Explore digital courses

Amazon Keyspaces (for Apache Cassandra) is a serverless database that can help you manage large, wide-column datastores. It offers single-digit millisecond read/write performance at scale. You can migrate your on-premises Cassandra workloads to…

Amazon MemoryDB for Redis is a Redis-compatible, durable, in-memory database service that can deliver ultra-fast performance. In this course, you will learn about the MemoryDB service, including its benefits, typical use cases, pricing, and…

Amazon Neptune is a fully managed graph database service that lets you build and run graph applications with highly connected datasets without worrying about hardware provisioning, software patching, setup, configuration, or backups. In this…

Amazon OpenSearch Service is a managed service that helps you perform interactive log analytics, real-time application monitoring, website search, and more. OpenSearch Service provisions all the resources for your cluster and launches it. It also…

Amazon Timestream is a scalable, fully managed, purpose-built serverless time series database that can help you store and analyze time series data. In this course, you will learn the benefits, typical use cases, and technical concepts of…

This credential earner demonstrates a foundational understanding of data concepts, such as types of data, big data, the data analytics process, data visualization, and the data science landscape. The individual has worked with data analytics tool to import, analyze and visualize data.

Learn how to use the SQL SELECT statement in PostgreSQL to retrieve, filter, and format data with specific columns, DISTINCT, and expressions.

Units in this learning path:

• Introduction
• Sample Database Overview
• Querying Columns Distinct
• Concatenation Calculated Columns
• Summary

Products: Azure Database Postgresql

Roles: Database Administrator, Developer

Level: Beginner

Subjects: Databases

Duration: 12 minutes

GitHub Copilot Across Environments: IDE, Chat, GitHub.com, and Command Line Techniques explore the versatile integration of GitHub's AI-powered coding assistance across your entire development workflow. It covers effective use of Copilot's auto-suggestions and multiple panes in IDEs, using natural language interactions in Copilot Chat, and streamlining command-line workflows. The guide delves into optimizing prompts, understanding context-aware code generation, and customizing Copilot's behavior to accelerate code changes and automate routine development tasks across different coding environments.

Units in this learning path:

• Introduction
• Code Completion with Git Hub Copilot
• Git Hub Copilot Chat
• Git Hub Copilot Github Web
• Git Hub Copilot for the Command Line
• Knowledge Check
• Summary

Products: Github

Roles: Developer, Devops Engineer, Student

Level: Intermediate

Subjects: Data Integration

Duration: 48 minutes

Overview of collaboration on GitHub Enterprise Server (GHES), focusing on governance, branch policies, and pull request workflows.

Units in this learning path:

• Repository Creation Organization
• Branch Strategies
• Branch Protection Rules
• Pull Request Review
• Collaboration Constraints
• Knowledge Check
• Summary

Products: Github

Roles: Devops Engineer, Administrator, Developer, Student

Level: Intermediate

Subjects: Data Integration

Duration: 31 minutes

Overview of GitHub Enterprise Server (GHES) and its self-managed GitHub experience for secure or regulated environments.

Units in this learning path:

• Github Enterprise Server Introduction
• Github Enterprise Server Cloud Differences
• Release Cadence Version Management
• Github Enterprise Server Developer Experience
• Github Connect Hybrid Scenarios
• Knowledge Check
• Summary

Products: Github

Roles: Devops Engineer, Administrator, Developer, Student

Level: Intermediate

Subjects: Data Integration

Duration: 31 minutes

Learn how to govern data and AI assets in Azure Databricks using Unity Catalog, including access control, data lineage, audit logging, and secure sharing.

Units in this learning path:

• Introduction
• Preserve Table Column Definitions
• Configure Abac Tags Policies
• Apply Data Retention Policies
• Manage Data Lineage Tracking
• Configure Audit Logging
• Secure Delta Sharing Strategy
• Exercise
• Knowledge Check
• Summary

Products: Azure Databricks

Roles: Data Engineer

Level: Intermediate

Subjects: Data Engineering

Duration: 108 minutes

Implement Fabric-native governance practices including data classification, sensitivity labels, endorsement, and documentation to ensure data assets are trustworthy and governed for both human and AI consumption.

Units in this learning path:

• Introduction
• Classify Protect
• Endorse Document
• Govern AI
• Exercise
• Knowledge Check
• Summary

Products: Fabric

Roles: Data Engineer

Level: Intermediate

Subjects: Data Management

Duration: 57 minutes