Who is this course for?

This course is ideal for developers, data scientists, AI enthusiasts, and software engineers looking to enhance their skills in building AI-powered applications.It'salso great for thoseseekingto specialize in integrating Gemini and OpenAI technologies into production systems.

Why should I enroll in this AI Agents Development course?

Enroll in this course to gain practical experience with the latest AI technologies such as Gemini and OpenAI. You will learn how to develop scalable AI agents along with advanced tools like RAG and MCP, which are crucial for high-demand fields such as AI development, backend architecture, and full-stack AI solutions.

What career opportunities will this course open up?

The skills you gained in this course can be applicable in roles requiringexpertisein natural language processing,machine learning, and AI system design.

Is this course aligned with industry standards for building AI-powered solutions?

Yes, the course teaches industry-standard practices for integrating AI models like Gemini and OpenAI, building efficient backend systems, andutilizingRAG and MCP to create robust, scalable AI solutions that align with the latest in AI technology development.

What is the focus of the Agentic AI Engineering course?

This course covers building AI agents using Retrieval Augmented Generation (RAG) and ModelContextProtocol(MCP). You will learn to integrate Gemini and OpenAI with Node.js backend, React, and real-world tool APIs to develop autonomous AI systems.

When will I have access to the lectures and assignments?

To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.

What will I get if I subscribe to this Specialization?

When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.

Is financial aid available?

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

Build Production AI Agents with RAG & MCP

kurs ist nicht verfügbar in Deutsch (Deutschland)

Wir übersetzen es in weitere Sprachen.

Build Production AI Agents with RAG & MCP

Dieser Kurs ist Teil von Spezialisierung „Agentic AI Engineering: RAG, MCP & MERN“

Dozenten: LearnKartS

Bei enthalten

Mehr erfahren

3 Module

Verschaffen Sie sich einen Einblick in ein Thema und lernen Sie die Grundlagen.

Stufe Mittel

Empfohlene Erfahrung

1 Woche zu vervollständigen

unter 10 Stunden pro Woche

Flexibler Zeitplan

In Ihrem eigenen Lerntempo lernen

3 Module

Verschaffen Sie sich einen Einblick in ein Thema und lernen Sie die Grundlagen.

Stufe Mittel

Empfohlene Erfahrung

1 Woche zu vervollständigen

unter 10 Stunden pro Woche

Flexibler Zeitplan

In Ihrem eigenen Lerntempo lernen

Was Sie lernen werden

Master building AI-powered chat systems with Node.js and Gemini API for seamless text generation and dynamic responses.
Implement static RAG systems andleverageknowledge bases to create advanced, responsive AI-driven Q&A bots.
Integrate OpenAI with RAG for intelligent response generation, improving accuracy and enhancing user experience.
Build real-world tool APIs using MCP, including customer service and weather APIs, to elevate AI system performance.

Kompetenzen, die Sie erwerben

Kategorie: Embeddings
Kategorie: Javascript
Kategorie: Retrieval-Augmented Generation
Kategorie: Server Side
Kategorie: Web Development
Kategorie: API Design
Kategorie: Generative AI Agents
Kategorie: Data Management
Kategorie: Back-End Web Development

Werkzeuge, die Sie lernen werden

Kategorie: OpenAI API
Kategorie: Gemini
Kategorie: Agentic Workflows
Kategorie: OpenAI
Kategorie: Node.JS
Kategorie: AI Workflows
Kategorie: Model Context Protocol
Kategorie: TypeScript
Kategorie: Google Gemini
Kategorie: Prompt Engineering
Kategorie: Web Applications

Wichtige Details

Zertifikat zur Vorlage

Zu Ihrem LinkedIn-Profil hinzufügen

Kürzlich aktualisiert!

April 2026

Bewertungen

20 Aufgaben

Unterrichtet in Englisch

91% of learners achieved a positive career outcome

Erfahren Sie, wie Mitarbeiter führender Unternehmen gefragte Kompetenzen erwerben.

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Dieser Kurs ist Teil der Spezialisierung Spezialisierung „Agentic AI Engineering: RAG, MCP & MERN“

Wenn Sie sich für diesen Kurs anmelden, werden Sie auch für diese Spezialisierung angemeldet.

