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🔥 Most Popular in Jaipur

LLM Engineering Training Course in Jaipur by Uncodemy

Learners in Jaipur can take Uncodemy's LLM Engineering program as a 5–6 month instructor-led live online course. The syllabus walks through LLM APIs, embeddings & vector databases, RAG, fine-tuning, LLM agents & tool calling, and deployment. Aimed at developers, data scientists/ML engineers and aspiring AI engineers, the program spans 13 modules, 100+ live sessions, 160+ hours and an enterprise LLM capstone. Course fee: ₹17,500 + 18% GST, total ₹20,650. EMI available from ₹4,032/month.

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Total ₹20,650
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Starting ₹4,032/M*
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Expert Trainers

Learn from 8+ years experienced professionals

Hands-on Automation Projects

Build real LLM test suites, not just theory

Lifetime Access

Get lifetime access to recorded sessions & materials

Dedicated Career & Placement Assistance

Resume Building, Mock Interviews & Job Support

Certified Course

Certificate of Completion from Uncodemy

Flexible Batches

Weekday & Weekend Online & Offline

Why Choose
Uncodemy?

14+
Years of Training Excellence
850+
Companies in Our Hiring Network
54,000+
Learners Trained
200+
Corporate Associations
100%
Placement Support
Online & Offline Classes
Weekend & Weekday Batches
100% Practical Training
Affordable Fees
EMI Options Available
Dedicated Support

Program Details

LLM Engineering Course — Live Online Program Hands-on learning that focuses on practical LLM engineering skills and interview preparation.
A comprehensive 5–6 month instructor-led live online program covering LLM APIs, embeddings & vector databases, RAG, fine-tuning, LLM agents & tool calling, and deployment along with practical projects, mentoring and career support.
📚 Learning:
160+ Hours of Learning
⏱️ Program Duration:
5–6 Months
🎓 Live Training:
100+ Live Sessions
🛠️ Technology Coverage:
15+ Tools & Technologies
💼 Practical Learning:
Hands-on Projects, RAG Applications & AI Case Studies
💰 Program Fee:
₹17,500 + 18% GST
💰 Total Fee:
₹20,650
💳 EMI:
Starting From ₹4,032/Month*
🚀 Career Support:
Dedicated Career & Placement Assistance
🏢 Hiring Network:
850+ Companies in Our Hiring Network
🎯 Career Support Includes:
Resume Building & LinkedIn Optimization, Mock Interviews & Interview Preparation, Career Guidance & Job Opportunity Assistance

LLM Engineering Course in Jaipur — Quick Facts

🎓 Course:
LLM Engineering
🏢 Provider:
Uncodemy Edutech Pvt. Ltd.
📚 Total Learning:
160+ Hours of Learning
📖 Curriculum:
13 Modules
💼 Projects:
Hands-on Projects + Enterprise LLM Capstone
🛠️ Tools:
LLM APIs/SDKs, LangChain, Vector DBs, Python, Hugging Face, Prompt Engineering, Fine-Tuning, Evaluation, Git
🌐 Modes:
Live Online (offline only at Delhi & Noida centres; Jaipur learners join live online)
✅ Prior Coding:
Programming fundamentals helpful; Python taught from Module 2 onward. Basic ML/NLP built up in Module 3.
📜 Certificate:
Uncodemy LLM Engineering Program Certificate (verifiable online)
🗓️ Last Reviewed:
27 September 2026

List of Placed Students Trained by Uncodemy

Learners who complete the Uncodemy LLM Engineering program gain hands-on, applied skills in LLM APIs, RAG pipelines, fine-tuning, vector databases and LLM agents. After finishing training and career preparation, eligible learners can aim for roles such as LLM Engineer, AI Engineer and RAG/AI Application Engineer. Placement records for Jaipur learners are refreshed from time to time — see verified outcomes at uncodemy.com/placement.

What is LLM Engineering?

