technifyed

Udacity via Udacity

Data Wrangling with MongoDB Free Course

4.36 ratings at Udacity

Overview

Data Scientists spend most of their time cleaning data. In this course, you will learn to convert and manipulate messy data to extract what you need.

Syllabus 11

  1. Data Extraction Fundamentals

    Review the fundamentals of tabular data formats CSV and Excel and learn about the JSON format.

  2. Problem Set: Data Extraction Fundamentals

    Gain experience working with .csv files and wrangling JSON.

  3. Data in More Complex Formats

    Start working with XML and learn how to use BeautifulSoup to scrape web pages.

  4. Problem Set: Data in More Complex Formats

    Practice working with XML and parsing HTML with BeautifulSoup.

  5. Data Quality

    Learn about what can make data "dirty" and find out how you can audit your data for quality.

  6. Problem Set: Data Quality

    Practice auditing and cleaning dirty data.

  7. Working with MongoDB

    Find out how to use MongoDB to store and query your data.

  8. Problem Set: Working with MongoDB

    Practice wrangling data and inserting data into MongoDB.

  9. Analyzing Data

    Learn how to create more sophisticated MongoDB queries using pipelines and operators.

  10. Problem Set: Analyzing Data

    Gain experience with MongoDB pipelines and operators.

  11. Case Study: OpenStreetMap Data

    Go through a case study showing how to audit, clean and prepare OpenStreetMap data for insertion into a database.

Advantages and disadvantages

Advantages

  • Completely free.
  • Self-paced: start any time.
  • A clear syllabus (11 parts) you can see before you start.

Disadvantages

  • Short (5 minutes): an overview, not deep coverage.

Some points apply to every course of this kind; see how we rank.

Free

  • Free: Sign up on Udacity to start.
  • Certificate: Free courses give no certificate.

Taught by

  • Gundega Dekena
  • Shannon Bradshaw

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