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Read More →Visakhapatnam-based learners can now join Uncodemy's instructor-led RAG Engineering program, taught live online across 5–6 months. The course moves through document ingestion & chunking, embeddings, vector databases, retrieval pipelines, hybrid search and production RAG deployment. It is built for developers, data scientists/ML engineers and aspiring AI engineers, and spans 13 modules, 90+ live sessions, 140+ hours and an enterprise RAG capstone. Fee: ₹17,500 + 18% GST, total ₹20,650. EMI from ₹4,032/month.
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Certificate of Completion from Uncodemy
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Learners who complete Uncodemy's RAG Engineering training build practical, working knowledge of document processing, embeddings, vector databases, retrieval pipelines and hybrid search. Once training and career preparation are finished, eligible learners may apply for roles such as RAG Engineer, AI Application Engineer and GenAI Engineer. Placement records for Visakhapatnam learners are refreshed at regular intervals — verified outcomes appear at uncodemy.com/placement.
RAG Engineering (Retrieval-Augmented Generation) is the field of connecting large language models to an external retrieval mechanism so that outputs stay grounded in current, verifiable enterprise data rather than depending solely on pretraining. The process spans document ingestion, chunking, embedding generation, vector database operations and retrieval pipelines that supply the right context to the LLM at query time. This approach meaningfully reduces hallucination and lets AI systems respond reliably to questions about proprietary, industry-specific or continuously changing information.
What does a RAG engineer do? A RAG engineer handles document ingestion and chunking, produces embeddings and runs vector databases, designs retrieval pipelines, implements hybrid search, evaluates RAG accuracy, and deploys production RAG systems. Day-to-day, this involves Python scripting, using frameworks like LangChain and LlamaIndex, tuning chunking and retrieval strategies, measuring relevance and faithfulness, and exposing RAG-powered APIs that applications can consume.
RAG Engineering centres on engineering retrieval-grounded AI systems over enterprise knowledge, while LLM Engineering covers LLM-powered applications more broadly and Generative AI emphasises autonomous agents.
| Aspect | RAG Engineering | LLM Engineering | Generative AI |
|---|---|---|---|
| Core focus | Building retrieval-grounded AI systems on enterprise knowledge | Building, fine-tuning & deploying LLM-powered applications broadly | Building GenAI apps + autonomous AI agents |
| Coding depth | High | High | Moderate to High |
| Typical entry salary | ₹5–9 LPA (Entry-Level RAG Engineer) | ₹6–10 LPA (per LLM Engineering course sheet) | [CONFIRM per GenAI course sheet] |
| Uncodemy program duration | 5–6 months | 5–6 months | ~3–4 months (indicative) |
Salary ranges are indicative and vary by role, skills, experience, location and employer.
Structured as a 13-module journey and taught completely live online, this RAG Engineering program runs over 5–6 months and includes 90+ instructor-led sessions alongside 140+ hours of guided learning. The modules build in careful order: RAG & enterprise knowledge AI foundations, Python for RAG engineering, LLM fundamentals & API integration, document processing & data ingestion, text chunking & document transformation, embeddings & semantic search, vector databases & indexing, RAG, advanced retrieval & reranking, hybrid search & knowledge retrieval, RAG evaluation & optimization, and production RAG APIs & deployment — closing with a 20-hour enterprise RAG capstone. Each module carries hands-on exercises using real tools. Learners based in Visakhapatnam attend the same live online batch as participants across India.
Who should join this course:
Eligibility: Programming fundamentals are helpful but not required — Python is introduced starting in Module 2. Awareness of basic LLM concepts is beneficial, though it is developed from Module 3 onward. A laptop and dependable internet connection are essential for the practical sessions.
Choose the batch slot that best fits your schedule. Live online batches follow IST. Book a free demo class to see the teaching style upfront, or join our next weekday and weekend live batches — created for both working professionals and students, with flexible timings and hands-on practice.
| Date | Time | Trainer | Seats Left |
|---|---|---|---|
| 16oct | 07:30 PM – 08:30 PM | Mr. Irshad | 01Seat |
| 22oct | 02:00 PM – 03:00 PM | Mr. Upendra Kumar Tiwari | 02Seats |
| 26oct | 10:30 AM – 11:30 AM | Mr. Irshad | 01Seat |
| 30oct | 12:00 PM – 01:00 PM | Mr. Upendra Kumar Tiwari | 02Seats |
| Date | Time | Trainer | Seats Left |
|---|---|---|---|
| 27oct | 03:00 PM – 05:00 PM | Mr. Irshad | 02Seats |
8+ new batches start every month. All timings are in IST. Seats are limited and updated daily.