LLM engineering involves the design, build-out, fine-tuning and deployment of applications powered by large language models. While classic software engineering relies on deterministic logic and data science is centred on predictive modelling from data, LLM engineering works with probabilistic models, prompt design, retrieval pipelines and model adaptation. It bridges software engineering, machine learning and product development, turning raw LLM capabilities into dependable, production-grade features.

What does an LLM engineer do? In their role, an LLM engineer works with LLM APIs and SDKs, assembles RAG pipelines from embeddings and vector databases, fine-tunes models for specialized use cases, designs LLM agents capable of tool calling, evaluates model outputs, and deploys applications driven by LLMs. They regularly write Python, craft prompts, assess retrieval, integrate APIs, and use frameworks such as LangChain to wire models, data, and tools into a working app.

LLM Engineering vs Generative AI vs Data Science

LLM Engineering focuses on building, fine-tuning and deploying LLM-powered applications, while Generative AI & Agentic AI emphasises autonomous agents and Data Science focuses on predictive modelling.

Aspect LLM Engineering Generative AI Data Science
Core focus Building, fine-tuning & deploying LLM-powered applications Building GenAI apps + autonomous AI agents/multi-agent systems Predictive modelling from data
Coding depth High Moderate to High High
Typical entry salary ₹6–10 LPA (Entry-Level LLM Engineer) [CONFIRM per GenAI course sheet] ₹4–8 LPA (per Data Science course sheet)
Uncodemy program duration 5–6 months ~3–4 months (indicative) 8–9 months

Salary ranges are indicative and vary by role, skills, experience, location and employer.

Course Overview

For learners in Jaipur, this LLM Engineering program runs as a fully live online course across 5–6 months, with 100+ live sessions and 160+ hours of instruction. The 13 modules flow in a clear sequence — Generative AI foundations, Python for LLM engineering, ML & NLP fundamentals, transformer architecture, prompt engineering, LLM APIs & SDKs, embeddings & vector databases, RAG, LLM application development, fine-tuning, LLM agents & tool calling, evaluation & deployment, and a 20-hour Enterprise LLM capstone. Each module pairs conceptual learning with practical exercises using real tools, and the program closes with hands-on projects, RAG applications and an enterprise capstone. Everything is delivered online, making it convenient for Jaipur and pan-India learners.

Who should join this course:

  • Developers wanting to specialise in LLM-powered applications and generative AI.
  • Data scientists and ML engineers looking to upskill into LLM engineering and RAG pipelines.
  • Aspiring AI engineers who want to build production-ready LLM applications.
  • Working professionals moving into GenAI/LLM roles from software or analytics backgrounds.
  • Jaipur-based learners interested in instructor-led live online training with real hands-on projects.

Eligibility: Basic programming knowledge is beneficial, not obligatory — Python begins in Module 2 onward. Familiarity with elementary ML/NLP concepts is advantageous but cultivated in Module 3. A laptop with a steady internet connection is essential for the practical sessions.

Upcoming LLM Engineering Course Batches for Jaipur Learners

Select from live online batches scheduled at convenient IST timings. You can book a free demo class to get a first-hand feel for the trainer and curriculum, then choose an upcoming weekday or weekend batch. Timings work for both working professionals and students, with flexible schedules and a strong focus on hands-on practice.

Weekdays

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

Weekends

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.

Curriculum for LLM Engineering Training Course in Jaipur

LLM Engineering Course Syllabus in Jaipur

The syllabus is organised into 13 modules covering 160 hours. The order follows how LLM engineering actually works: foundations → Python → ML/NLP basics → transformer architecture → prompt engineering → LLM APIs → embeddings/vector DBs → RAG → application development → fine-tuning → agents & tool calling → evaluation/deployment → capstone. Each module includes practical exercises with real tools, and the program closes with hands-on projects, RAG applications and an enterprise LLM capstone.

