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Term: Spring 2024

AZTransfer SUN courses only

INF 110 - Discovering Informatics: This course provides learning opportunities in the foundations of informatics, an interdisciplinary area fusing computer science, programming, and data analysis skills used to solve problems in any field, particularly the natural sciences, business, and the arts. This course will particularly focus on problems drawn from areas that provide significant benefits to human and environmental health. The course does not require any prior experience in programming and is intended for students of any background and major. This course also provides an opportunity for students to explore their interest in topics that are central to the Bachelor of Science in Informatics, Computer Science, and Applied Computer Science programs, and therefore be more informed in considering further study in one of these programs. Letter grade only.
INF 199 - Special Topics: Foundations of intellectual inquiry. In-depth study of a substantive problem. Letter grade only. May be repeated for up to 9 units of credit.
INF 205 - Introduction To Ecoinformatics: This class will introduce a range of ecoinformatic techniques that will show how informatics can help address the world's key environmental problems. There are four key modules each teaching a different ecoinformatic skill: 1) learn about climate change and energy using simple quantitative techniques like box models; 2) apply simple programming technique towards biodiversity conservation using simple individual based models; 3) learn simple data collection field techniques; 4) learn simple remote sensing techniques with the Google Earth engine. Letter grade only.
INF 299 - Special Topics: In-depth study of an aspect, concept, or problem. Letter grade only. May be repeated for up to 9 units of credit.
INF 376 - Research Initiation: A structured introduction to interdisciplinary research in informatics and one of the Bachelor's of Science in Informatics (BSI) emphasis areas. Topics include research and lab techniques, experimental design, and team work in a lab context. Letter grade only.
INF 386 - Research Planning: A structured interdisciplinary research experience that focuses on planning research in informatics and one of the BSI emphasis areas. Topics include research and lab techniques, experimental design, and team work in a lab context. Letter grade only.
INF 399 - Special Topics: In-depth study of an aspect, concept, or problem. Letter grade only. May be repeated for up to 9 units of credit.
INF 408 - Fieldwork Experience: Individualized supervised field experience in an appropriate agency or organization. Pass/Fail only. No repeat limit.
INF 413 - Cancer Evolution And Ecology: The purpose of this course is to familiarize informatics students with computational models that explore evolutionary and ecological aspects of cancer and predict tumor progression and patient outcomes. Students access primary literature, work with computational models, and practice effective communication to understand evolutionary and ecological models of cancer, in which the evolutionary forces of drift and selection affect the fate of somatic mutations, and tumor cells compete for resources with and evade protective and cooperative strategies of normal cells. Examines clinical applications of evolutionary and ecological theories of cancer as well as adaptations for cancer suppression across the tree of life. Co-convened with INF 513. Letter grade only.
INF 414 - Modeling The Spread Of Infectious Disease: This course will provide students with a basic understanding of disease modeling. We will derive and simulate fundamental insights about infectious disease dynamics, including the topics of predicting the size of epidemics, understanding disease cycles, and simulating spatially-explicit disease models. Throughout, we will reinforce quantitative insights with biological concepts, computer-based assignments, and relevant readings from the literature. Co-convened with INF 514. Letter grade only.
INF 415 - Comparative Genomics: Emphasis on the analysis of genomic sequences, including sequencing technologies, genome assembly, functional and structural predictions, and comparisons at macroevolutionary timescales in a phylogenetic context. Special emphasis is on building practical skills in computational biology. Classes will consist of lectures, student led discussions of primary literature, and computational labs. Co-convened with INF 515. Letter grade only.
INF 416 - Transcriptomics: This course will prepare the student for real-world applications in RNA-Seq. We will review quantitative methods for gene transcription in a single-organism, as well as bacterial-community settings. Special emphasis will be placed on computational and statistical methods of identifying differentially expressed genes and their impact on observed phenotypes. Co-convened with INF 516. Letter grade only.
INF 421 - Mechanistic Ecological And Environmental Modeling: This class will teach a range of ecological and environmental modelling techniques from simple back of the envelope climate models, to simple models, to more complex models, and spatial modelling. We will start by creating a simple climate model to calculate Earth's temperature. Next, we will learn to create and test a simple mechanistic models with Matlab. In part three, we will run and modify complex mechanistic models such as the land model component of a Global Circulation Model (GCM) and the Madingley model, the first global model to incorporate both animal and plant ecology. Finally, we will learn spatial modelling using the Google Earth engine which combines a multi-petabyte catalog of satellite imagery and geospatial datasets with planetary-scale analysis capabilities. The class will serve as an introduction to all of these techniques. Overall, it will be a practical, results driven modelling class that will help advanced undergrad students learn new methods and techniques. Co-convened with INF 521. Letter grade only.