This syllabus is made up of 13 modules that add up to 140 hours. Its order tracks how RAG engineering actually unfolds in practice: foundations → Python → LLM fundamentals & API integration → document processing & chunking → embeddings & semantic search → vector databases → RAG → advanced retrieval/reranking → hybrid search → evaluation → production deployment → capstone. Every module embeds practical exercises with real tools, and the program ends with hands-on RAG projects along with an enterprise RAG capstone.
| # | Module | Hours | Tools |
|---|---|---|---|
| 1 | RAG & Enterprise Knowledge AI Foundations | 8 | Python, LLM APIs |
| 2 | Python for RAG Engineering | 10 | Python, Git |
| 3 | LLM Fundamentals & API Integration | 10 | OpenAI APIs, Hugging Face |
| 4 | Document Processing & Data Ingestion | 8 | Python, LlamaIndex |
| 5 | Text Chunking & Document Transformation | 8 | LangChain, LlamaIndex |
| 6 | Embeddings & Semantic Search | 10 | Hugging Face, OpenAI Embeddings |
| 7 | Vector Databases & Indexing | 10 | FAISS, ChromaDB, Pinecone, pgvector |
| 8 | Retrieval-Augmented Generation (RAG) | 12 | LangChain, LlamaIndex, Vector DBs |
| 9 | Advanced Retrieval & Reranking | 10 | LangChain, Cross-Encoders |
| 10 | Hybrid Search & Knowledge Retrieval | 10 | Elasticsearch/OpenSearch, LangChain |
| 11 | RAG Evaluation, Accuracy & Optimization | 12 | RAGAS, LangSmith, Python |
| 12 | Production RAG, APIs & Deployment | 12 | FastAPI, Docker, Cloud Deployment Tools |
| 13 | Enterprise RAG Projects & Capstone | 20 | All tools |
| Total | 140 Hours | 15+ tools | |
On finishing all 13 modules, the assignments and the Enterprise RAG capstone project, learners receive the Uncodemy RAG Engineering Program Certificate. The certificate carries the program name, duration, tools covered and completion date. It is verifiable online at certificate.uncodemy.com and serves as a documented record of successful completion of the Uncodemy RAG Engineering program.
The certificate reflects the practical work completed through the program — hands-on RAG pipeline work, retrieval evaluation and the 20-hour Enterprise RAG capstone project. Learners work with Python, OpenAI APIs, Hugging Face, LangChain, LlamaIndex, LangGraph, FAISS, ChromaDB, Pinecone, PostgreSQL/pgvector, Elasticsearch/OpenSearch, FastAPI, Docker, Git/GitHub and cloud deployment tools.
This is an independent Uncodemy certificate. It is not affiliated with, endorsed by, or a credential of OpenAI, Pinecone or any other RAG/vendor provider whose tools are taught in this course. Certificate verification process pending confirmation.
Uncodemy Certificate Verification Online Certificate Verification & Download certificate.uncodemy.com_2.webp)
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OpenAI APIs
LangChain
LlamaIndex
Vector Databases
Hugging Face
FAISS
ChromaDB
Pinecone
FastAPI
Docker
<Elasticsearch
Git & GitHub
Uncodemy is a career-centric IT training institute operated by Uncodemy Edutech Pvt. Ltd. With 14+ years of training excellence, physical classroom centres in Delhi and Noida, and live online classes reaching learners throughout India, Uncodemy offers instructor-led training for emerging technologies.
Inside this RAG Engineering program, participants build retrieval pipelines, hybrid search systems and production RAG APIs, then complete an enterprise RAG capstone project. The training shows how retrieval-grounded AI systems are engineered in production — covering document processing, embeddings, vector search, retrieval evaluation and deployment. You can study the full module-by-module curriculum before making an enrolment decision.
Beyond the syllabus, Uncodemy provides instructor-led sessions, practical assignments, project-based learning, interview preparation and career support. What that support includes — and what it does not — is set out in our career support policy, along with the eligibility conditions published before enrolment rather than after payment.
If you are still exploring options, Uncodemy also runs LLM Engineering, AI Testing and Data Science courses for Visakhapatnam and Andhra Pradesh learners.
Portfolio/capstone project review:Your hands-on RAG pipelines, retrieval evaluation work and enterprise RAG capstone are reviewed and refined into a portfolio an interview will find credible.
Resume & LinkedIn:We build your resume around RAG engineering keywords and measurable outcomes, and align your LinkedIn profile to match.