Module 1: LLM & Generative AI Foundations — 8 Hours

  • Introduction to large language models and generative AI
  • LLM architecture basics: parameters, context windows
  • Tokenization, embeddings and model behaviour
  • GenAI landscape: major model providers and use cases
  • How LLMs differ from traditional software systems
  • Probabilistic outputs and non-determinism in LLMs

Module 2: Python for LLM Engineering — 10 Hours

  • Python syntax, data structures and control flow
  • Functions, modules and packages
  • Working with APIs, JSON and environment variables
  • Virtual environments and dependency management
  • Error handling and debugging for LLM applications
  • Async programming basics for API calls

Module 3: Machine Learning & NLP Fundamentals — 10 Hours

  • Supervised vs unsupervised learning basics
  • Training, validation and test splits
  • Text preprocessing and tokenization for NLP
  • Word embeddings and vector representations
  • Attention mechanisms and sequence modelling
  • Evaluation metrics for NLP tasks

Module 4: Transformers & LLM Architecture — 12 Hours

  • Transformer architecture: encoder, decoder, attention
  • Self-attention and multi-head attention
  • Positional encoding and context length
  • Pre-training vs fine-tuning paradigms
  • Model sizes, distillation and quantization
  • Hands-on: loading and inspecting transformer models

Module 5: Prompt Engineering & Structured Outputs — 8 Hours

  • Prompt design patterns and best practices
  • Zero-shot, few-shot and chain-of-thought prompting
  • Structured outputs: JSON, XML, function schemas
  • Prompt versioning and regression testing
  • Handling ambiguity and edge cases
  • Evaluating prompt reliability

Module 6: Working with LLM APIs & SDKs — 10 Hours

  • Overview of LLM APIs (OpenAI/Gemini/Claude-style)
  • Authentication, rate limits and error handling
  • Streaming responses and async calls
  • Function calling and structured output APIs
  • Cost management and token optimization
  • Building reusable API wrappers in Python

Module 7: Embeddings & Vector Databases — 10 Hours

  • Text embeddings and semantic similarity
  • Vector databases: FAISS, Chroma, Pinecone
  • Indexing strategies and performance trade-offs
  • Chunking strategies for documents
  • Metadata filtering and hybrid search
  • Hands-on: building a vector search pipeline

Module 8: Retrieval-Augmented Generation (RAG) — 15 Hours

  • RAG architecture: retriever, generator, context
  • Building end-to-end RAG pipelines with LangChain
  • Retrieval accuracy and relevance evaluation
  • Reranking and context compression
  • Handling multi-document and multi-hop queries
  • Hands-on: building a production-style RAG application

Module 9: LLM Application Development — 12 Hours

  • Designing LLM-powered applications
  • Chains, memory and context management
  • Integrating LLMs with external data sources
  • Building chat interfaces and APIs
  • Error handling and fallback strategies
  • Hands-on: building an LLM app with LangChain

Module 10: Fine-Tuning & Model Adaptation — 15 Hours

  • When to fine-tune vs prompt engineering vs RAG
  • Dataset preparation and formatting for fine-tuning
  • Parameter-efficient fine-tuning (LoRA, adapters)
  • Using Hugging Face Transformers for fine-tuning
  • Evaluating fine-tuned model performance
  • Hands-on: fine-tuning a small LLM on a custom dataset

Module 11: LLM Agents & Tool Calling — 15 Hours

  • Agent architecture: planning, tool use, memory
  • Tool calling and function execution
  • Multi-step reasoning and task decomposition
  • Building agents with LangChain
  • Agent evaluation and failure mode analysis
  • Hands-on: building a tool-using LLM agent

Module 12: LLM Evaluation, Optimization & Deployment — 15 Hours

  • Evaluation metrics for LLM outputs
  • Automated evaluation with LLM-as-judge
  • Observability and tracing for LLM applications
  • Latency, cost and throughput optimization
  • Deployment patterns: APIs, containers, serverless
  • Monitoring production LLM applications

