Mastering MCP: Transform AI Integration with Open Standards is an advanced-level course designed for AI engineers, data scientists, and technical architects who want to revolutionize how AI systems connect with external data sources. In today's fragmented AI landscape, integration challenges consume development time and create security vulnerabilities. This course teaches you to implement the Model Context Protocol (MCP)—the open standard that's transforming AI integration across industry leaders like Microsoft, GitHub, and Block. You'll master MCP's core components, learn to build production-ready servers with enterprise-grade security, and create scalable integration architectures. Through hands-on labs, real-world case studies, and a comprehensive capstone project, you'll develop the expertise to lead MCP implementations that reduce integration complexity by 75% while improving security and reliability. Whether you're modernizing existing AI systems or building next-generation integrations, this course provides the advanced knowledge and practical skills to succeed in the standardized AI integration ecosystem.
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Expérience recommandée
Compétences que vous acquerrez
- Catégorie : Real Time Data
- Catégorie : Servers
- Catégorie : API Design
- Catégorie : AI Security
- Catégorie : Software Architecture
- Catégorie : Performance Tuning
- Catégorie : Enterprise Security
- Catégorie : Interoperability
- Catégorie : System Design and Implementation
- Catégorie : Scalability
- Catégorie : Model Context Protocol
Détails à connaître
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décembre 2025
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Il y a 3 modules dans ce cours
In this foundational lesson, learners will explore the emergence of Model Context Protocol as a revolutionary open standard for AI integration. They'll examine how MCP addresses fragmentation in AI-data connections, evaluate its benefits over traditional integration methods, and analyze real-world implementations by industry leaders like Anthropic, Microsoft, and Block. Through hands-on activities, learners will assess MCP's impact on system interoperability and prepare to implement these standards in their own AI projects.
Inclus
4 vidéos3 lectures1 devoir
This lesson focuses on the practical implementation of MCP specifications to create efficient, reliable AI-data connections. Learners will explore MCP's core components—resources, tools, and prompts—while examining real-world implementations from Microsoft Azure OpenAI Services and DataCamp's tutorial examples. Through hands-on activities, learners will design MCP resource schemas, implement tool integration patterns, and build their first MCP client connection, gaining the practical skills needed to deploy MCP in production environments.
Inclus
3 vidéos2 lectures1 devoir
In this capstone lesson, learners will master the design and implementation of production-ready MCP servers with enterprise-grade security and reliability. They'll explore security best practices, authentication patterns, and performance optimization strategies used by industry leaders. Through comprehensive hands-on activities, learners will build a complete MCP server implementation, design security architectures, and create a deployment-ready system that demonstrates mastery of MCP principles and real-world application.
Inclus
4 vidéos2 lectures3 devoirs
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