Online Graduate Certificate in Spatial Data Science
Meet the Growing Demand for Spatial Data Science Experts
Use Big Data to Make a Big Impact in Agriculture and Natural Resources Management
Build expertise in spatial data science, GIS analytics and geospatial data visualization—100% online, and in just two semesters. A leading education provider in this fast-evolving industry, Purdue University prepares you for emerging opportunities in data science for agriculture, land-use management and big data applications in many dynamic fields.
#1 in Agricultural / Biological Engineering
Rated a top graduate biological/agricultural engineering program—10 years running—by U.S. News & World Report1
#2 in Precision Agriculture
One of the nation’s best colleges for precision agriculture, with a mission to prepare the next generation of precision ag technology specialists2
#6 Top Public Institution
Ranked in the top 10 best public universities in the U.S. by The Wall Street Journal/Times Higher Education3
#6 Most Innovative Nationwide
U.S. News & World Report named Purdue in the top 10 most innovative institutions4
Spatial Data Science Learning Objectives
The Purdue online graduate certificate in spatial data science provides students with the knowledge and skills to:
- Master key concepts of geographic information systems (GIS) and spatial data science, including data sources, projections, spatial data processing and analysis methods, data and metadata creation and a conceptual framework for solving spatial problems.
- Apply spatial analysis techniques using GIS and other software to make judgments and solve problems in the environmental, agricultural and engineering sectors.
- Define landscapes and describe the causes (natural and human) of landscape pattern and the threats to biodiversity locally and globally.
- Demonstrate abilities to access and utilize geospatial data and understand data quality and levels of aggregation of spatial data.
- Identify the important relationships of pattern and process at plot, field and landscape scales for important natural resource management issues such as water quality, biogeochemical cycles, species composition and biomass.
- Demonstrate proficiency in scripting languages, data types, databases and data visualization and analysis for spatial and time series data.
- Demonstrate abilities to apply remote sensing and spatial databases to observe and manage land and other natural resources within a defined area, ecosystem and watershed.
- Be able to provide analysis and interpretation of remotely sensed data in combination with field observations and other data sources.
Note: The Spatial Data Science Graduate Certificate is not eligible for Title IV federal financial aid.
Purdue University’s College of Agriculture is one of the world’s leading colleges of agricultural, food, life and natural resource sciences. We are known around the world for developing innovative, multidisciplinary solutions to challenges and then putting those solutions into action. We develop graduate students who make a difference in the world.
Purdue University College of Agriculture faculty members are nationally and internationally acclaimed award-winning researchers and teachers. Their accomplishments position Purdue Agriculture as a leader at the local, state, national and international levels in food, agricultural, life and natural resources sciences. Our faculty include three World Food Prize laureates and many other distinguished and named professors.
To be considered for admission into the Spatial Data Science Graduate Certificate program, you must have a bachelor’s degree from a regionally accredited institution with a GPA of 3.0 or higher. You will also need to submit the following items:
- Statement of purpose (optional for those with a bachelor's degree in agriculture, forestry, life sciences or a closely related field)
- Official transcripts for every higher education institution attended
- Your TOEFL or IELTS score (for international students)
If you have a bachelor's degree that is not in agriculture, forestry, life sciences or a closely related field, or a GPA below 3.0, you must also submit two letters of recommendation (one from a supervisor).
Statement of Purpose
You are encouraged to submit a statement of approximately 500 words concerning your interest in undertaking or continuing graduate study, your reasons for wanting to study at Purdue and your professional plans, career goals and research interests. You also may explain any unique circumstances applicable to your background and elaborate on your special abilities, awards, achievements, scholarly publications and/or professional history.
Letters of Recommendation
Two online recommendations are required for your application to be received if you have a bachelor's degree that is not in agriculture, forestry, life sciences or a closely related field, or a GPA below 3.0. Guidelines:
- Recommendations will only be accepted through the online application (no paper recommendations will be accepted).
- We prefer that recommenders be employers who are able to render an opinion on the basis of close, current and sustained observation. We strongly urge (but do not require) that one recommendation be from your direct supervisor.
- Recommendations from friends, family members, acquaintances and other sources unable to evaluate professional or academic qualifications for graduate study are not acceptable.
- No more than two recommendations are needed.
- We require that recommenders submit the recommendations online (instructions to do so are provided within the online application).
- Please note that we will not receive your application until at least two registered recommenders have submitted recommendations through the online application.
