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🔥 Most Popular in Bhubaneswar

LLM Engineering Training Course in Bhubaneswar by Uncodemy

Uncodemy's LLM Engineering program is now accessible to learners in Bhubaneswar through a fully live online, instructor-led format spanning 5–6 months. The curriculum covers LLM APIs, embeddings & vector databases, RAG, fine-tuning, LLM agents & tool calling, and deployment. Tailored for developers, data scientists/ML engineers and aspiring AI engineers, the program includes 13 modules, 100+ live sessions, 160+ hours and an enterprise LLM capstone. Fee: ₹17,500 + 18% GST, total ₹20,650. EMI starts at ₹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 Bhubaneswar — 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; Bhubaneswar 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:

3 October 2026

List of Placed Students Trained by Uncodemy

Uncodemy learners who complete the LLM Engineering program acquire practical, job-ready expertise in LLM APIs, RAG pipelines, fine-tuning, vector databases and LLM agents. After finishing training and career preparation, eligible candidates can pursue roles like LLM Engineer, AI Engineer and RAG/AI Application Engineer. Placement records for Bhubaneswar learners are updated periodically — see verified outcomes at uncodemy.com/placement.

What is LLM Engineering?

LLM engineering is the discipline of designing, building, fine-tuning and deploying applications that leverage large language models. Traditional software engineering relies on deterministic logic, while data science focuses on predictive modelling. LLM engineering instead works with probabilistic models, prompt design, retrieval pipelines and model adaptation. It merges software engineering, machine learning and product development into a single practice, turning raw LLM capabilities into reliable, production-grade features.

What does an LLM engineer do? An LLM engineer uses large language model APIs and SDKs, creates RAG pipelines with embeddings and vector databases, adapts models through fine-tuning for specialized domains, builds LLM agents that can call tools, assesses model responses, and deploys applications powered by LLMs. Their day-to-day work involves writing Python scripts, crafting prompts, evaluating retrieval, integrating APIs, and leveraging frameworks such as LangChain to link models, data, and tools into a functioning 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

This LLM Engineering course is delivered entirely live online over 5–6 months, featuring 100+ live sessions and 160+ hours of learning. The 13 modules are sequenced logically: 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 combines conceptual learning with practical exercises using real tools, and the program concludes with hands-on projects, RAG applications and an enterprise-grade capstone. Delivery is fully online, making it convenient for Bhubaneswar 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 aiming to build production-ready LLM applications.
Working professionals transitioning into GenAI/LLM roles from software or analytics backgrounds.
Bhubaneswar-based learners seeking instructor-led live online training with real hands-on projects.

Eligibility: Knowing programming basics helps, though it isn't required — Python is taught from Module 2 onward. Familiarity with basic ML/NLP ideas is beneficial but developed in Module 3. A laptop with reliable internet is necessary for the practical sessions.

Upcoming LLM Engineering Course Batches for Bhubaneswar Learners

Choose a live online batch timing that suits your schedule — all batches run on IST. A free demo class is a great way to see the trainer's delivery style before you decide. Then pick from our upcoming weekday or weekend batches, tailored for working professionals and students, with flexible timings and a strong hands-on focus.

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.

Enroll Now

Curriculum for LLM Engineering Training Course in Bhubaneswar

LLM Engineering Course Syllabus in Bhubaneswar

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

Mr. Irshad

Curriculum & Technical Reviewer

[8+ Years Of Experience]

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

LinkedIn Profile

LLM Engineering Curriculum

The curriculum has been designed and technically reviewed by expert industry professional Mr. Irshad, with additional review by Mr. Upendra Kumar Tiwari.

160+Hours of Learning

100+Live Sessions

15+Tools & Technologies

Get Your LLM Engineering Certification In Bhubaneswar

After completing all 13 modules, the assignments and the Enterprise LLM capstone project, learners are awarded the Uncodemy LLM Engineering Program Certificate. It records the program name, duration, tools covered and completion date. The certificate can be verified online at certificate.uncodemy.com and serves as an official record of successful completion of the Uncodemy LLM Engineering program.