Module 13: Enterprise LLM Projects & Capstone — 20 Hours

  • End-to-end LLM application design and architecture
  • RAG + fine-tuning + agents integration project
  • Deployment and evaluation of capstone application
  • Code review and portfolio preparation
  • Presentation and documentation of capstone project
  • Interview preparation around capstone work
# Module Hours Tools
1 LLM & Generative AI Foundations 8 ChatGPT, Gemini, Claude
2 Python for LLM Engineering 10 Python, Git
3 Machine Learning & NLP Fundamentals 10 Python, scikit-learn, NLTK
4 Transformers & LLM Architecture 12 Hugging Face Transformers
5 Prompt Engineering & Structured Outputs 8 ChatGPT, Gemini, Claude
6 Working with LLM APIs & SDKs 10 OpenAI/Gemini/Claude APIs, Python
7 Embeddings & Vector Databases 10 FAISS, Chroma, Pinecone
8 Retrieval-Augmented Generation (RAG) 15 LangChain, Vector DBs
9 LLM Application Development 12 LangChain, Python
10 Fine-Tuning & Model Adaptation 15 Hugging Face, LoRA
11 LLM Agents & Tool Calling 15 LangChain, Python
12 LLM Evaluation, Optimization & Deployment 15 LangSmith, Docker, Python
13 Enterprise LLM Projects & Capstone 20 All tools
Total 160 Hours 15+ tools

Contacted by

IR

Mr. Irshad

Curriculum & Technical Reviewer

[8+ Years Of Experience]

Specialization: LLM Engineering, Generative AI, RAG & Fine-Tuning

Get Your LLM Engineering Certification In Jaipur

Once you complete the 13 modules, the assignments and the Enterprise LLM capstone project, you're awarded the Uncodemy LLM Engineering Program Certificate. It records the program name, its duration, the tools covered and the completion date. The certificate can be verified online at certificate.uncodemy.com and acts as a formal record of successful completion of the Uncodemy LLM Engineering program.

The certificate is linked to the practical work completed during the program — hands-on RAG applications, fine-tuning exercises and the 20-hour Enterprise LLM capstone project. Learners work with LLM APIs & SDKs (OpenAI/Gemini/Claude-style), LangChain, Vector Databases (FAISS/Chroma/Pinecone), Python, Hugging Face Transformers, prompt engineering tools, fine-tuning frameworks and evaluation/observability tools.

Key Benefits of Our LLM Engineering Certification:

  • Program Completion :Provides a record of successful completion of the LLM Engineering program.
  • Online Verification :Certificate is verifiable online at certificate.uncodemy.com.
  • Practical Learning :Training includes hands-on RAG applications, fine-tuning work and an enterprise capstone.

This is an independent Uncodemy certificate. It is not affiliated with, endorsed by, or a credential of OpenAI, Google, Anthropic or any other LLM/vendor provider whose APIs are taught in this course. Certificate verification process pending confirmation.

Uncodemy Certificate Verification Online Certificate Verification & Download certificate.uncodemy.com
IIBA Endorsed Education Provider certificate — Uncodemy
Uncodemy LLM Engineering Program Certificate
Uncodemy MSME registration certificate

Tools and Technologies Covered

Apply Now

Introducing Uncodemy


Portfolio/capstone project review:Your hands-on RAG applications, fine-tuning work and enterprise LLM capstone are reviewed and refined into a portfolio an interviewer will find credible.

Resume & LinkedIn:We shape your resume around LLM engineering keywords and measurable outcomes, and align your LinkedIn profile to match.

Interview preparation:System design for LLM applications, RAG pipeline debugging, fine-tuning trade-off questions and LLM engineering case studies specific to AI hiring.

Mock interviews:Sessions with industry trainers, followed by written feedback on what to improve.

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.

Instructors

The people who actually teach this course

Uncodemy separates two roles that most institutes merge into one. Trainers conduct the live sessions. Domain reviewers — independent specialists who don't teach the batch — confirm the curriculum is technically accurate and up to date. For this program, curriculum and technical content are reviewed by Mr. Irshad, with additional review by Mr. Upendra Kumar Tiwari. This means the person teaching a course is not the only person checking whether its content is correct.

