AI Engineer Core & Agentic Track with RAG, LLM, Agent, QLoRA

About this course

The AI Engineer Core & Agentic Track with RAG, LLM, Agent, QLoRA is a comprehensive online course designed to help learners develop practical skills in modern artificial intelligence engineering. This course covers essential AI engineering concepts, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), agentic AI systems, and advanced model fine-tuning techniques using QLoRA. Whether you are a beginner exploring AI engineering or a developer looking to expand your expertise, this course provides a structured learning path to understand and build intelligent AI-powered applications.

You will begin by exploring the fundamentals of Large Language Models, transformer architectures, prompt engineering, and integrating LLMs into real-world applications. You will learn how AI models process information, generate responses, and support intelligent application development. The course introduces practical approaches to working with LLMs and building applications that use generative AI capabilities to solve real-world problems.

Next, you will learn how to build Retrieval-Augmented Generation systems that combine the capabilities of LLMs with external knowledge sources. You will explore document processing, text embeddings, vector databases, semantic search, and retrieval pipelines. These techniques will help you develop AI applications that retrieve relevant information and generate context-aware responses based on specific datasets and documents.

The course also introduces agentic AI development, where AI agents can use tools, maintain context, perform multi-step reasoning, and execute tasks through structured workflows. You will learn how to design AI agents that interact with external systems, automate repetitive tasks, and support more complex problem-solving scenarios. You will also explore how agent-based workflows can be integrated with LLMs and RAG systems to build more capable AI applications.

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