RESEARCH COMPUTING IN ATMOSPHERIC AND OCEANIC SCIENCES

Name: RESEARCH COMPUTING IN ATMOSPHERIC AND OCEANIC SCIENCES
Availability: OutOfStock
Rating: 4.4 (74 reviews)

ATMOCN 573

과목 설명

Hands-on introduction to open-source research computing tools commonly used in the atmospheric and oceanic sciences. Covers Python basics, including standard data structures, environments, and packages that are useful for analyzing and visualizing a variety of observational and computational atmospheric and oceanic science datasets. Additional open-source tools for version control, sharing code, and collaborating on analysis are also introduced and open science best practice are discussed.

선수과목

(MATH 234 and COMPSCI 220 ) or graduate/professional standing

충족 요건

ATMOCN 575

학점

미보고

개설 시기

미보고

평점

3.68

4.46% 과거 데이터 대비

수료율

100%

과거 데이터 대비 변화 없음

A 비율

63.16%

37.46% 과거 데이터 대비

학급 규모

28.38% 과거 데이터 대비

Cumulative Grade Distribution

강사 (2026 Summr)

다음 사이트의 평점순으로 정렬 Rate My Professors

유사 과목

FOUNDATIONS OF ATMOSPHERIC AND OCEANIC SCIENCES RESEARCH

ATMOCN 901

Discussions on adapting to graduate school and graduate-level research, history and future of discipline, research ethics, issues of diversity and inclusion.

RESEARCH

ATMOCN 990

Research with atmospheric and oceanic science faculty advisors.

RESEARCH ADVANCES IN THE ATMOSPHERIC AND OCEANIC SCIENCES

ATMOCN 903

Discussions on philosophy of science, literature review, development of ideas in Atmospheric and Oceanic Sciences, training in proposal writing, and preparation for Ph.D. dissertation proposal in advance of preliminary exam.

EXPLORATIONS OF ATMOSPHERIC AND OCEANIC SCIENCES

ATMOCN 201

Exploration of a field within atmospheric and oceanic sciences. Exposure to scientific principles, current findings, and career routes as it applies to topics such as meteorology, weather systems and weather forecasting, climate and climate change, atmospheric satellite remote sensing, oceanography, and professional careers in the discipline.

ADVANCED CLIMATOLOGICAL ANALYSIS

ATMOCN 775

Application and analysis of advanced statistical, mathematical, and machine learning tools in Atmospheric, Oceanic, and Climate Sciences. Emphasizes application of statistical techniques to synthetic and real data; analysis of existing research in Atmospheric, Oceanic, and Climate Sciences; and exploration of new applications of statistical and machine learning techniques in relevant scientific literature. Knowledge of basic statistical methods and statistical programming [such as those introduced in 575] is required