All applicants must upload to the online application official transcript(s) and/or academic document(s) for every institution of higher education attended. Guidelines:
- If a transcript and diploma/degree certificate is not in English, an English translation (certified by the college or university that issued it) must be uploaded.
- The uploaded transcript and/or academic document must be from the official version of the document. An official transcript bears the original signature of the registrar and/or the original seal of the issuing institution.
- All transcripts and/or academic documents uploaded by anyone other than the Graduate School to the online application system are considered unofficial. A hard copy or electronic version coming directly from every institution will be required within the first semester.
- If personal identifying information such as a student identification number or social security number appear on the document, remove this information from the electronic version of your document or mark out the information in black ink before scanning your document.
The cross-disciplinary curriculum blends coursework from our Forestry and Natural Resources (FNR), Agricultural and Biological Engineering (ABE), Agricultural Systems Management (ASM) and Agronomy (AGRY) departments. Total credits: 12
ABE 65100 Environmental Informatics
This course will educate students in the use, manipulation and analysis of environmental data by introducing them to scripting languages (e.g., C shell, Python), data types (e.g., ASCII, binary, NetCDF), databases (e.g., XML, DBF) and data visualization software (e.g., GMT, ArcMap) as well as techniques for checking data quality, working with missing data and handling large diverse sources of time series and spatial data.
Students will manipulate, check and insert data from a variety of sources, use that data as input to distributed hydrologic model, analyze model output and learn methods for properly documenting their data use (creation of metadata) and long-term archival storage of those data. Skills learned should be applicable to most computer operating systems, but the majority of work for this class will be done within the Unix/Linux environment.
Students taking this course should have experience with one or more programming languages, including but not limited to C, Fortran, Perl, Python, Java, BASIC or two writing scripts or macros within programs such as MATLAB, S-PLUS, R or SAS.
FNR 58700 Advanced Spatial Ecology and GIS
Introduction to the principles of landscape ecology and biogeography with a laboratory devoted to the analysis of spatial data using geographic information systems (GIS) and other database tools.
Landscape ecology focuses on the important relationships of landscape structure (pattern, heterogeneity) and ecological processes (movement of animals, hydrologic dynamics) and how this information is used for natural resource management. Biogeography examines ecological patterns and processes at larger scales (generally at subcontinental to global) for the purposes of managing plants and animals of global importance.
In the last 15 years, tremendous efforts have been made to create spatial databases that help support research and management of natural resources at various scales. The lab will focus on the use and application of these databases that are common in natural resource management settings.
ASM 54000 Geographic Information System Application
This course provides an introduction to fundamentals of geographic information systems (GIS) for spatially analyzing problems related to environmental, agricultural and engineering domains. You will learn key concepts of GIS, including data sources, projections, spatial analysis methods, data and metadata creation and conceptualization framework for solving spatial problems.
GIS is a powerful tool and most students find it to be interesting and enjoyable. The course will use Esri ArcGIS Pro software. At the end of the course we expect you to be an informed GIS user, as well as being reasonably competent using ArcGIS Pro.
AGRY 54500 Remote Sensing of Land Resources
This course introduces students to the principles of remote sensing and teaches methods for analysis and interpretation of remotely sensed data. The emphasis of the first half of the course is on passive optical technology and methodology for analysis of remotely sensed data.
The second half of the course introduces other sensing technologies and their application to the remote observation of soil, vegetation and water resources (together referred to as land resources) by airborne (manned and unmanned) and space-based sensors.
Students will be introduced to the latest developments in instrumentation and information technology in remote sensing and will learn how to utilize remotely sensed data to support research and decision making in agriculture, science and engineering.
NOTES AND CONDITIONS - PLEASE READ
1 Source: U.S. News & World Report (tie), on the internet at www.usnews.com/best-graduate-schools/top-engineering-schools/biological-agricultural-rankings.
2 Source: PrecisionAg.com, on the internet at www.precisionag.com/market-watch/25-best-colleges-for-precision-agriculture/.
3 Source: The Wall Street Journal/Times Higher Education, on the internet at www.timeshighereducation.com/student/best-universities/best-public-universities-united-states.
4 Source: U.S. News & World Report, on the internet at www.usnews.com/best-colleges/rankings/national-universities/innovative.
5 Tuition and fees are subject to increase based on approval by the Purdue University Board of Trustees. Application fee and textbooks are not included in the cost of tuition.
6 Plan of study subject to change.