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LLM Engineering Training Course in Delhi by Uncodemy

Uncodemy offers a focused 5–6 month instructor-led LLM Engineering program designed for learners in Delhi. The curriculum covers LLM APIs and SDKs, embeddings with vector databases, Retrieval-Augmented Generation (RAG), fine-tuning techniques, and LLM agents with tool calling. Classes are available in classroom mode at our Delhi centre as well as live online. The program fee is ₹17,500 + 18% GST, bringing the total to ₹20,650.

4.7/5 (500+)

5/5 (30+)

4.7/5 (500+)

5/5

4/5 (130+) Trustindex

5/5 (54+)

1,200+ Reviews Across Major Platforms*

*Ratings and review counts reflect current publicly available platform information and may change over time.

⚡SPECIAL LIMITED TIME OFFER

Special Offer: LLM Engineering Program

Now Pay Only

₹17,500/-

+ 18% GST

No Hidden Charges | EMI Available — Starting from ₹4,032/month*

Location: Delhi | Nearby cities | Online

No Hidden Charges

100% Transparent

Total ₹20,650

Incl. 18% GST

EMI AVAILABLE

Starting ₹4,032/M*

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Expert Trainers

30+ Industry Trainers & Mentors

Hands-on Projects & RAG Applications

Build real LLM-powered applications, 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

Transparent Fees

EMI Options Available

Dedicated Support

Program Details

LLM Engineering Course — Live Online Program Practical learning designed to build LLM engineering skills and prepare for technical interviews.

A structured 5–6 month instructor-led live online program designed to build practical skills in LLM APIs, embeddings and vector databases, RAG, fine-tuning, LLM agents and tool calling, and deployment, supported by real-world projects, mentoring, and career guidance.

📚 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 Delhi — 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 centres; Delhi learners join live online for this course)

✅ 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

Learners who complete the LLM Engineering program develop practical skills in building and deploying LLM-powered applications. These capabilities prepare them for roles such as LLM Engineer, AI Engineer and RAG / AI Application Engineer. Placement records for Delhi learners are updated regularly — view verified outcomes at uncodemy.com/placement.

What is LLM Engineering?

LLM Engineering focuses on designing, building, fine-tuning and deploying applications that run on large language models. It differs from traditional software engineering and data science by concentrating specifically on the full lifecycle of LLM-based systems rather than general application development or pure predictive modelling.

An LLM engineer typically works with LLM APIs and SDKs, constructs Retrieval-Augmented Generation pipelines, fine-tunes models for domain needs, designs agents that can call external tools, and evaluates and deploys the resulting applications into production environments.

LLM Engineering vs Generative AI & Agentic 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 & Agentic 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)	Varies by role	₹4–8 LPA
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

The LLM Engineering program runs for 5–6 months and includes more than 100 live sessions amounting to 160+ hours of learning across 13 modules. Learners progress from foundations through Python, machine learning and NLP basics, transformer architecture, prompt engineering, LLM APIs, embeddings and vector databases, RAG systems, application development, fine-tuning, agents with tool calling, evaluation and deployment, ending with an enterprise-level capstone. Delhi learners can attend classroom sessions at our Delhi centre or join live online batches.

Who should join this course:

Developers who want to specialise in building production-ready LLM-powered applications.
Data scientists and ML engineers looking to upskill into LLM engineering roles.
Aspiring AI engineers seeking structured, hands-on training in large language models.
Working professionals transitioning into Generative AI or LLM-focused positions.
Delhi-based learners who prefer the option of in-person classroom training.

Eligibility: A working knowledge of programming fundamentals is helpful. Python is taught from the basics in Module 2. Familiarity with core machine-learning or NLP ideas is an advantage but is covered in Module 3. Participants need a laptop and a stable internet connection for live sessions and project work.

Upcoming LLM Engineering Course Batches for Delhi Learners

8+ new batches start every month. All timings are in IST. Secure a free demo class for an initial preview, or join one of our upcoming weekday or weekend live batches — designed for working professionals and students alike.

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 Delhi

LLM Engineering Course Syllabus in Delhi

The 13-module curriculum delivers 160 hours of structured learning. It moves systematically from foundational concepts through Python, machine-learning and NLP basics, transformer architecture, prompt engineering, LLM APIs, embeddings and vector databases, Retrieval-Augmented Generation, application development, fine-tuning, agents and tool calling, evaluation and deployment, and culminates in an enterprise capstone project.

