Guided Project: Get Started with Data Science in Agriculture
Data science has revolutionized the way farmers and agricultural professionals approach their work. This guided project introduces the use of Python data analysis tools, such as pandas and seaborn, to help farmers make data-driven decisions using soil, water, and economic data. This project provides an overview of the data science process and how it can be applied to agriculture. ▼
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Course Feature
Cost:
Free
Provider:
Edx
Certificate:
Paid Certification
Language:
English
Start Date:
Self paced
Course Overview
❗The content presented here is sourced directly from Edx platform. For comprehensive course details, including enrollment information, simply click on the 'Go to class' link on our website.
Updated in [February 21st, 2023]
Data science tools have revolutionized the way farmers and agricultural professionals approach their work. Python data analysis tools, such as pandas and seaborn, enable farmers to make data-driven decisions using soil, water, and economic data accounts. Pandas is a Python library used to simplify handling large sets of data. Seaborn is a data visualization library used to quickly create graphs.
This hands-on guided project will prepare you to handle agricultural datasets using these Python tools. You will develop job-ready skills, like how to download, prepare, analyze, and visualize data using Python libraries, including pandas and seaborn. You will learn how to build a trend line in order to forecast future trends, and finally, you will learn how to create interactive maps which show data change over time.
You will be provided with access to a Cloud-based IDE, which has all of the required software, including Python, pre-installed. All you need is a recent version of a modern web browser to complete this project.
(Please note that we obtained the following content based on information that users may want to know, such as skills, applicable scenarios, future development, etc., combined with AI tools, and have been manually reviewed)
This course provides learners with the opportunity to gain hands-on experience in using Python data analysis tools to make data-driven decisions in the agricultural field. Learners will develop job-ready skills such as downloading, preparing, analyzing, and visualizing data using Python libraries, including pandas and seaborn.
Possible Development Paths include becoming a data analyst in the agricultural field, a data scientist in the agricultural field, or a data visualization specialist in the agricultural field.
Learning Suggestions for learners include taking courses in data analysis, data science, and data visualization. Additionally, learners should become familiar with the Python programming language and the pandas and seaborn libraries. They should also practice using the Cloud-based IDE provided in the course.
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