Every trainer and domain reviewer linked with Uncodemy is published by name, with their domain and background — you can check them before you enrol rather than after.

Enroll in Our LLM Engineering Training for Jaipur Learners Today!

Begin your LLM engineering journey with Uncodemy's course built for Jaipur learners. Through live online, instructor-led sessions, you'll gain practical skills in LLM APIs, RAG pipelines, fine-tuning and LLM agents — reinforced by hands-on projects and an enterprise LLM capstone. Structured training and career preparation, all rolled into one program.

LLM Engineer Jobs and Career Scope in Jaipur+

Jaipur has grown into one of North India's notable IT and startup hubs, anchored by Mahindra World City, Sitapura Industrial Area, World Trade Park, and a diverse base of IT services firms, product companies, BPO/KPO centres and fast-rising SaaS startups. Organisations across Malviya Nagar, Vaishali Nagar, Mansarovar, C-Scheme, Tonk Road, Jagatpura, Pratap Nagar and Sitapura are adding LLM-powered features — customer-support chatbots, RAG-based knowledge assistants, document-processing systems and agentic AI workflows — creating demand for engineers who can work with LLM APIs, retrieval pipelines, fine-tuning trade-offs and deployment. IT services, BFSI, healthcare, edtech, e-commerce, tourism-tech, government-tech and textile/manufacturing-tech sectors in Jaipur are also adopting GenAI, and they need engineers who can ship reliable LLM-powered applications rather than short-lived prototypes. Interviews in Jaipur typically weight system design for LLM applications, RAG pipeline design and debugging, and fine-tuning trade-offs most heavily. Candidates with software engineering or data/ML experience, combined with LLM engineering skills, are especially well-positioned for these roles.

Job Roles After This Course+

LLM Engineer, AI Engineer, RAG/AI Application Engineer, Generative AI Engineer, ML Engineer (LLM-focused) and AI Solutions Architect (Junior) are the roles this course maps to. Each role involves building, fine-tuning or deploying LLM-powered applications, but they differ in the specific LLM components and tools used.
Role Core Tools
LLM Engineer LLM APIs, LangChain, Python, Vector DBs
AI Engineer Python, Hugging Face, RAG, Fine-Tuning
RAG/AI Application Engineer LangChain, Vector DBs, Embeddings
Generative AI Engineer LLM APIs, Prompt Engineering, Python
ML Engineer (LLM-focused) Hugging Face, Fine-Tuning, Evaluation Tools
AI Solutions Architect (Junior) LangChain, Deployment Tools, Python
Most graduates start as an LLM Engineer, AI Engineer or RAG/AI Application Engineer and move into the others with two to four years of experience, as they build depth in a specific LLM component or domain. Progression typically involves owning larger systems, leading projects, and specialising in fine-tuning, agents or deployment architecture.

LLM Engineer Salary in Jaipur — Role-wise+

Salaries in Jaipur vary by experience level, sector and how strong your LLM engineering skills are. The gap between the lowest and highest earners at the same title is often wider than freshers expect.
Role Salary Range
Entry-Level LLM Engineer₹6–10 LPA
LLM Engineer / AI Engineer₹10–18 LPA
Mid-Level LLM Engineer₹15–25 LPA
Generative AI Engineer₹10–20 LPA
RAG / AI Application Engineer₹10–20 LPA
Senior LLM Engineer₹20–35 LPA
Lead AI / LLM Engineer₹25–45 LPA
Sources reviewed: AmbitionBox, Glassdoor, Indeed and Uncodemy placement records. Reviewed: September 2026.

Salary figures are presented as indicative market ranges, not guaranteed course outcomes. Actual offers vary by role, skills, experience, employer and market conditions. Uncodemy does not guarantee any specific salary or employment outcome.