Module 1: LLM & Generative AI Foundations — 8 Hours

Introduction to large language models and generative AI
Evolution of language models
Key capabilities and limitations of modern LLMs
Overview of popular LLM families
Ethical considerations and responsible use
High-level architecture concepts

Module 2: Python for LLM Engineering — 10 Hours

Python fundamentals for AI workflows
Data structures and control flow relevant to LLM work
Working with APIs in Python
Libraries commonly used in LLM pipelines
Environment setup and package management
Basic scripting for data preparation

Module 3: Machine Learning & NLP Fundamentals — 10 Hours

Core machine-learning concepts
Supervised and unsupervised learning overview
Text preprocessing and tokenization
Classic NLP techniques
Evaluation metrics for language tasks
Bridging traditional NLP to modern LLMs

Module 4: Transformers & LLM Architecture — 12 Hours

Attention mechanisms and self-attention
Transformer encoder-decoder structure
Positional encodings
Pre-training and post-training paradigms
Scaling laws and model size considerations
Architectural variants used in production LLMs

Module 5: Prompt Engineering & Structured Outputs — 8 Hours

Prompt design principles
Zero-shot, few-shot and chain-of-thought prompting
Structured output techniques
System and user message strategies
Prompt iteration and testing
Common failure modes and mitigations

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

Authentication and rate-limit handling
Chat and completion endpoints
Streaming responses
Function/tool calling interfaces
Cost and latency considerations
Error handling and retries

Module 7: Embeddings & Vector Databases — 10 Hours

Text embeddings and similarity search
Popular embedding models
Vector database concepts
Indexing strategies
Hybrid search approaches
Integration patterns with LLM applications

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

RAG architecture and components
Document loading and chunking strategies
Retrieval quality and ranking
Context construction and prompt assembly
Advanced RAG patterns
Evaluation of RAG systems

Module 9: LLM Application Development — 12 Hours

Building end-to-end LLM applications
Conversation memory and state management
User interface considerations
Logging and observability basics
Security and input validation
Deployment-ready code structure

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

When to fine-tune versus prompt
Parameter-efficient fine-tuning methods
Data preparation for fine-tuning
Training loops and monitoring
Evaluation after fine-tuning
Serving fine-tuned models

Module 11: LLM Agents & Tool Calling — 15 Hours

Agent architectures and planning
Tool definition and registration
Multi-step reasoning patterns
Error recovery in agent loops
Multi-agent considerations
Practical agent implementation

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

Evaluation frameworks and metrics
Latency and cost optimisation
Guardrails and safety layers
Monitoring in production
Scaling and infrastructure choices
Continuous improvement loops

Module 13: Enterprise LLM Projects & Capstone — 20 Hours

End-to-end project planning
Requirements gathering for LLM systems
Architecture design and trade-offs
Implementation of a complete solution
Documentation and presentation
Peer and mentor review

#	Module	Hours	Focus Area
1	LLM & Generative AI Foundations	8	Foundations
2	Python for LLM Engineering	10	Programming
3	Machine Learning & NLP Fundamentals	10	ML/NLP
4	Transformers & LLM Architecture	12	Architecture
5	Prompt Engineering & Structured Outputs	8	Prompting
6	Working with LLM APIs & SDKs	10	APIs
7	Embeddings & Vector Databases	10	Retrieval
8	Retrieval-Augmented Generation (RAG)	15	RAG
9	LLM Application Development	12	Applications
10	Fine-Tuning & Model Adaptation	15	Fine-tuning
11	LLM Agents & Tool Calling	15	Agents
12	LLM Evaluation, Optimization & Deployment	15	Production
13	Enterprise LLM Projects & Capstone	20	Capstone
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 Delhi

On successful completion of the program, learners receive the Uncodemy LLM Engineering Program Certificate. The certificate records the program name, duration, key tools covered and the date of completion, and carries a unique verification reference.

The certificate reflects practical work completed during the course, including hands-on RAG applications, fine-tuning exercises and the Enterprise LLM capstone project.

Key Benefits of Our LLM Engineering Certification:

Program Completion :Official recognition of program completion.
Online Verification :Online verification of certificate authenticity.
Practical Learning :Evidence of practical, project-based learning.

Certificates can be verified at certificate.uncodemy.com. This is an independent Uncodemy certificate and is not affiliated with or issued by OpenAI, Google, Anthropic or any other LLM provider whose APIs are covered in the curriculum.

