RAG & Vector Database Training for AI Developers
Master Retrieval-Augmented Generation (RAG) by building complete file-based AI systems using embeddings and vector databases. Learn how to connect LLMs with enterprise documents, design intelligent search pipelines, and deploy real-world GenAI applications through hands-on, step-by-step training.
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Course Description
RAG & Vector Database Training for AI Developers Course Overview Overview
60 Hours
Training Duration
20 Modules
Total Modules
Included in Every Module
Hands-On Labs
1 End-to-End RAG System Project
Capstone Project
Why do RAG & Vector Database Training for AI Developers at Nevo Learn
Learn like never before. Not just learning, you interact and gain real experience.
- Get practical, real-world learning experience
- Engage in interactive sessions and activities
- Apply concepts through hands-on exercises
Build skills that matter. Go beyond theory and develop job-ready expertise.
- Track and measure your skill progress
- Identify strengths and areas for improvement
- Gain industry-relevant knowledge and tools
Achieve your career goals with structured learning and expert guidance.
- Learn from industry experts and mentors
- Prepare for certifications and real-world challenges
- Boost your career growth with in-demand skills
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RAG & Vector Database Training for AI Developers Curriculum
Concepts
ā What is Generative AI?
ā How LLMs work (simple explanation)
ā Real-world use cases of GenAI
Hands-On Lab
ā Explore LLM responses using simple prompts
ā Understand input ā output behavior
Concepts
ā What is Retrieval-Augmented Generation?
ā Why RAG is needed beyond chat prompts
ā RAG vs traditional chatbots
Hands-On Lab
ā Visualize a simple RAG workflow
ā Test retrieval-based responses
Concepts
ā What is a prompt?
ā Prompt structure and best practices
ā Controlling AI output safely
Hands-On Lab
ā Write effective prompts
ā Improve response accuracy step by step
Concepts
ā What are prompt chains?
ā Chains vs agents vs memory (beginner view)
ā When to use chaining
Hands-OnLab
ā Build a simple chained prompt workflow
Concepts
ā PDFs, DOCX, TXT in AI systems
ā Text extraction basics
ā Common ingestion challenges
Hands-On Lab
ā Load and read documents into an AI pipeline
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About RAG & Vector Database Training for AI Developers Certification
Follow these simple steps to earn your professional certification and validate your expertise.
Enroll in the RAG & Vector Database Training program through an official registration process from Nevolearn
Attend and complete all 60 hours of instructor-led training sessions.
Actively participate in hands-on labs covering embeddings, vector databases, and RAG pipeline implementation.
Successfully complete module-wise practical exercises and guided assignments.
Develop and submit the end-to-end capstone project (File-Based RAG System).
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Prerequisites
No prior experience in Generative AI or RAG systems is required. Basic computer literacy is sufficient to begin. Programming concepts are introduced gradually in a beginner-friendly manner. Familiarity with Python or SQL is helpful but not mandatory. An interest in AI application development and problem-solving will help learners maximize outcomes.
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Who should attend the RAG & Vector Database Training for AI Developers training
This program is ideal for beginners and professionals who want to enter the fast-growing field of Generative AI and RAG-based application development. It is structured to support both technical and semi-technical learners.
COMMON QUESTIONS
RAG & Vector Database Training for AI Developers FAQs
Skills Covered
What Will You Learn?
Still have a question? Get in Touch with our Experts
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Set your teams up with this course
This RAG & Vector Database Training empowers professionals to move beyond basic AI usage and build production-ready Generative AI systems. Learners gain the ability to design document ingestion pipelines, generate embeddings, implement vector search, and develop enterprise-grade Retrieval-Augmented Generation (RAG) applications that reduce hallucinations and improve response accuracy.
The course builds strong practical expertise in RAG architecture, embedding optimization, and vector database workflows. It enhances career mobility into high-demand AI roles and enables organizations to develop secure AI systems connected to enterprise data, improving knowledge retrieval and accelerating enterprise GenAI adoption.
Transforming your team
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Meet the team that is invested in your success
Arjun Mehta
Artificial intelligence Instructor
Experience
1-3 Years
Experienced AI trainer specializing in Generative AI, Machine Learning, Deep Learning, prompt engineering, and practical AI solutions for business and...
Arjun Mehta
Artificial intelligence Instructor
Experience
1-3 Years
Experienced AI trainer specializing in Generative AI, Machine Learning, Deep Learning, prompt engineering, and practical AI solutions for business and...
CERTIFICATION
Earn a certificate on completion of this course
After finishing Nevolearn's RAG & Vector Database Training for AI Developers course, you'll earn an industry-recognized professional certificate. This certificate is designed for sharing on LinkedIn, allowing you to highlight your accomplishments and share your new skills with your network.
Validating your expertise with a professional certification helps you stand out in the job market and provides tangible proof of your commitment to continuous learning and professional growth.
Still have a question? Get in Touch with our Experts
TESTIMONIALS
What Learners are Saying
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RAG & Vector Database Training is one of the most in-demand programs for professionals aiming to build a career in Generative AI and enterprise AI application development. A well-structured RAG training course equips learners with practical expertise in Retrieval-Augmented Generation systems, embeddings, and vector search, making them industry-ready for real-world AI implementation projects.
This RAG & Vector Database course focuses on building end-to-end AI systems that connect Large Language Models (LLMs) with enterprise documents and structured data. Learners gain in-depth knowledge of document ingestion pipelines, embedding generation, vector database indexing, similarity search, retrieval optimization, and file-based chatbot development.
An industry-oriented RAG & Vector Database training program ensures the curriculum reflects enterprise GenAI implementation standards, including metadata filtering, guardrails, NLP-to-SQL integration, and retrieval accuracy tuning. Through structured labs and real-world capstone projects, learners build confidence in designing scalable AI systems powered by embeddings and vector databases.
RAG & Vector Database Training for AI Developers is a hands-on RAG training and vector database training program focused on building production-ready Retrieval-Augmented Generation (RAG) systems. This RAG course covers embeddings, embedding generation, vector search, and similarity search to power enterprise-grade AI solutions.
As part of this Generative AI training and GenAI course, you will design document ingestion pipelines, implement NLP-to-SQL workflows, and build real-world file-based chatbot development projects. The program also prepares you for RAG certification and vector database certification, making it ideal AI developer training for building scalable enterprise AI applications.