Lernen Sie neue Konzepte von Branchenexperten
Gewinnen Sie ein Grundverständnis bestimmter Themen oder Tools
Erwerben Sie berufsrelevante Kompetenzen durch praktische Projekte
Erwerben Sie ein Berufszertifikat zur Vorlage

In diesem Kurs gibt es 3 Module

Ready to revolutionize AI development?

The world of AI is rapidly evolving, and building intelligent, autonomous agents is the next frontier. But how do you go from just understanding AI concepts to creating powerful, production-ready systems? In this course, you’ll not only learn the theory but also gain real-world experience by building AI agents using Gemini and OpenAI. You’ll start by setting up a robust Node.js backend and then integrating Gemini for effortless text generation. Dive deep into creating static RAG systems for advanced Q&A bots and use OpenAI to take your AI’s responses to the next level. Unlike other courses, this Agentic AI course gives you the tools to create scalable, real-world applications like customer service bots and knowledge bases, ensuring your skills are directly applicable in the industry. Whether you're a developer, data scientist, or AI enthusiast, this course will sharpen your AI development skills and prepare you for real-world AI challenges. Don’t just learn about AI—build the future of AI agents. Enroll now and take the first step toward mastering AI development!

Moduldetails

Develop a robust Node.js backend, integrate the Gemini API with a React chat interface, and implement a Static RAG system to deliver structured, knowledge-driven responses.

Das ist alles enthalten

17 Videos8 Aufgaben

17 VideosInsgesamt 75 Minuten

Course Introduction1 Minute
Setting Up the Node.js Backend Project3 Minuten
Building and Running an Express Server5 Minuten
Using Environment Variables, Watch Mode, and NPM Scripts7 Minuten
Introduction to Gemini API and Exploring the Documentation5 Minuten
Generating the Gemini API Key and Environment Configuration4 Minuten
Creating the Gemini Provider Class and Backend Structure5 Minuten
Implementing Text Generation Using the Gemini SDK5 Minuten
Building the Chat API Endpoint and Testing the Backend5 Minuten
Testing NodeJS API in React Chat App - Chat with AI4 Minuten
Understanding React Component Structure for the Chat Screen3 Minuten
Refactoring Chat Components and Improving Code Organization5 Minuten
Optimizing UI Design and Finalizing Light/Dark Mode Styling5 Minuten
Setting Up the Knowledge Base and RAG Service4 Minuten
Preparing Context and Prompt for Static RAG4 Minuten
Integrating RAG with Chat Router and Testing the Q&A Bot6 Minuten
Introduction to Embeddings and RAG Workflow5 Minuten

8 AufgabenInsgesamt 144 Minuten

Checkpoint Quiz16 Minuten
Checkpoint Quiz16 Minuten
Checkpoint Quiz16 Minuten
Checkpoint Quiz16 Minuten
Proficiency Quiz20 Minuten
Proficiency Quiz20 Minuten
Proficiency Quiz20 Minuten
Proficiency Quiz20 Minuten

Leverage embeddings and semantic search techniques to build a dynamic RAG Q&A system, integrating OpenAI for intelligent, context-aware answer generation.

Das ist alles enthalten

13 Videos4 Aufgaben

13 VideosInsgesamt 64 Minuten

Exploring Gemini Embedding API and Task Types3 Minuten
Creating the Embedding Generation Function3 Minuten
Installing Cosine Similarity and Setting Up RAG Utilities4 Minuten
Generating Query Embeddings and Fetching Knowledge Base Data5 Minuten
Creating FAQ Embedding Vectors from Knowledge Base5 Minuten
Calculating Cosine Similarity and Selecting Relevant Context7 Minuten
Setting Up OpenAI API Key and Selecting the Model4 Minuten
Creating the OpenAI Provider Class and Installing the SDK4 Minuten
Implementing Response Generation and Embeddings in OpenAI5 Minuten
Integrating OpenAI with the Chat Router and Testing the LLM7 Minuten
Testing Q&A Bot with OpenAI for Answers5 Minuten
Testing Error Handling8 Minuten
Interview Prep: RAG & Similarity Questions6 Minuten

4 AufgabenInsgesamt 117 Minuten

Checkpoint Quiz28 Minuten
Checkpoint Quiz24 Minuten
Proficiency Quiz35 Minuten
Proficiency Quiz30 Minuten

Establish a TypeScript backend, design real-world APIs, and apply MCP principles—Tools, Resources, and Prompts—to build scalable, intelligent AI agents.