Explore digital courses

Learn how to build your first web app with Blazor.

Units in this learning path:

• 1 Introduction
• Configure Environment
• 3 Exercise Configure Environment
• 4 Blazor Components
• 5 Exercise Add Component
• Knowledge Check
• 8 Summary

Products: Aspnet Core, Blazor, Dotnet

Roles: Developer

Level: Beginner

Duration: 32 minutes

Bring automation and workflows to Microsoft Teams by using Microsoft Power Automate and Microsoft Dataverse for Teams.

Units in this learning path:

• 1 Introduction
• 2 Workflow Types
• 3 Create Workflow
• 4 Add Flow
• 5 Schedule
• 6 Check
• 7 Summary

Products: Power Platform, Power Automate

Roles: Business User, Maker

Level: Beginner

Subjects: Process Workflow

Duration: 25 minutes

Build your own AI copilot with vCore-based Azure Cosmos DB for MongoDB and Azure OpenAI.

Units in this learning path:

• Introduction
• Explore Azure Openai
• Understand Vector Database Retrieval Augmentation Generation Embeddings
• Implement Retrieval Augmentation Generation Vcore Based Cosmos Db Mongodb
• Exercise Develop AI Copilot Vcore Based Azure Cosmos Db Mongodb
• Knowledge Check
• Summary

Products: Azure Cosmos Db, Azure Openai

Roles: Developer

Level: Intermediate

Subjects: Artificial Intelligence, Databases

Duration: 73 minutes

Find out how to build your startup team and find cofounders. Learn how to benefit from diversity in teams, mentors, and risk management measures.

Units in this learning path:

• Introduction
• Ideal Startup Team
• Risk Management
• Build Diverse Teams
• Use Mentors
• Knowledge Check
• Summary

Products: Consumer

Roles: Business Owner, Business Analyst, Functional Consultant, Student

Level: Beginner

Subjects: Business Applications

Duration: 34 minutes

This badge earner demonstrates knowledge and understanding in technical and scientific concepts related to building AI solutions with open-source frameworks (such as TensorFlow and Keras) to make model predictions using regression, classification, and clustering algorithms such as Naive Bayes, Logistic regression, K-nearest neighbors, Polynomial Linear Regression, SVM (Kernel), Decision tree, and Ensemble learning, K means and DBSCAN for anomaly detection and computer vision.

In this course, you will learn about the benefits, architecture, deployment, and additional features of the Scale-Out Computing on AWS solution. This course includes presentations, demonstrations, videos, and an assessment.

This Playlist is an unordered collection of supplemental labs that have relevance to the classroom training Building Batch Data Analytics Solutions on AWS. Students of that class may find the labs in this playlist to be useful hands-on practice.

In this course, you learn how to make infrastructure choices to support containerized applications running on Amazon Elastic Container Service (Amazon ECS) at an enterprise scale. You learn how to scope requirements based on your application,…

Amazon EventBridge is a serverless event bus that makes it easy to connect applications together using data from customers applications, integrated software-as-a-service (SaaS) applications, and AWS services. You can use this service to build…

This course is designed for application developers interested in building generative artificial intelligence (generative AI) applications using either the Amazon Bedrock APIs or AWS-LangChain integration. In this course, you will explore the…

Amazon SageMaker helps data scientists prepare, build, train, deploy, and monitor machine learning (ML) models. SageMaker brings together a broad set of capabilities, including access to distributed training libraries, open source and foundation…

Retrieval Augmented Generation (RAG) is a powerful technique that enhances the accuracy and relevance of AI-generated responses by combining information retrieval with text generation. In this course, you will explore how to build RAG solutions…