Top Sectors Hiring LLM Engineers in Jaipur+

Uncodemy works with 850+ companies in our hiring network across India, spanning large enterprises, mid-size firms and fast-growing startups, which gives learners exposure to more than one kind of hiring process and interview style. In Jaipur specifically, LLM engineering demand is emerging in:
  • IT services and global capability centres — Mahindra World City, Sitapura Industrial Area and the surrounding Jaipur belt
  • Product companies and SaaS startups — building chatbots, AI assistants and RAG-based features
  • BFSI and fintech — deploying LLMs for risk, fraud detection and customer support
  • Healthcare, edtech and e-commerce — LLMs for personalisation, content and customer service
  • Tourism-tech, government-tech and textile/manufacturing-tech — LLM-driven knowledge systems, documentation and support applications
Each of these sectors tends to weight skills slightly differently, so as you get closer to placement, it helps to tailor your capstone project toward the one or two sectors you're most interested in.

How to Become an LLM Engineer — Step by Step+

Becoming an LLM engineer is a step-by-step skill build, not a single course, and skipping steps usually shows up later as gaps in interviews or on the job.
  • Python fundamentals— syntax, data structures, APIs and environment management.
  • ML/NLP basics— supervised learning, text preprocessing, embeddings.
  • Transformer architecture— attention, positional encoding, pre-training vs fine-tuning.
  • Prompt engineering— design patterns, structured outputs, evaluation.
  • LLM APIs & embeddings— API integration, streaming, vector databases.
  • RAG & application development— retrieval pipelines, LangChain, chat interfaces.
  • Fine-tuning, agents & deployment— LoRA, tool calling, evaluation and production deployment.
Typical timeline: 5–6 months of consistent study to reach interview-ready standard, assuming focused hours most days rather than occasional binge sessions.

How This Course Compares to Other AI Courses in Jaipur+

Jaipur has dozens of AI training options at very different price points, ranging from short weekend workshops to multi-month bootcamps. Here is an honest comparison, so you can judge the fit yourself rather than relying on marketing claims alone.
Factor This Program
Duration5–6 months
Learning hours160+
Live sessions100+
Tools15+
Fine-tuning moduleDedicated 15-hour module
Capstone20-hour Enterprise LLM project
Career supportDedicated Career & Placement Assistance
Compared to Uncodemy's Generative AI & Agentic AI course (~3–4 months, focused on GenAI apps and autonomous agents) and AI Testing course (1.5 months, focused on testing LLMs, RAG and AI agents), this LLM Engineering program is the deepest, longest and most engineering-heavy option — it includes dedicated fine-tuning and deployment modules plus a 20-hour capstone. If your goal is a full LLM engineering career transition, this is the right fit. If you only need prompt-engineering upskilling, a shorter course may suit you better. If you are specifically building AI agents, the Generative AI & Agentic AI course is a closer match.

Where we are not the cheapest option: shorter self-paced courses cost less. If your goal is a quick LLM refresher rather than a full career transition, a shorter program may suit you better, and it's worth being honest with yourself about which of the two you actually need.

Online vs Offline vs Hybrid — Which Should You Choose?+

Offline classroom is available at our Delhi and Noida centres; Jaipur learners typically join live online. Live online retains the full instructor-led experience with no commute, and every session is recorded for revision. Offline works best for learners based near Delhi or Noida who prefer face-to-face interaction. Hybrid is not currently offered for this program. For Jaipur-based working professionals, live online is usually the most practical choice — real-time doubt clearing, hands-on labs and lifetime access to recordings, without any travel.

Is this course right for you?+

If you want... Recommend
Full LLM Engineering career transition This program
Quick prompt-engineering upskilling only Consider AI Testing or GenAI course
Already strong in traditional ML, want to specialise in LLMs This program
Building AI agents specifically Consider Generative AI & Agentic AI course

Frequently Asked Questions

1. How long is the LLM Engineering course in Jaipur?▼

The program is designed to be completed in 5–6 months, covering 160+ hours across 100+ live sessions. You can opt for either weekday or weekend batches.

