Udacity: Data Wrangling with MongoDB

 with  Shannon Bradshaw
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.


### 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
7 Student
Cost Free Online Course
Pace Self Paced
Subject Databases
Institution MongoDB University
Provider Udacity
Language English
Hours 6 hours a week
Calendar 8 weeks long

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FAQ View All
What are MOOCs?
MOOCs stand for Massive Open Online Courses. These are free online courses from universities around the world (eg. Stanford Harvard MIT) offered to anyone with an internet connection.
How do I register?
To register for a course, click on "Go to Class" button on the course page. This will take you to the providers website where you can register for the course.
How do these MOOCs or free online courses work?
MOOCs are designed for an online audience, teaching primarily through short (5-20 min.) pre recorded video lectures, that you watch on weekly schedule when convenient for you.  They also have student discussion forums, homework/assignments, and online quizzes or exams.

7 reviews for Udacity's Data Wrangling with MongoDB

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2 out of 2 people found the following review useful
a year ago
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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.
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1 out of 1 people found the following review useful
2 years ago
Roshan Shetty 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.
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3 years ago
Anirudha Bose 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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0 out of 1 people found the following review useful
3 years ago
Lukas Tencer completed this course and found the course difficulty to be medium.
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0 out of 1 people found the following review useful
3 years ago
Gennady completed this course.
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8 months ago
Adam Hjerpe completed this course.
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8 months ago
Atila Romero partially completed this course.
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