INF 422 - Ecoinformatics Tools And Data: Surveys data collection tools and products used by ecoinformaticists, along with introductions to the organizations and professionals that build and utilize those tools and products. Co-convened with INF 522. Letter grade only.
INF 423 - Informatics For Community Food, Energy And Water Systems: This course employs the FEWSION for Community Resilience (F4R) process and a related curriculum to engage students in collecting data on the physical structure and stakeholder networks of their local critical infrastructure Food, Energy, and Water (FEW) systems in Flagstaff. Students will network with community leaders and stakeholders, NGO's, private sector FEW businesses, utilities, emergency managers, and volunteers who contribute to the successful operation of the system. Students will employ field work to construct a detailed map of the system and contribute to an ongoing annual effort to quantify Flagstaff's FEW systems. Training on software and data systems specialized for FEW supply chains will be delivered. The sustainability, equity, and security of the system will be studied and measured. Student projects will employ these relationships and data to study how policy and action can improve the local FEW system. Co-convened with INF 523. Letter grade only.
INF 450 - Survey In Ecoinformatics Tools: This course surveys data collection tools and products used by ecoinformaticists, along with introductions to the organizations and professionals that build and utilize those tools and products. Co-convened with INF 550. Letter grade only.
INF 476C - Research Design: Application of research planning and design to the development of a culminating research project in informatics with a faculty mentor. Part of a two course Capstone sequence. Topics include research planning, software and experimental design, project management, teaming, testing, analysis, and documentation. Letter grade only.
INF 485 - Undergraduate Research: Original research under the supervision of a research adviser. Department consent required. Pass/Fail or Letter grade. May be repeated for up to 12 units of credit.
INF 486C - Capstone Experience: Culminating capstone experience in interdisciplinary research related to informatics with a faculty mentor. Topics include research planning, software and experimental design, project management, teaming, testing, analysis, and documentation. Letter grade only.
INF 499 - Special Topics: Examines recent trends and investigations in a selected area. Letter grade only. May be repeated for up to 9 units of credit.
INF 501 - Research Methods In Informatics And Computing: Introduction to research areas in informatics and computing and overview of critical research design concerns, research methods, and literature review techniques. Letter grade only.
INF 502 - Software Development Methodologies: Study of advanced programming techniques, overview of software engineering principles, and study and project-based application of agile software development methods and tools. Letter grade only.
INF 503 - Large-scale Data Structures And Organization: Study of advanced techniques for the design, implementation, and testing of data structures and formats for large-scale problems associated with informatics applications. Letter grade only.
INF 504 - Data Mining And Machine Learning: Study of machine learning principles with a focus on uncertainty modeling, Bayesian inference, graphical models for complex inference problems, computational inference including message passing and Markov Chain Monte Carlo, and open research questions. Letter grade only.
INF 511 - Modern Regression I: Matrix-based coverage of linear statistical models for independent data from frequentist and Bayesian perspectives, including regression, analysis of variance (ANOVA), estimation, testing, selection, diagnostics, and associated random variables and probability distributions. Letter grade only.
INF 512 - Modern Regression II: Matrix-based coverage of linear statistical models for dependent data. Non-linear models for independent and dependent data. Includes estimation, testing and diagnostics within the context of generalized linear models, non-linear models, linear mixed models, generalize linear mixed models, non-linear mixed models. Letter grade only.
INF 513 - Cancer Evolution And Ecology: The purpose of this course is to familiarize informatics students with computational models that explore evolutionary and ecological aspects of cancer and predict tumor progression and patient outcomes. Students access primary literature, work with computational models, and practice effective communication to understand evolutionary and ecological models of cancer, in which the evolutionary forces of drift and selection affect the fate of somatic mutations, and tumor cells compete for resources with and evade protective and cooperative strategies of normal cells. Examines clinical applications of evolutionary and ecological theories of cancer as well as adaptations for cancer suppression across the tree of life. Co-convened with INF 413. Letter grade only.
INF 514 - Modeling The Spread Of Infectious Disease: This course will provide students with a basic understanding of disease modeling. We will derive and simulate fundamental insights about infectious disease dynamics, including the topics of predicting the size of epidemics, understanding disease cycles, and simulating spatially-explicit disease models. Throughout, we will reinforce quantitative insights with biological concepts, computer-based assignments, and relevant readings from the literature. Co-convened with INF 414. Letter grade only.
INF 515 - Comparative Genomics: Emphasis on the analysis of genomic sequences, including sequencing technologies, genome assembly, functional and structural predictions, and comparisons at macroevolutionary timescales in a phylogenetic context. Special emphasis is on building practical skills in computational biology. Classes will consist of lectures, student led discussions of primary literature, and computational labs. Co-convened with INF 415. Letter grade only.
