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⇱ Modeling Climate Anomalies with Statistical Analysis | Coursera

Modeling Climate Anomalies with Statistical Analysis

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Modeling Climate Anomalies with Statistical Analysis

Included with

Gain insight into a topic and learn the fundamentals.
Intermediate level

Recommended experience

7 hours to complete
Flexible schedule
Learn at your own pace
Gain insight into a topic and learn the fundamentals.
Intermediate level

Recommended experience

7 hours to complete
Flexible schedule
Learn at your own pace

What you'll learn

  • Visualize and interpret climate anomalies using statistical analysis.

  • Use APIs to import climate data from government portals.

  • Visualize data in Python with matplotlib. 

Details to know

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Assessments

3 assignments

Taught in English
Build toward a degree

Build your subject-matter expertise

This course is part of the Modeling and Predicting Climate Anomalies Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
  • Learn new concepts from industry experts
  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
  • Earn a shareable career certificate

There are 3 modules in this course

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.

This course can be taken for academic credit as part of CU Boulder’s Master of Science in Data Science (MS-DS) degree offered on the Coursera platform. The MS-DS is an interdisciplinary degree that brings together faculty from CU Boulder’s departments of Applied Mathematics, Computer Science, Information Science, and others. The degree offers targeted courses, short 8-week sessions, and pay-as-you-go tuition. Admission is based on performance in three preliminary courses, not academic history. CU degrees on Coursera are ideal for recent graduates or working professionals. Learn more: MS in Data Science: https://www.coursera.org/degrees/master-of-science-data-science-boulder

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.

What's included

4 videos5 readings1 assignment1 programming assignment

4 videos•Total 55 minutes
  • Introduction to the Course•3 minutes
  • Meet the Instructor•1 minute
  • Introduction to Pandas for Data Loading and Exploration•26 minutes
  • Introduction to Matplotlib and Seaborn for Data Visualization•25 minutes
5 readings•Total 46 minutes
  • Course Updates and Accessibility Support•1 minute
  • Earn Academic Credit for your Work!•10 minutes
  • Course Support•10 minutes
  • Pandas•15 minutes
  • Course Assignments with Jupyter•10 minutes
1 assignment•Total 15 minutes
  • Pandas and Matplotlib•15 minutes
1 programming assignment•Total 30 minutes
  • Introduction to Pandas and Matplotlib•30 minutes

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.

What's included

4 videos6 readings2 assignments

4 videos•Total 32 minutes
  • Introduction to APIs•9 minutes
  • Introduction to NOAA Website for Data Collection•9 minutes
  • Introduction to USGS Website and Available Data•6 minutes
  • Collecting GWL Data FROM USGS via NWIS•8 minutes
6 readings•Total 105 minutes
  • APIs, JSON, and Python Requests•15 minutes
  • API Hands-On (Lab Activity)•30 minutes
  • NOAA API and Available Data•10 minutes
  • Datasets by USGS•10 minutes
  • Methods and Datasets via NWIS•10 minutes
  • Access Streamflow Data via NWIS (Lab Activity)•30 minutes
2 assignments•Total 16 minutes
  • API Hands-On•15 minutes
  • Access Streamflow Data via NWIS•1 minute

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.

What's included

4 videos1 programming assignment1 peer review1 discussion prompt1 ungraded lab

4 videos•Total 28 minutes
  • Visualizing & Analyzing Air Temperature Data•7 minutes
  • Visualizing & Analyzing Precipitation Data•5 minutes
  • Visualizing & Analyzing GWL Data•6 minutes
  • Visualizing & Analyzing Soil Temperature and Moisture Data•9 minutes
1 programming assignment•Total 45 minutes
  • Analyzing Climate Data•45 minutes
1 peer review•Total 15 minutes
  • Visualizing Climate Data•15 minutes
1 discussion prompt•Total 10 minutes
  • Anomalies and Climate Data•10 minutes
1 ungraded lab•Total 45 minutes
  • Visualizing Climate Data•45 minutes

Earn a career certificate

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Build toward a degree

This course is part of the following degree program(s) offered by University of Colorado Boulder. If you are admitted and enroll, your completed coursework may count toward your degree learning and your progress can transfer with you.¹

Instructor

University of Colorado Boulder
5 Courses•4,814 learners

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Frequently asked questions

To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.

When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

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