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Data Wrangling with MongoDB
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Tags: data extraction / databases / MongoDB
“In this course, we will explore how to wrangle data from diverse sources and shape it to enable data-driven applications. Some data scientists spend the bulk of their time doing this!
Students will learn how to gather and extract data from widely used data formats. They will learn how to assess the quality of data and explore best practices for data cleaning. We will also introduce students to MongoDB, covering the essentials of storing data and the MongoDB query language together with exploratory analysis using the MongoDB aggregation framework.
This is a great course for those interested in entry-level data science positions as well as current business/data analysts looking to add big data to their repertoire, and managers working with data professionals or looking to leverage big data.”
This course is part of the Udacity Data Analyst Nanodegree and consists of the following lessons:
- Data Extraction Fundamentals
- Data in More Complex Formats
- Data Quality
- Working with MongoDB
- Analyzing Data
- Case Study – OpenStreetMap Data
Recommended Prerequisites: "Programming experience in Python or a willingness to read a little documentation to understand examples and exercises throughout the course. The ability to perform rudimentary system administration on Windows or Unix. At least some experience using a unix shell or Windows PowerShell will be helpful, but is not required. No prior experience with databases is needed."
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