The certificate reflects 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

Tools and Technologies Covered

LLM APIs & SDKs
LangChain
Vector Databases
Python
Hugging Face
Prompt Engineering
Fine-Tuning
Evaluation/Observability
Git & GitHub

Apply Now

Introducing Uncodemy

Uncodemy, operated by Uncodemy Edutech Pvt. Ltd., is a career-focused IT training institute with a 14+ year track record. It runs physical classroom centres in Delhi and Noida, and delivers live online classes to learners across India, offering instructor-led training in emerging technologies.

In this LLM Engineering course, participants create RAG applications, fine-tune models, design LLM agents with tool calling, and finish an enterprise LLM capstone project. The program teaches how LLM-powered applications are built in production — prompt design, retrieval pipelines, model adaptation and deployment. You can review the full module-by-module curriculum before you enrol.

Beyond training, Uncodemy offers instructor-led sessions, practical assignments, project-based learning, interview preparation and career support. What this support covers — and what it does not — is fully explained in our career support policy, together with the eligibility conditions shared before enrolment rather than after payment.

Other courses for Bhubaneswar learners

If you are still exploring, Uncodemy also offers Generative AI , Data Science and Playwright Automation Testing courses for Bhubaneswar and Odisha learners.

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.

Review

4.7/5500+ Google Reviews

5/530+ Sulekha Reviews

4.7/5500+ Just Dial Reviews

5/5Facebook Reviews

4/5130+ Mouthshut

5/554+ Trustindex Reviews

Instructors

The people who actually teach this course

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

Every trainer and domain reviewer linked to 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 Bhubaneswar Learners Today!

Start your LLM engineering career with Uncodemy's course tailored for Bhubaneswar learners. Instructor-led live online sessions help you build practical skills in LLM APIs, RAG pipelines, fine-tuning and LLM agents — backed by real projects and an enterprise LLM capstone. Get structured training and career preparation in one comprehensive program.

LLM Engineer Jobs and Career Scope in Bhubaneswar+

Bhubaneswar has rapidly evolved into a key technology and startup hub in eastern India, driven by Infocity, Chandaka Industrial Estate, and a growing cluster of IT services firms, product companies, SaaS startups and BPO/KPO centres. Organisations across Patia, Chandrasekharpur, Nayapalli, Saheed Nagar, Rasulgarh, Mancheswar and Khandagiri are embedding LLM-powered features — support chatbots, RAG-based knowledge assistants, document-processing pipelines and agentic AI workflows — creating demand for engineers who understand LLM APIs, retrieval pipelines, fine-tuning trade-offs and deployment. IT services, BFSI, fintech, healthcare, edtech, e-commerce, manufacturing-tech and government-tech sectors in Bhubaneswar are also adopting GenAI, and they need engineers who can deliver reliable LLM-powered applications, not just prototypes. Interviews in Bhubaneswar tend to focus most heavily on system design for LLM applications, RAG pipeline design and debugging, and fine-tuning trade-offs. Candidates with software engineering or data/ML experience, combined with LLM engineering skills, are particularly 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 Bhubaneswar — Role-wise+

Salaries in Bhubaneswar 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 Bhubaneswar+

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 Bhubaneswar specifically, LLM engineering demand is emerging in:

IT services and global capability centres — Infocity, Chandaka Industrial Estate and the surrounding tech corridors
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
Government-tech and 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 Bhubaneswar+

Bhubaneswar 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
Duration	5–6 months
Learning hours	160+
Live sessions	100+
Tools	15+
Fine-tuning module	Dedicated 15-hour module
Capstone	20-hour Enterprise LLM project
Career support	Dedicated 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; Bhubaneswar learners typically join live online. Live online preserves the full instructor-led experience with no commute, and every session is recorded for revision. Offline fits learners near Delhi or Noida who prefer face-to-face interaction. Hybrid is not currently offered for this program. For Bhubaneswar-based working professionals, live online is usually the most practical route — real-time doubt clearing, hands-on labs and lifetime access to recordings, all without travelling.

