DATA VISUALIZATION FOR AGRICULTURAL AND LIFE SCIENCES

Name: DATA VISUALIZATION FOR AGRICULTURAL AND LIFE SCIENCES
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AAE 337

과목 설명

Introduction to principles data visualization with applications in agricultural and life sciences. Learn to effectively communicate quantitative data via visual graphics and critically evaluate graphical data in the news and popular media. Develop practical data visualization skills in Microsoft-based programs Excel and Power BI, including tables, maps, dashboards, charts and other graphics that display trends and relationships within and between quantitative variables.

선수과목

AAE 335 or GENBUS 106

충족 요건

This course does not satisfy any prerequisites.

학점

미보고

개설 시기

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평점

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변화 계산 불가

수료율

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변화 계산 불가

A 비율

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변화 계산 불가

학급 규모

미보고

과거 데이터 대비 변화 없음

데이터 없음

강사 (2026 Summr)

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유사 과목

DATA VISUALIZATION FOR ECONOMISTS

ECON 315

Introduction to the fundamental concepts of economic data visualization and analysis. Develop a toolkit of skills to visualize, interpret, and communicate data. After examining the fundamentals of data visualization, emphasis is on methods using Tableau to design and develop dashboards, graphs, and charts to ease quick and accurate interpretation of economic relationships. Move beyond tabular results to display and demonstrate the findings of economic research.

DATA SCIENCE FOR AGRICULTURAL AND APPLIED ECONOMICS

AAE 718

Introduction to data and data processing using both Python and R programming languages. Concepts covered include loading data, data acquisition, cleaning data, visualization/exploring data, and storing data.

CONCEPTS AND TOOLS FOR DATA ANALYSIS AND VISUALIZATION

JOURN/LIS 677

An introduction to information and data visualization: introduction to major concepts, instruction in specific tools for data analysis and visualization, and application of skills in a final project.

DATA VISUALIZATION

COMPSCI 765

Principles of the visual presentation of data. Survey of Information Visualization, Scientific Visualization, and Visual Analytics. Design and evaluation of visualizations and interactive exploration tools. Introduction to relevant foundations in visual design, human perception, and data analysis. Encodings, layout and interaction. Approaches to large data sets. Visualization of complex data types such as scalar fields, graphs, sets, texts, and multi-variate data. Use of 2D, 3D and motion in data presentations. Implementation issues.

INTRODUCTORY DATA SCIENCE FOR THE AGRICULTURAL AND LIFE SCIENCES

BSE 380

Agricultural and life scientists need to creatively apply physical, chemical, and biological principles to address technical, business, and environmental challenges. Many of these challenges involve numerical analyses, including the interpretation of large datasets. The fundamentals of computer coding using numerical software will be taught, using real-world data science challenges from the agricultural and life sciences.