Interview preparation:Retrieval pipeline design questions, chunking-strategy trade-offs, evaluation-metric discussions and RAG engineering case studies specific to AI hiring.
Mock interviews:Sessions with industry trainers, followed by written feedback on what to fix.
Opportunity sharing:Relevant openings from our hiring network of 850+ companies are shared with you, with support through the application and interview process.
Continued support:This is active assistance, not a guarantee of employment — no training institute can honestly promise a job. Support continues after your program ends for learners who stay engaged with the process.
The people who actually teach this course
Irshad Khan, Senior Trainer at Uncodemy, leads this program, bringing 8+ years across Data Science, Data Analytics, SQL, Power BI, Python and Generative AI. He's also the one who reviewed and approved the curriculum you see here.
Most institutes blur two jobs into one; Uncodemy keeps them apart. Trainers handle the live teaching. A separate group of domain reviewers — specialists who never teach the batch — check that the curriculum stays accurate and up to date. Upendra Kumar Tiwari reviews the technical content for this program, so the person teaching it isn't the only one vouching for it.
Uncodemy publishes every trainer and domain reviewer by name, along with their area of focus and background — so you can check them out before enrolling, not afterward.
Senior Data Science Trainer
Expertise15+ years of industry experience building production machine learning systems for retail, telecom and consulting teams.
Modelling security breaches in iOS apps, dormant customer prediction and factor analysis, last-mile delivery optimisation, and credit card fraud detection.
Data Analytics & AI Trainer
ExpertisePython · SQL · Machine Learning · Tableau · Artificial Intelligence · Deep Learning · Power BI · MLOps
8+ years across consulting and public-sector analytics, with deep hands-on work in AI and MLOps delivery.
Built an OCR model, a disease-prediction model, and a fraud-control model deployed across every Indian state under the Ministry of Health & Welfare.
Data Analytics & AI Trainer
ExpertiseExcel, SQL, Python, statistics, Power BI, Tableau and Generative AI
7+ years turning aviation and enterprise data into forecasting models, dashboards and AI assistants.
AI agent chat/voice bot, AI-driven data analysis, a sales-forecasting ML model, NPS data model evaluation, and a face-recognition model for biometrics.
Data Analytics Trainer
ExpertisePython · SQL · Excel · Power BI · Tableau · ML · DL · NLP · Time Series · IoT Devices · Prompt Engineering · Chatbots
5+ years in logistics and consumer-brand analytics, with a strong focus on time series, NLP and applied automation.
Speech-to-text using core NLP (T2S), talent acquisition research, and product launch & CMS work on keventers.com using Sparktech.
Data Analytics Trainer
ExpertiseAdvanced Excel · SQL · Power BI · Tableau · Python · Data Visualisation · Statistics
Trainer for the analytics and business intelligence track at Uncodemy, working with learners on Excel, SQL and BI tooling from first principles to interview-ready projects.
Guides classroom capstones on sales and customer dashboards, KPI reporting and end-to-end data cleaning workflows.
Data Analytics Trainer
Expertise
Data Analytics Trainer
Expertise
MD & CEO
ExpertiseFounder, MD & CEO of Uncodemy and GS Net Academy, with experience in education, technology leadership, research, mentorship and career development.
Leads strategic direction, academic initiatives, technology-driven education programs and mentorship across Uncodemy and GS Net Academy.
Data Analytics Trainer
Expertise
MD & CEO
ExpertiseFounder, MD & CEO of Uncodemy and GS Net Academy, with experience in education, technology leadership, research, mentorship and career development.
Leads strategic direction, academic initiatives, technology-driven education programs and mentorship across Uncodemy and GS Net Academy.
CEO & Founder
ExpertiseCEO & Founder of GvCloud Secure and Uncodemy with 14+ years of professional experience building scalable web, mobile and AI-driven solutions for clients across India, USA, UK, Canada, Australia and Singapore.
Leads technology strategy, scalable web and mobile solutions, AI-driven products and EdTech initiatives across Uncodemy and GvCloud Secure.
