Advanced NoSQL for Data Science

Go to class
Write Review

Free Online Course: Advanced NoSQL for Data Science provided by LinkedIn Learning is a comprehensive online course, which lasts for 1-2 hours worth of material. The course is taught in English and is free of charge. Upon completion of the course, you can receive an e-certificate from LinkedIn Learning. Advanced NoSQL for Data Science is taught by Dan Sullivan.

Overview
  • Explore the fundamentals of NoSQL. Learn the differences between NoSQL and traditional relational databases, discover how to perform common data science tasks with NoSQL, and more.

Syllabus
  • Introduction

    • Welcome
    • What you should know
    • Exercise files
    1. Why NoSQL?
    • The limits of relational databases
    • Types of NoSQL databases
    • Advantages of NoSQL databases
    • Performing data science tasks with NoSQL
    2. Perform Common Data Science Tasks with NoSQL Databases
    • Preparing data
    • Exploring data
    • Building models
    • Applying models
    3. Document Databases for Data Science
    • Document data models
    • JSON structures
    • Prepare data with document databases
    • Install Anaconda
    • Install MongoDB
    • Working with Jupyter
    • Explore data with document databases
    • Extract data with document databases
    • Perform quality checks
    • Index data with document databases
    • Data frames in MongoDB
    • Tips for using document databases for data science
    4. Wide-Column Databases for Data Science
    • Wide-column data models
    • Prepare data with wide-column databases
    • Install the Java Development Kit
    • Install Cassandra
    • Prepare data for Cassandra
    • Load data into Cassandra
    • Cassandra and Spark
    • Tips for using wide-column databases for data science
    5. Graph Databases for Data Science
    • Graph data models
    • Key graphi concepts
    • Prepare data with graph databases
    • Install Neo4j
    • Explore data with graph databases
    • Extract data with graph databases
    • Tips for using graph databases for data science
    Conclusion
    • Next Steps