2. Is prior Python or ML experience necessary?▼

No prior Python or ML background is required. Module 2 introduces Python from the ground up, and Module 3 covers foundational ML/NLP. A laptop with reliable internet is essential.

3. Which tools are taught in this course?▼

The program teaches 15+ tools: LLM APIs & SDKs (OpenAI/Gemini/Claude-style), LangChain, Vector Databases (FAISS/Chroma/Pinecone), Python, Hugging Face Transformers, Prompt Engineering Tools, Fine-Tuning Frameworks, Evaluation/Observability Tools, and Git & GitHub.

4. Are fine-tuning and LLM agents part of the syllabus?▼

Yes, both are included. Module 10 covers Fine-Tuning & Model Adaptation (15 hours) and Module 11 focuses on LLM Agents & Tool Calling (15 hours). Both are hands-on.

5. What does the capstone project involve?▼

The capstone, Module 13 (Enterprise LLM Projects & Capstone, 20 hours), has you build a complete LLM-powered application that brings together RAG, fine-tuning, agents and deployment.

6. Are classes conducted live or are they pre-recorded?▼

All 100+ sessions are live, instructor-led classes. Recordings are shared afterwards so you can revisit any topic.

7. What is the course fee for Jaipur learners?▼

The fee is ₹17,500 plus 18% GST, which totals ₹20,650. This applies uniformly across cities and modes.

8. Are EMI plans available?▼

EMI options start at ₹4,032 per month. Exact terms depend on your chosen financing option — your counsellor can confirm.

9. Can I attend a demo class before enrolling?▼

Yes, you can schedule a demo class to experience the teaching style and review the curriculum. Contact us to book a slot.

10. Do you offer placement assistance?▼

Dedicated Career & Placement Assistance covers resume building, LinkedIn optimisation, portfolio review, interview preparation, mock interviews and opportunity sharing via our 850+ company network. Employment is not guaranteed.

11. Can I secure an entry-level LLM Engineer role after this course?▼

Entry-level LLM Engineer roles typically range ₹6–10 LPA (indicative). Actual outcomes depend on your skills, experience, employer and market. Uncodemy doesn't guarantee any specific salary.

12. What is the salary of an LLM Engineer in Jaipur?▼

Indicative ranges: Entry-Level ₹6–10 LPA, Mid-Level ₹15–25 LPA, Senior ₹20–35 LPA, Lead ₹25–45 LPA. Offers vary by role, skills, experience, employer and market conditions.

13. Which job roles can I target after this course?▼

Roles include LLM Engineer, AI Engineer, RAG/AI Application Engineer, Generative AI Engineer, ML Engineer (LLM-focused) and AI Solutions Architect (Junior).

14. Who is eligible for this LLM Engineering course?▼

The course is designed for developers wanting to specialise in LLM-powered applications, data scientists/ML engineers upskilling into LLM engineering, aspiring AI engineers, and working professionals transitioning into GenAI/LLM roles.

15. Are the salary, placement and review figures on this page guaranteed?▼

No. These figures come from Uncodemy's records and public review platforms. Outcomes vary by learner, skills, experience, location, employer and market conditions.

16. Is classroom training available in Jaipur?▼

The course is delivered live online nationwide, including for Jaipur learners. Classroom options exist at Delhi and Noida centres for other courses. Jaipur learners typically join live online.

17. Is Uncodemy's LLM Engineering certificate affiliated with OpenAI, Google or Anthropic?▼

No, the certificate is issued independently by Uncodemy. It has no affiliation with OpenAI, Google, Anthropic or any other vendor.

Why Trust This Page? Discover Why Students Choose Uncodemy

How we maintain this page

  • Content written by:Mr. Rahul
  • Content rechecked and verified by: Mr. Irshad
  • Course curriculum verified by:Mr. Irshad
  • Technical content verified by: Mr. Irshad
  • Fee verified by: Admin Department
  • Placement figures sourced from internal placement records
  • Review counts verified against respective third-party platforms
  • Last reviewed:
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