Data Engineering
Showing 421–432 of 829 results
Introduction to dbt
This course introduces dbt for data modeling, transformations, testing, and building documentation.
Introduction to Graph Databases, Cypher, and Neo4j 4
An introduction to graph databases, the Cypher query language, and the Neo4j graph database product. This course is updated in October 2018.
Introduction to Microsoft Dataverse ( previously Common Data Service)
The Microsoft Power Platform is one of the fastest-growing low-code platforms for building high productivity PaaS applications, and Common Data Service (CDS) is an integral part of the Power Platform. This course will teach you the basics of CDS.
Introduction to MLflow
Learn how to use MLflow to simplify the complexities of building machine learning applications. Explore MLflow tracking, projects, models, and model registry.
Introduction to MongoDB 2
MongoDB is a very popular NoSQL database that is fast and scalable. This course will get you familiar with this unique database and arm you with the essential skills to start using Mongo to power your software application.
Introduction to MongoDB in Python
Learn to manipulate and analyze flexibly structured data with MongoDB.
Introduction to NoSQL
Conquer NoSQL and supercharge data workflows. Learn Snowflake to work with big data, Postgres JSON for handling document data, and Redis for key-value data.
Introduction to open source database migration to Azure Cosmos DB
In this module, you will gain an understanding of Cosmos DB and the main considerations when migrating to Cosmos DB.
Introduction to open-source database migration on Azure
In this module, you'll learn about the issues and considerations for migrating on-premises open-source databases to Azure, the services that Azure provides to help you migrate your databases, and how to plan a migration.
Introduction to Oracle SQL
Sharpen your skills in Oracle SQL including SQL basics, aggregating, combining, and customizing data.
Introduction to project FarmVibes.AI
Explain the fundamental components of Project FarmVibes.AI (for brevity, we'll refer to it as FarmVibes.AI) tooling such as soil analysis capabilities, crop health monitoring systems, and advanced data analytics. Characterize the agricultural challenges that FarmVibes.AI is designed to address. Describe how FarmVibes.AI integrates these components to enhance agricultural practices, improve decision-making in farming.
Introduction to Spark SQL in Python
Learn how to manipulate data and create machine learning feature sets in Spark using SQL in Python.