GenAI Data Engineering and RAG Systems
This specialized course transforms you into an expert data engineer who can build sophisticated RAG (Retrieval-Augmented Generation) systems that seamlessly bridge AI models with your organization's knowledge assets.
Overview
This course includes:
- On-demand videos
- Practice assessments
- Multiple hands-on learning activities
- Exposure to a real-world project
- 100% self-paced learning opportunities
- Certification of completion
Ready to make AI systems work with your organization's unique knowledge and data? Most AI implementations hit a wall because they can't effectively access, process, and utilize enterprise information, leaving vast potential untapped and organizations frustrated with generic responses.
This specialized course transforms you into an expert data engineer who can build sophisticated RAG (Retrieval-Augmented Generation) systems that seamlessly bridge AI models with your organization's knowledge assets. You'll master advanced data processing pipelines that transform raw documents into AI-ready formats, architect high-performance vector databases for semantic search, and implement intelligent retrieval strategies that deliver contextually perfect responses. Through comprehensive hands-on labs, you'll build enterprise-grade RAG systems with adaptive orchestration, context-aware personalization, and production-ready monitoring.
By the end of this course, you'll confidently deploy RAG solutions that revolutionize how organizations access and utilize their information, create intelligent knowledge management systems that scale to millions of documents, and implement customer support applications that provide instant, accurate answers from your proprietary knowledge base. You'll have mastered the critical bridge between raw enterprise data and intelligent AI applications.
Join the specialists building the intelligent information infrastructure that makes AI truly valuable and become the RAG architect every knowledge-intensive organization desperately needs.
Skills You Will Gain
Learning Outcomes (At The End Of This Program, You Will Be Able To...)
-
Construct robust data processing pipelines that transform raw data into AI-ready formats
-
Implement advanced RAG architectures with component integration and performance optimization
-
Develop customer support RAG systems with domain-specific knowledge base management
-
Apply advanced retrieval strategies including metadata filtering, reranking, and quality enhancement
Prerequisites
Learners should have proficiency in Python, a solid understanding of databases and data processing, basic knowledge of machine learning concepts, and experience working with APIs and web services.
Who Should Attend
This course is designed for data engineers transitioning into AI systems, ML engineers focused on data pipelines, software engineers developing knowledge systems, and AI/ML specialists implementing RAG solutions.
