year.

Course Requirements

To graduate, students are required to take a minimum of 31 credits of courses in following Categories 1–6.

Category 1. Data-science Core Courses. Take minimum 2 (6 credits) in Table 1.

Purpose: Enable students to start constructing their own data-driven models for EAPS problems by teaching them what lies behind the methods.

Table 1. Data-science Core courses. Minimum two (2) are required.
Course # Course Title
EAPS 50700
EAPS 50900
Introduction to Analysis and Computing with Geoscience Data

Data Analysis Techniques in Earth and Atmospheric Science
EAPS 51000 Time Series Analysis for Geosciences
EAPS 51500 Geodata Science
EAPS 65700 Geophysical Inverse Theory


Category 2. Foundational Core Courses. Take minimum three courses (9 credits) in Table 2.

Purpose: Ensure students’ knowledge proficiency in the domain science and train their ability to incorporate data science with other scientific paradigms such as theories, experiments, and computation in their specific area of specialization in the Earth, Atmospheric and Planetary sciences. A data-science core course not used to fulfill the Category 1 core requirement could be used to fulfill the requirement here.

Table 2. Foundational courses for the proposed GDSP concentration. Minimum three (3) are required.
Course # Course Title
EAPS 52000 Theory of Climate
EAPS 52100 Atmospheric Chemistry
EAPS 52300 Radar Meteorology
EAPS 52500 Boundary Layer Meteorology
EAPS 52700 Ecosystem Ecology
EAPS 52900 Modeling Ecosystems and Biogeochemical Cycles
EAPS 53200 Atmospheric Physics I
EAPS 53300 Atmospheric Physics II
EAPS 53600 Introduction to General Circulation
EAPS 53900 Mesoscale Meteorology
EAPS 54000 Introduction to Geodesy
EAPS 55700 Introduction to Seismology
EAPS 57700 Geologic Remote Sensing of the Planets
EAPS 58400 Hydrogeology
EAPS 59100 Integr. Global System Modeling
EAPS 63000 Atmospheric Remote Sensing
EAPS 68000 Contaminant Hydrogeology
AAE 52300 Introduction to Remote Sensing
CE 59700 Geographic Information Systems
Additional/alternative courses as approved by the GDSP organizers on an individual basis.  EAPS offers qualified 500-600 level courses every year.


Category 3. Applied Courses. Take minimum two courses (6 credits) in Table 3.

Purpose: These are domain-relevant courses aimed to build concepts and procedural knowledge in specific and practical application areas and teach state-of-the-art computational and/or data analysis techniques, in order for students to acquire expertise in evaluating the results of analysis for decision-support.

The applied areas include (but not limited to) weather and climate risk assessments, environmental remote-sensing applications, Geographical Information System (GIS) applications, etc.

Table 3. Applied courses. Minimum two (2) are required.
Course # Course Title
EAPS 59100 Forecast Verification
EAPS 53000 Extreme Weather and Climate: Science and Risk
EAPS 54100 Geodetic Data and Applications
EAPS 55900 3D Seismic Interpretation and Visualization
EAPS 59100 Introductino to Reflection Seismology
AAE 57500 Introduction to Satellite Navigation and Positioning
ABE 65100 Environmental Informatics
AGRY 54500 Remote Sensing of Land Resources
ASM 54000 GIS Applications
CE 54900 Computational Watershed Hydrology
CE 59700 Geospatial Modeling and Analysis
FNR 395/59800 Advanced Spatial Ecology and GIS
FNR 55800 Digital Remote Sensing and GIS
Additional/alternative courses as approved by the GDSP steering committee


Category 4. Computational and Statistical Elective Courses. Take minimum two (6 credits) from Table 4.

Purpose: Approved elective courses can help broaden and enhance students’ practical knowledge base and skill sets in data science.  Students can consider getting a Computational Science & Engineering Certificate with these electives and others according to

The CS&E faculty representative at EAPS is Dr. Robert Nowack (contact: nowack at purdue dot edu).

Alternatively, students can consider further study and receive a Graduate Certificate in Applied Statistics Graduate Certificate in Applied Statistics after consulting with a GDSP advisor.

Table 4. Elective courses for the proposed GDSP concentration. Minimum two (2) courses are required (Please be aware of pre- and co-requisites)
Course # Course Title
CS 50100
All CS&E
Introduction to Computational Science 
ECE 53800 Digital Signal Processing I
MA 51100 Linear Algebra
MA 527/52800 Advanced Mathematics for Engineers and Physicists I/II
MA 59800 Machine Learning and Uncertainty Quantification for Data Science
ME 57900 Fourier Methods in Digital Signal Processing
PHYS 58000 Computational Physics
STAT 51100 Statistical Methods
STAT 51200 Applied Regression Analysis
STAT 51300 Stat Quality Control
STAT 51400 Design of Experiment
STAT 51600 Basic Probability Appl
STAT 51700 Statistical Inference
STAT 69500 D&R with DeltaRho for Big Data & High Computational Complexity (cannot be take with EAPS 51500)
Additional courses as approved by the GDSP steering committee


Category 5. Internship Experiences

Students register in 3 credits of EAPS 59100 (Advanced Topics in Earth and Atmospheric Sciences) to fulfill the internship requirement, completed with a written MS Project Report for each internship. The credit hours can be broken into 1 credit of off-campus internship in a semester and 2 credits of written MS Project Report in the following semester.

Category 6. EAPS 59100 Geodata Science (GDS) Seminar

Students are required to register for one (1) credit of the GDS Seminar and orally present the results of their internship or applied research experience. (This is in addition to their written MS Project Report).

Responsible Conduct of Research

Students are strongly recommended to take Responsible Conduct of Research workshops before or during their writing their MS Project Reports:

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