
Learning Public Data Sets





Discover how to access and utilize public data sets to gain insights into a variety of topics, such as business, education, and health. Learn how to download the data for your own analysis and gain a better understanding of the issues.▼
Course Feature
Cost:
Free Trial
Provider:
LinkedIn Learning
Certificate:
No Information
Language:
English
Start Date:
Course Overview
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Updated in [March 06th, 2023]
This course, Learning Public Data Sets, provides an overview of how to find free, public data sources on a wide range of business, education, and health issues. It introduces a number of US government resources, ranging from the US Census Bureau to the US Patent and Trademark Office, and surveys datasets from international organisations such as the World Bank and the United Nations. The course also goes over data search engines, web services, and even language resources like Google Books' Ngram Viewer. Upon completion of this course, learners will be better equipped to locate the information they require for their scholarship and data analysis efforts.
[Applications]
Upon completing this course, learners can apply their knowledge to locate public data sets for their own research and analysis. They can use the resources and search engines discussed in the course to find data sets related to business, education, and health issues. Learners can also use the language resources, such as Google Books' Ngram Viewer, to find data sets related to language and literature. Finally, learners can use the US government resources and international organisations discussed in the course to find data sets related to global issues.
[Career Paths]
1. Data Scientist: Data Scientists are responsible for collecting, analyzing, and interpreting large amounts of data. They use their expertise in statistics, mathematics, and computer science to develop algorithms and models that can be used to make predictions and decisions. Data Scientists are in high demand, as businesses increasingly rely on data-driven decisions.
2. Data Analyst: Data Analysts are responsible for analyzing data to identify trends and patterns. They use their knowledge of statistics and data visualization to create reports and presentations that help organizations make informed decisions. Data Analysts are also responsible for developing and maintaining databases.
3. Business Intelligence Analyst: Business Intelligence Analysts are responsible for collecting, analyzing, and interpreting data to help organizations make better decisions. They use their knowledge of data analysis and visualization to create reports and presentations that help organizations understand their data and make informed decisions.
4. Data Engineer: Data Engineers are responsible for designing, building, and maintaining data systems. They use their knowledge of databases, programming languages, and software engineering to develop data pipelines and systems that can be used to store, process, and analyze large amounts of data. Data Engineers are in high demand, as businesses increasingly rely on data-driven decisions.
[Education Paths]
1. Bachelor of Science in Data Science: This degree program focuses on the development of skills in data analysis, data mining, machine learning, and other related areas. It also covers topics such as data visualization, data engineering, and data management. This degree is becoming increasingly popular as businesses and organizations are relying more and more on data-driven decisions.
2. Master of Science in Business Analytics: This degree program focuses on the application of data analytics to business decisions. It covers topics such as predictive analytics, data mining, and machine learning. It also covers topics such as data visualization, data engineering, and data management. This degree is becoming increasingly popular as businesses and organizations are relying more and more on data-driven decisions.
3. Master of Science in Data Science: This degree program focuses on the development of skills in data analysis, data mining, machine learning, and other related areas. It also covers topics such as data visualization, data engineering, and data management. This degree is becoming increasingly popular as businesses and organizations are relying more and more on data-driven decisions.
4. Doctor of Philosophy in Data Science: This degree program focuses on the development of advanced skills in data analysis, data mining, machine learning, and other related areas. It also covers topics such as data visualization, data engineering, and data management. This degree is becoming increasingly popular as businesses and organizations are relying more and more on data-driven decisions.
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