INF 516 - Transcriptomics: This course will prepare the student for real-world applications in RNA-Seq. We will review quantitative methods for gene transcription in a single-organism, as well as bacterial-community settings. Special emphasis will be placed on computational and statistical methods of identifying differentially expressed genes and their impact on observed phenotypes. Co-convened with INF 416. Letter grade only.
INF 521 - Mechanistic Ecological And Environmental Modeling: This class will teach a range of ecological and environmental modelling techniques from simple back of the envelope quantitative techniques, to simple models, to more complex models, and spatial modelling. Specifically, in the first part, we will learn quantitative techniques from the book "Consider a spherical cow" and solve complex questions with back of the envelop techniques. Next, we will learn to create and test a simple mechanistic models with Matlab. In part three, we will run and modify complex mechanistic models such as the land model component of a Global Circulation Model (GCM) and the Madingley model, the first global model to incorporate both animal and plant ecology. Finally, we will learn spatial modelling using the Google Earth engine which combines a multi-petabyte catalog of satellite imagery and geospatial datasets with planetary-scale analysis capabilities. The class will serve as an introduction to all of these techniques. Overall, it will be a practical, results driven modelling class that will help graduate students learn new methods and techniques that can be applied to their dissertation research. Co-convened with INF 421. Letter grade only.
INF 522 - Ecoinformatics Tools And Data: Surveys data collection tools and products used by ecoinformaticists, along with introductions to the organizations and professionals that build and utilize those tools and products; builds applied skill in using those tools for the purpose of conducting graduate research. Co-convened with INF 422. Letter grade only.
INF 523 - Informatics For Community Food, Energy And Water Systems: This course employs the FEWSION for Community Resilience (F4R) process and a related curriculum to engage students in collecting data on the physical structure and stakeholder networks of their local critical infrastructure Food, Energy, and Water (FEW) systems in Flagstaff. Students will network with community leaders and stakeholders, NGO's, private sector FEW businesses, utilities, emergency managers, and volunteers who contribute to the successful operation of the system. Students will employ field work to construct a detailed map of the system and contribute to an ongoing annual effort to quantify Flagstaff's FEW systems. Training on software and data systems specialized for FEW supply chains will be delivered. The sustainability, equity, and security of the system will be studied and measured. Student projects will employ these relationships and data to study how policy and action can improve the local FEW system. Co-convened with INF 423. Letter grade only.
INF 529 - Applied Remote Sensing: This course will introduce the principles and applications of digital image analysis. Students will work with various multispectral satellite images from different sensors, 3-dimensional lidar data, and airborne UAV hyperspectral images in the latest edition of ENVI software. An individual term project will be required using the techniques learned in the course and via literature review. Cross-listed with EES 529 and GSP 529. Letter grade only.
INF 550 - Advanced Survey In Ecoinformatics Tools: This course surveys data collection tools and products used by ecoinformaticists, along with introductions to the organizations and professionals that build and utilize those tools and products; builds applied skill in using those tools for the purpose of conducting graduate research. Co-convened with INF 450. Letter grade only.
INF 599 - Contemporary Developments: Examines recent trends and investigations in a selected area. Pass-Fail or letter grade, depending on department policy.
INF 601 - Professional And Career Development: Overview of academic and non-academic career opportunities in informatics and computing, career planning and search strategies, and techniques to promote success in graduate study. Pass-fail only.
INF 602 - Professional Communication: Overview of best practices for effective professional communication in informatics and computing, including oral presentations, posters, digital social media, and professional networking. Pass-fail only.
INF 603 - Proposal And Grant Preparation: Overview of best practices for effective grant proposal preparation in informatics and computing, with a focus on federal funding sources. Pass-fail only.
INF 604 - Writing Scientific Papers: The process of writing and peer review is often intimidating for many scientists, particularly those at the early-career stage. This class aims to demystify the process, and provide students with a solid skill-set that will serve them well for a life-long career in scientific research. This is a hands-on, workshop-style class that demands active participation and hard work, and challenges students to communicate their science in an engaging, memorable, and effective way. The course is intended for students pursuing a graduate degree (MS or PhD) in the sciences who are ready to put together a manuscript for submission to, and potential publication in, a peer-reviewed scientific journal. The class will emphasize the idea that good papers tell stories that engage, rather than bore, the reader. By the end of the semester, students will produce a coherent, well-structured, and polished manuscript. Instructor consent required. Letter grade only.
INF 605 - Professional Communication For Informatics And Computing: Overview of academic and non-academic career opportunities in informatics and computing, career planning and search strategies, as well as best practices for effective professional communication, including oral presentations, posters, digital social media, grant writing, and professional networking. Letter grade only.
INF 608 - Fieldwork Experience: Supervised field experience in an appropriate agency, organization, or situation. Requires department consent. Pass/Fail only. May be repeated for up to 12 units of credit.
INF 610 - Topics In Bioinformatics: Study of methods, techniques, and research areas in bioinformatics, with varying emphases between offerings. Letter grade only. May be repeated for up to 6 units of credit with different topic.