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 Bhubaneswar?▼

The program is 5–6 months long, delivering 160+ hours of learning through 100+ live sessions. Both weekday and weekend batches are available.

2. Do I need prior Python or ML experience to join?▼

No prior experience is necessary. Module 2 starts with Python fundamentals, and Module 3 covers basic ML/NLP. A laptop and stable internet are required.

3. What tools are covered in this course?▼

You will learn 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. Does the course include fine-tuning and LLM agents?▼

Yes. Module 10 is dedicated to Fine-Tuning & Model Adaptation (15 hours), and Module 11 covers LLM Agents & Tool Calling (15 hours). Both include hands-on practice.

5. What does the capstone project involve?▼

The capstone is Module 13: Enterprise LLM Projects & Capstone (20 hours). You will build an end-to-end LLM-powered application integrating RAG, fine-tuning, agents and deployment.

6. Are the classes live or pre-recorded?▼

All 100+ sessions are live and instructor-led. Recordings are shared afterwards so you can revise at your convenience.

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

The fee is ₹17,500 + 18% GST, which totals ₹20,650. This fee is the same across all cities and delivery modes.

8. Are EMI options available?▼

EMI starts at ₹4,032 per month. The exact amount, tenure and eligibility depend on the payment or financing option selected — a counsellor can provide details.

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

Yes. You can book a demo class to experience the teaching style and review the curriculum before deciding. Contact us to schedule one.

10. Do you provide placement assistance?▼

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

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

Entry-level LLM Engineer roles generally offer around ₹6–10 LPA (indicative). Outcomes depend on your skills, experience, employer and market conditions. Uncodemy does not guarantee any specific salary or employment outcome.

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

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. Uncodemy does not guarantee any specific salary.

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

You can target roles such as 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?▼

This 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 moving into GenAI/LLM roles.

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

No. These figures come from Uncodemy's internal records and publicly available review platforms. Outcomes vary by learner, skills, experience, location, employer and market conditions. Career support is not a guarantee of employment or a specific salary.

16. Is classroom training available in Bhubaneswar?▼

The course is delivered live online across India, including for Bhubaneswar learners. Classroom training for other courses is available at our Delhi and Noida centres. Bhubaneswar 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 is not affiliated with, endorsed by, or a credential of OpenAI, Google, Anthropic or any other LLM/vendor whose APIs are taught in this course.

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: 25 Sep 2026

Written by:Mr. Rahul

Reviewed by: Mr. Upendra Kumar Tiwari

Final editorial check:Mr. Gangesh Gaunr, Director at Uncodemy

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LLM Engineering Training Course in Bhubaneswar by Uncodemy

Special Offer: LLM Engineering Program

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Curriculum for LLM Engineering Training Course in Bhubaneswar

LLM Engineering Course Syllabus in Bhubaneswar

Module 1: LLM & Generative AI Foundations — 8 Hours

Module 2: Python for LLM Engineering — 10 Hours

Module 3: Machine Learning & NLP Fundamentals — 10 Hours

Module 4: Transformers & LLM Architecture — 12 Hours

Module 5: Prompt Engineering & Structured Outputs — 8 Hours

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

Module 7: Embeddings & Vector Databases — 10 Hours

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

Module 9: LLM Application Development — 12 Hours

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

Module 11: LLM Agents & Tool Calling — 15 Hours

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

Module 13: Enterprise LLM Projects & Capstone — 20 Hours

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Mr. Irshad

Get Your LLM Engineering Certification In Bhubaneswar

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LLM Engineer Jobs and Career Scope in Bhubaneswar+

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Frequently Asked Questions

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

2. Do I need prior Python or ML experience to join?▼

3. What tools are covered in this course?▼

4. Does the course include fine-tuning and LLM agents?▼

5. What does the capstone project involve?▼

6. Are the classes live or pre-recorded?▼

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

8. Are EMI options available?▼

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

10. Do you provide placement assistance?▼

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

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

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

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

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

16. Is classroom training available in Bhubaneswar?▼

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

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