This course introduces the use of statistical analysis in Python programming to study and model climate data, specifically with the SciPy and NumPy package. Topics include data visualization, predictive model development, simple linear regression, multivariate linear regression, multivariate linear regression with interaction, and logistic regression. Strong emphasis will be placed on gathering and analyzing climate data with the Python programming language.
Modeling Climate Anomalies with Statistical Analysis
Modeling Climate Anomalies with Statistical Analysis
位教师：Osita Onyejekwe
访问权限由 New York State Department of Labor 提供
您将学到什么
Visualize and interpret climate anomalies using statistical analysis.
Use APIs to import climate data from government portals.
Visualize data in Python with matplotlib.
您将获得的技能
- Anomaly Detection
- Data Visualization
- Data Visualization Software
- Application Programming Interface (API)
- Time Series Analysis and Forecasting
- Regression Analysis
- Matplotlib
- Pandas (Python Package)
- Data Science
- Statistical Modeling
- Data Manipulation
- Data Collection
- Data Analysis
- Statistical Analysis
- 技能部分已折叠。显示 7 项技能，共 14 项。
要了解的详细信息
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作业
3 项作业
授课语言：英语（English）
了解顶级公司的员工如何掌握热门技能
积累特定领域的专业知识
本课程是 Modeling and Predicting Climate Anomalies 专项课程 专项课程的一部分
在注册此课程时，您还会同时注册此专项课程。
- 向行业专家学习新概念
- 获得对主题或工具的基础理解
- 通过实践项目培养工作相关技能
- 获得可共享的职业证书
该课程共有3个模块
In this module, we'll start with an introduction to the Python library, Pandas. You'll also learn the fundamentals of data visualization using Matplotlib, a powerful library for creating insightful plots and graphs. At the end of the module you will practice manipulating data with Pandas and visualizing your findings using Matplotlib.
涵盖的内容
4个视频5篇阅读材料1个作业1个编程作业
In this module, you will be introduced to APIs and the Python requests library, enabling you to connect and interact with web-based data services. You'll explore climate data sources from NOAA, USGS, and NWIS, and practice accessing data using the dataretrieval library.
涵盖的内容
4个视频6篇阅读材料2个作业
In this module, you will delve into visualizing and analyzing various climate data sets, including air temperature, precipitation, groundwater level (GWL), and soil temperature and moisture. You will learn to create informative visualizations to identify patterns, trends, and anomalies in the data.
涵盖的内容
4个视频1个编程作业1次同伴评审1个讨论话题1个非评分实验室
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攻读学位
课程 是 University of Colorado Boulder提供的以下学位课程的一部分。如果您被录取并注册，您已完成的课程可计入您的学位学习，您的学习进度也可随之转移。
位教师
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University of Colorado Boulder
University of Colorado Boulder
University of Colorado Boulder
University of Colorado Boulder