Sign up for Uncodemy's RAG Engineering course tailored for Visakhapatnam learners today! Develop practical skills in document processing, embeddings, vector databases, retrieval pipelines and hybrid search via instructor-led live online training, hands-on projects and an enterprise RAG capstone. Kickstart your RAG engineering journey with structured training and career preparation.
| Role | Core Tools |
|---|---|
| RAG Engineer | LangChain, LlamaIndex, Vector DBs, Python |
| AI Application Engineer | LangChain, FastAPI, Vector DBs |
| GenAI Engineer | OpenAI APIs, LangChain, Embeddings |
| LLM/RAG Engineer | LangChain, LlamaIndex, Evaluation Tools |
| AI Solutions Engineer (Junior) | FastAPI, Docker, Cloud Deployment Tools |
| Search/Retrieval Engineer | Elasticsearch/OpenSearch, Vector DBs, Python |
| Role | Salary Range |
|---|---|
| Entry-Level RAG Engineer | ₹5–9 LPA |
| RAG / GenAI Engineer | ₹8–15 LPA |
| AI Application Engineer | ₹8–16 LPA |
| LLM / RAG Engineer | ₹10–20 LPA |
| Senior RAG Engineer | ₹18–30 LPA |
| AI Solutions Engineer | ₹15–28 LPA |
| Lead AI / RAG Engineer | ₹25–40 LPA |
| Factor | This Program |
|---|---|
| Duration | 5–6 months |
| Learning hours | 140+ |
| Live sessions | 90+ |
| Tools | 15+ |
| Capstone | 20-hour Enterprise RAG project |
| Career support | Dedicated Career & Placement Assistance |
| If you want... | Recommend |
|---|---|
| Full RAG Engineering career transition | This program |
| Already know LLM Engineering fundamentals, want to specialise in retrieval systems | This program |
| Building AI agents specifically | Consider Generative AI & Agentic AI course |
| Broad LLM application development | Consider LLM Engineering course |
The program runs for 5–6 months and includes 140+ hours of learning across 90+ live sessions. Weekday and weekend batches are both available.
Programming fundamentals are helpful but not mandatory — Python is taught from Module 2 onward. Familiarity with basic LLM concepts is a plus but built up in Module 3. A laptop with stable internet is required.
15+ tools including Python, OpenAI APIs, Hugging Face, LangChain, LlamaIndex, LangGraph, FAISS, ChromaDB, Pinecone, PostgreSQL/pgvector, Elasticsearch/OpenSearch, FastAPI, Docker, Git/GitHub and cloud deployment tools.
Yes. Module 7 covers Vector Databases & Indexing (10 hours) and Module 10 covers Hybrid Search & Knowledge Retrieval (10 hours). Both are core components with hands-on exercises.
The capstone is Module 13: Enterprise RAG Projects & Capstone (20 hours). You build an end-to-end RAG application applying document processing, embeddings, vector search, retrieval, evaluation and deployment.
All 90+ sessions are live and instructor-led, with recordings available afterwards for revision.
The program fee is ₹17,500 plus 18% GST. Total fee is ₹20,650. The same fee applies in all modes and cities.
EMI starts from ₹4,032 per month. The exact amount, tenure and eligibility depend on the applicable payment or financing option — a counsellor can confirm your plan.
Yes. You can attend a demo session to see the teaching style, meet the trainer and review the curriculum before deciding. Contact us to book a demo.
We provide Dedicated Career & Placement Assistance — resume building, LinkedIn optimisation, portfolio review, interview preparation, mock interviews and opportunity sharing through our network of 850+ companies. We do not guarantee employment.
Entry-level RAG Engineer roles in the market range around ₹5–9 LPA (indicative). Outcomes vary by skills, experience, employer and market conditions. Uncodemy does not guarantee any specific salary or employment outcome.
Indicative market ranges: Entry-Level ₹5–9 LPA, RAG/GenAI Engineer ₹8–15 LPA, Senior RAG Engineer ₹18–30 LPA, Lead AI/RAG Engineer ₹25–40 LPA. Actual offers vary by role, skills, experience, employer and market conditions. Uncodemy does not guarantee any specific salary.
RAG Engineer, AI Application Engineer, GenAI Engineer, LLM/RAG Engineer, AI Solutions Engineer (Junior) and Search/Retrieval Engineer.
Developers wanting to specialise in retrieval-grounded AI systems, data scientists/ML engineers upskilling into RAG engineering, aspiring AI engineers, and working professionals moving into GenAI/RAG roles.
Statistics are based on Uncodemy's internal records and publicly available review-platform information. Placement and salary outcomes vary by learner, skills, experience, location, employer and market conditions. Career and placement assistance does not constitute a guarantee of employment or a specific salary package.
This course is delivered live online nationwide, including for Visakhapatnam learners. Classroom training is available at our Delhi and Noida centres for other courses. Visakhapatnam learners typically join live online.
No. This is an independent Uncodemy certificate. It is not affiliated with, endorsed by, or a credential of OpenAI, Pinecone or any other RAG/vendor provider whose tools are taught in this course.
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