INF 611 - Topics In Population Health: Study of methods, techniques, and research areas in population health, with varying emphases between offerings. Letter grade only. May be repeated for up to 6 units of credit with different topic.
INF 612 - Topics In Healthcare Informatics: Study of methods, techniques, and research areas in healthcare informatics, with varying emphases between offerings. Letter grade only. May be repeated for up to six units of credit with different topic.
INF 620 - Topics In Remote Sensing: Study of methods, techniques, and research areas in remote sensing, with varying emphases between offerings. Letter grade only. May be repeated for up to 6 units of credit with different topic.
INF 621 - Topics In Ecological Modeling: Study of methods, techniques, and research areas in ecological modeling, with varying emphases between offerings. Letter grade only. May be repeated for up to 6 units of credit with different topic.
INF 622 - Topics In Environmental Data Analysis: Study of methods, techniques, and research areas in environmental data analysis, with varying emphases between offerings. Letter grade only. May be repeated for up to 6 units of credit with different topic.
INF 623 - Contemporary Developments: Ecoinformatics Seminar: This seminar series focuses on research topics and skills (hard and soft) training in ecological and environmental informatics ("ecoinformatics"). The overall objective of the course is to introduce students to the wide range of research that is being conducted by renowned ecoinformatics researchers within SICCS, in other departments at NAU, and outside of NAU. Letter grade only.
INF 626 - Applied Bayesian Modeling: Bayesian statistical methods for analyzing data, with emphasis on ecological and biological data. Includes Bayes rule, basic Bayesian formulation (priors, posteriors, likelihoods), single- and multiple-parameter models, hierarchical models, generalized linear models, multivariate models, mixture models, models for missing data, merging statistical and process models, overview of spatial and temporal processes, and introduction to computation methods. Letter grade only.
INF 626L - Applied Bayesian Modeling Lab: Laboratory section that accompanies INF 626. Guided, hands-on experience implementing Bayesian statistical models in JAGS and/or OpenBUGS via R. Emphasizes model building, writing code in JAGS or OpenBUGS, and writing code in R to run prepare data for the JAGS/OpenBUGS models, run the models, and evaluate model output. Letter grade only.
INF 630 - Topics In Cyber-physical Systems: Study of methods, techniques, and research areas in cyber-physical systems, with varying emphases between offerings. Letter grade only. May be repeated for up to 6 units of credit with different topic.
INF 631 - Topics In Software Engineering: Study of methods, techniques, and research areas in software engineering, with varying emphases between offerings. Letter grade only. May be repeated for up to 6 units of credit with different topics.
INF 632 - Topics In Wearable Computing: Study of methods, techniques, and research areas in wearable computing, with varying emphases between offerings. Letter grade only. May be repeated for up to 6 unis of credit with different topic.
INF 633 - Topics In Cybersecurity: Study of methods, techniques, and research areas in cybersecurity, with varying emphases between offerings. Letter grade only. May be repeated for up to 6 units of credit with different topic.
INF 638 - Cryptography And Public Key Infrastructure: Study of methods, techniques, and research areas in cryptography and public key infrastructure to strengthen cybersecurity. Letter grade only.
INF 639 - Nanomaterials And Nanoelectronics For Cybersecurity: Study of methods, techniques, and research areas in nanomaterials and nanoelectronics to strengthen cybersecurity. Letter grade only.
INF 684 - Interdisciplinary Research Rotation: Directed research and development across a selection of interdisciplinary areas in informatics and computing. Pass-fail only.
INF 685 - Graduate Research: Individualized directed research on selected topics. Pass-Fail or letter grade. May be repeated for credit.
INF 690 - Team-based Interdisciplinary Research: Students learn team-science skills for engaging in collaborative research, and for being a productive member of high-performing teams. Students work in small teams (3-4 members) to develop an interdisciplinary research proposal with an emphasis on applying informatics tools to address a biological, ecological, or environmental-motivated problem. Students learn and employ team-science approaches to developing this proposal and to conducting preliminary research that aligns with the proposal. Teams present on the proposed project, approaches, and initial results. Letter grade only.
INF 697 - Independent Study: Individualized directed study on selected topics. Note that no more than 3 units may be included on a master's plan in education. Department consent required. Pass-fail or letter grade, depending on departmental policy. No repeat limit. Please complete the Independent Study Proposal form and obtain signatures of approval BEFORE registering. https://nau.edu/wp-content/uploads/sites/26/Independent_Study_Form_FINAL-3.pdf
INF 699 - Thesis: Individualized directed research, writing, and oral defense of selected thesis topic. Pass-Fail only.
INF 799 - Dissertation: Individualized directed research, writing, and oral defense of selected dissertation topic. Pass-Fail only. May be repeated for credit.