Build documented research-computing workflows
Computing, Communication & Enterprise · Data Science & Research Computing
RC-310Research Computing & Visualization
Uses computational notebooks, scripting, visualization, statistical workflows, and research software practices to analyze and communicate complex evidence.
Course outcomes
What students develop
Select visual forms appropriate to evidence and audience
Automate repeatable analysis and reporting
Evaluate computational results through validation and peer review
Course content
Topics and questions
- Notebook and script workflows
- Data transformation
- Statistical and scientific computing
- Visualization and interaction
- Packaging, documentation, and reproducibility
Methods & resources
Tools and environments
- Python or R
- Notebook environment
- Visualization libraries
- Version control
Evaluation
Demonstration of learning
- Analysis notebooks
- Visualization critique
- Reproducible final project
Program relationships
Where this course fits
Core
Geography, Geospatial Intelligence & Spatial Systems
Combines human and physical geography with GIS, remote sensing, LiDAR, cartography, spatial data, and field interpretation.
Core
Integrative Biosciences & Genomic Methods
Connects biological foundations to genetics, genomics, evolution, physiology, ecology, computation, and laboratory practice.
Core
Genomics, Epigenetics & Biological Systems
Advanced study in genomic variation, gene regulation, long-read sequencing, bioinformatics, environment, and biological systems.
Core
Photonics, Measurement & Materials
Advanced work in optical sensing, spectroscopy, imaging, materials characterization, instrumentation, calibration, and analytical systems.
Core
Computational Intelligence & Data Systems
Combines computer science, AI, data engineering, research computing, visualization, systems thinking, and responsible application.
Core
Applied AI, Research Computing & Visualization
Advanced computational methods for research, data-intensive inquiry, AI systems, visualization, reproducibility, and decision environments.
Core
Computational Systems, Communication & Enterprise
Original research on computational systems and the institutions, communications, markets, and human environments through which they operate.
Core
GIS & Spatial Research
Cartography, GIS, LiDAR, remote sensing, spatial analysis, data quality, and research communication.
Core
Nanopore Genomics & Long-Read Analysis
Long-read sequencing, quality control, alignment, assembly, variant analysis, reproducibility, and genomic data stewardship.
Core
Archaeometry & Materials Analysis
Materials characterization, XRF, calibration, quality control, archaeological context, provenance reasoning, and technical reporting.
Core
Remote Sensing Instrumentation
Optical and electronic sensors, calibration, data acquisition, earth observation, signal quality, and field deployment.
Core
Research Computing & Visualization
Programming, reproducible analysis, data systems, scientific visualization, computational notebooks, and research software practice.
Core
Complex Adaptive Systems
Emergence, feedback, adaptation, networks, agent interaction, simulation, resilience, and cross-scale systems reasoning.
Core
Data Stewardship & Reproducible Research
Data structure, metadata, provenance, validation, versioning, privacy, repositories, and reproducible computational workflows.
Core
Research Data Stewardship
A compact credential in reproducible data organization, metadata, documentation, preservation, access control, and responsible research reuse.
Core
Long-Read Genomics
Run planning, long-read sequencing, quality control, alignment, analysis, reproducibility, and technical reporting.
Core
Research Computing Bootcamp
A concentrated workflow in programming, data management, notebooks, visualization, version control, and reproducible research.
Core
Geospatial Intelligence & LiDAR
Point clouds, terrain models, spatial analysis, cartographic communication, and decision-ready geospatial products.
Course inquiry
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