16 courses with the subject DIGA, each shown exactly as we captured it from the college's catalog, with every element we hold. Where the wording looks broken, that is our reading of the catalog, not the college's text.
DIGA 605Fundamentals of Geographic Information Systems (GIS) (3 cr.)
This course introduces the concepts of spatial data creation, editing, and analysis using GIS software. Emphasis is placed on spatial concepts and understanding and utilizing standard operating procedures. Topics covered include coordinate systems, data creation, derivation, editing, metadata, proximity and overlay analysis, and cartography. Technical proficiency is a primary objective of the course, reinforced by significant practical exercises utilizing GIS software. Examples of how the geospatial industry provides location intelligence to a variety of disciplines are explored.
DIGA 608Cloud Architecture and Web-Programming (3 cr.)
This course introduces students to effective use of the internet and technology for sharing spatial and non-spatial data, visualizations, and interactive applications via the web. The course examines cloud data architecture for managing, analyzing, and serving data over the Internet. Students are introduced to web-based programming languages and interfaces (APIs) for presentation, visual analysis/intelligence, and communication/presentation of data via the web.
DIGA 610Relational Database Design and Administration (3 cr.)
This course follows a logical progression from basic data types into normalization and relational database design. Stages of database design are addressed as well as techniques for documenting database workflows and schemas. The course explores implementing methods to promote spatial and tabular data integrity and facilitate analytical workflows. Structured query language (SQL) for querying, modifying, and managing data is also covered. The course includes enterprise database topics such as permissions, replication, and performance optimization.
DIGA 615Data Acquisition and Location of Things (3 cr.)
This course introduces methods centered around data collection in a geo-relational context. Data collection topics include applications centered around mobile global positioning systems (GPS), land and parcel data, sensors and drone data acquisition, and data generated within the Internet of Things (IoT). The course discusses concepts in understanding workflow, critical appraisal of data, and applications for various industries.
The course utilizes data processing requirements necessary to implement technology-based analytics. The course explores strengths and limitations of various data formats to make better decisions. The importance of structured and unstructured data formats as well as performing methods of data extraction, transformation, and loading are covered. Data wrangling methodologies explore constructing custom data pipelines to support efficient analysis. These methods include cleaning, filtering, standardizing, and categorizing data. Processes to review data for accuracy, consistency, and completeness are covered as well as techniques to mitigate error and improve data integrity. The course also investigates legal and ethical considerations of data management.
DIGA 635Data Modeling and Forecasting with Geo-AI (Artificial Intelligence) (3 cr.)
This course promotes problem solving, data modeling, and critical thinking related to data intelligence, data classifications, and predictive analysis. The course explores designing conceptual models to effectively explore and forecast data unique to spatial and other analytical challenges. The course addresses challenges in various disciplines. Problem-solving approaches are accomplished using an array of technology and software options.
DIGA 640Technical Research Writing, Design, and Ethics (3 cr.)
This course examines effective research methodologies used in understanding requirements and expectations associated with the capstone project. This includes formatting and graphic requirements, literature review development, proposal design, and expectations of the final project paper. Additional emphases include applied ethics of technology use and research design. The course prepares and provides progress for students on their capstone project.
This course provides an introduction to the fundamental principles and applications of spatial ecology, emphasizing the spatial distribution and dynamics of organisms across different scales. Students explore how ecological processes interact with the physical environment, shaping patterns of biodiversity and ecosystem function. Students develop skills in mapping, spatial analysis, and remote sensing techniques essential for effective conservation planning through hands-on projects. This course integrates theory with practical applications, preparing students to contribute to sustainable resource management efforts using modern technological approaches.
DIGA 660Python Programming for Technology and Data Science (3 cr.)
The course focuses on core programming concepts such as classes and objects, controlling flow, batch processing, and error handling while working in the context of data processing, analysis, and visualization. The course explores a variety of Python packages and integration for project development. Using Python to automate workflows and create custom visualizations is discussed, and students are able to explore tabular data, spatial data, cybersecurity, and data science applications of Python.
DIGA 665Cloud Architecture for Data Science and Visualization (3 cr.)
This course introduces students to effective use of the internet and technology for sharing spatial and non-spatial data, visualizations, and interactive applications via the web. The course examines cloud data architecture for managing, analyzing, and serving data over the Internet. Students are introduced to web-based programming languages and interfaces (APIs) for presentation, visual analysis/intelligence, and communication/presentation of data via the web.
