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Overview

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 also a part of our Data Analyst Nanodegree.



Why Take This Course?

At the end of the class, students should be able to:

  • Programmatically extract data stored in common formats such as csv, Microsoft Excel, JSON, XML and scrape web sites to parse data from HTML.
  • Audit data for quality (validity, accuracy, completeness, consistency, and uniformity) and critically assess options for cleaning data in different contexts.
  • Store, retrieve, and analyze data using MongoDB.



This course concludes with a final project where students incorporate what they have learned to address a real-world data analysis problem.

Syllabus

Lesson 1: Data Extraction Fundamentals

  • Assessing the Quality of Data
  • Intro to Tabular Formats
  • Parsing CSV
  • Parsing XLS with XLRD
  • Intro to JSON
  • Using Web APIs

Lesson 2: Data in More Complex Formats

  • Intro to XML
  • XML Design Principles
  • Parsing XML
  • Web Scraping
  • Parsing HTML

Lesson 3: Data Quality

  • What is Data Cleaning?
  • Sources of Dirty Data
  • Measuring Data Quality
  • A Blueprint for Cleaning
  • Auditing Validity
  • Auditing Accuracy
  • Auditing Completeness
  • Auditing Consistency
  • Auditing Uniformity

Lesson 4: Working with MongoDB

  • Data Modelling in MongoDB
  • Introduction to PyMongo
  • Field Queries
  • Projection Queries
  • Getting Data into MongoDB
  • Using mongoimport
  • Operators like $gt, $lt, $exists, $regex
  • Querying Arrays and using $in and $all Operators
  • Changing entries: $update, $set, $unset

Lesson 5: Analyzing Data

  • Examples of Aggregation Framework
  • The Aggregation Pipeline
  • Aggregation Operators: $match, $project, $unwind, $group
  • Multiple Stages Using a Given Operator

Lesson 6: Case Study - OpenStreetMap Data

  • Using iterative parsing for large datafiles
  • Open Street Map XML Overview
  • Exercises around OpenStreetMap data
  • Final Project Instructions

Taught by

Shannon Bradshaw

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Reviews for Udacity's Data Wrangling with MongoDB
3.0 Based on 9 reviews

  • 5 stars 22%
  • 4 stars 22%
  • 3 stars 22%
  • 2 star 0%
  • 1 stars 33%

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  • 1
Anonymous
1.0 10 months ago
Anonymous completed this course.
I do not know how anyone can rate the class more than 1 star. The learning materials were pathetic, and not usually on topic. I have had to go through the materials at least 3 times and consulted with Senior Data Analysts at my current employer. Their comments range from "That is completely unhelpful" to just quiet sighs.

At the start, the forums for the entire Nanodegree, were supported by mentors who would respond, often unhelpfully, but sometimes gleaning a nugget of knowledge. Late in 2017, I was informed that the forums are no longer being monitored. I was assigned a…
Was this review helpful to you? Yes
Anonymous
1.0 2 years ago
Anonymous is taking this course right now.
There are two main parts of that, SQL and MongoDB, SQL lecturer gave more details for students to understand but not for Data Wrangling and MongoDB, skipping lot of details and not well explanation for the codes. Sure that students need to invest more time to study but not recommend for those who do not have python knowledge, it's the worst course so far from data analyst nanodegree.
2 people found
this review helpful
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Roshan S
5.0 3 years ago
by Roshan completed this course, spending 10 hours a week on it and found the course difficulty to be hard.
I think the project at the end was very helpful. Getting to clean data, convert it from XML to JSON, load it into MongoDB and analyze it took effort. At the end, it seemed worth it.
1 person found
this review helpful
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Scott S
1.0 10 months ago
by Scott is taking this course right now, spending 12 hours a week on it and found the course difficulty to be very hard.
Where to start.

Although self paced, the course was without direction and expectations. I have worked through the lessons so many times and still the materials are not on target for the exercise. The "project Rubric", was a waste of a mouse click as it showed no specifics as to what is expected.

I have spent more than 5 months learning from other sites, (read non-Udacity) on how to proceed but I feel like a ship with out a rudder and no destination. It boggles the mind that there is no desired outcome for the project... Just ... Explore that data... what does that mean anyways?
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Anirudha B
4.0 4 years ago
by Anirudha completed this course.
I would highly recommend this course. Since this course is self paced, it is possible to finish it very quickly, as the material is not tough to comprehend. I didn't find any "Final Project Instructions" in the course though.
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Lukas T
4.0 4 years ago
by Lukas completed this course and found the course difficulty to be medium.
0 person found
this review helpful
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Gennady G
5.0 4 years ago
by Gennady completed this course.
0 person found
this review helpful
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Adam H
3.0 2 years ago
by Adam completed this course.
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Atila R
3.0 2 years ago
by Atila completed this course.
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  • 1

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