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LinkedIn Learning

Building Generative AI Skills for Developers

via LinkedIn Learning Path

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Overview

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Master generative AI development from foundational concepts to production systems. Learn LLMs, transformer architectures, advanced RAG implementations, vector databases, and enterprise deployment strategies. This path is perfect for developers building intelligent applications, chatbots, content generation tools, and AI-powered solutions that generate and retrieve contextual information at scale for business innovation.
  • Compare different LLM architectures for specific use cases.

Syllabus

Courses under this program:
Course 1: Generative AI vs. Traditional AI
-See the key differences between generative and traditional AI.

Course 2: Introduction to Large Language Models
-Learn about large language models—what they are, what they can do, and how they work.

Course 3: Generative AI: Working with Large Language Models
-Explore a user-friendly approach to working with transformers and large language models for natural language processing.

Course 4: LLM Foundations: Vector Databases for Caching and Retrieval Augmented Generation (RAG)
-Learn about the basics of vector databases and how to use them in LLM caching and retrieval-augmented generation.

Course 5: Advanced RAG Applications with Vector Databases
-Discover cutting-edge methods to perform retrieval-augmented generation (RAG) with a vector database.

Course 6: RAG Fine-Tuning: Advanced Techniques for Accuracy and Model Performance
-Fine-tune LLMs in Azure AI Studio using retrieval augmentation to create domain-specific AI systems using state-of-the-art RAFT technique.

Course 7: GenAIOps Foundations
-Leverage GenAIOps in your enterprises for effective development, deployment, and management of GenAI applications.

Courses

Taught by

Pinar Demirdag, Doug Rose, Xavier (Xavi) Amatriain, Ray Villalobos, Morten Rand-Hendriksen, Sandy Ludosky, Kesha Williams, Denys Linkov, Han-chung Lee, Alina Li Zhang and Priya Ranjani Mohan

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