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 is a career-focused IT training institute operated by Uncodemy Edutech Pvt. Ltd. With more than 14 years of training excellence, the institute runs classroom centres in Delhi and Noida and delivers live online classes to learners across India.

In the LLM Engineering program, participants build practical artefacts including RAG applications, fine-tuned models, LLM agents capable of tool calling, and a substantial enterprise-level capstone project.

Learning is delivered through instructor-led sessions, regular assignments, hands-on projects and structured interview preparation, supported by dedicated career assistance. Career support policy and eligibility conditions are published before enrolment. You can read the full module-by-module curriculum before you enrol.

Other courses for Delhi learners

Other courses for Delhi learners include Generative AI & Agentic AI, AI Testing, Data Science and Playwright Automation Testing.

Portfolio and 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 building and LinkedIn optimisation: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 network of 850+ companies are shared with you, with support through the application and interview process.

Continued support:Dedicated career and placement assistance is provided. Uncodemy does not guarantee employment or any specific salary outcome.

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

Live sessions are conducted by the Uncodemy trainer team. The institute works with 30+ industry trainers and mentors who collectively bring more than 10 years of average corporate training experience.

Uncodemy maintains a clear separation between trainers who deliver the sessions and domain reviewers who verify curriculum accuracy. For the LLM Engineering program, curriculum and technical content are reviewed by Mr. Irshad, with additional review by Mr. Upendra Kumar Tiwari.

Every trainer and reviewer is published by name together with profile links where available.

Enroll in Our LLM Engineering Training for Delhi Learners Today!

Secure your seat in the next available batch and start building production-ready LLM applications. Classroom sessions are available at our Delhi centre, with live online options for flexible learning. Reach out to the admissions team to discuss batch timings, fee payment options and next steps.

LLM Engineer Jobs and Career Scope in Delhi+

Delhi has grown into a major technology and business hub within Delhi NCR, hosting a dense concentration of IT services firms, captive centres, media houses, BFSI back-offices, electronics manufacturers and fast-growing AI and SaaS startups. Organisations across Connaught Place, Nehru Place, Okhla, Gurugram border, Noida Expressway and Greater Noida West are adding LLM capabilities — conversational assistants, RAG-powered knowledge systems, document processing pipelines and multi-agent workflows — fuelling demand for engineers familiar with LLM APIs, retrieval architectures, fine-tuning trade-offs and production deployment. BFSI, media, healthcare, electronics, edtech and e-commerce sectors in Delhi are also adopting GenAI rapidly, and they want engineers who can ship dependable LLM-powered applications at scale rather than quick demos. Interviews in Delhi emphasise system design for LLM applications, RAG pipeline architecture and debugging, evaluation strategy, and fine-tuning trade-offs. Candidates combining software engineering or data/ML backgrounds 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 Delhi — Role-wise+

Salaries in Delhi 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 Delhi+

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 Delhi specifically, LLM engineering demand is emerging in:

IT services and global capability centres — Connaught Place, Nehru Place and Noida Expressway, integrating LLMs into enterprise applications
Product companies and SaaS firms — building assistants, agents and RAG-powered features
BFSI and fintech — deploying LLMs for risk, fraud detection and customer support
Media, electronics and manufacturing-tech — LLMs for content, diagnostics and documentation
E-commerce, edtech and healthcare — LLMs for personalization, content and customer service

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 Delhi+

Delhi 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; Delhi learners can join classroom sessions for this program. Live online offers the same instructor-led experience with zero commute, and all sessions are recorded for revision. Offline suits learners who prefer face-to-face interaction and are based near Delhi or Noida. Hybrid is not currently offered for this program. For Delhi-based working professionals, live online is usually the most practical choice — you get real-time doubt clearing, hands-on labs and lifetime access to recordings 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 many months is the LLM Engineering course in Delhi?▼

The course unfolds over 5–6 months and provides 160+ hours of instruction spread across 100+ live sessions. Weekday and weekend batch options are both open.

2. Is prior Python or ML knowledge essential to join?▼

No prior knowledge is essential. Some programming familiarity does help, but Python is introduced starting with Module 2, and essential ML/NLP concepts are covered in Module 3. Learners need a laptop with steady internet.

3. Which tools does the curriculum include?▼

The course exposes learners to 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 included in the course?▼

Yes, both are core to the syllabus. Fine-Tuning & Model Adaptation is Module 10 (15 hours), while LLM Agents & Tool Calling is Module 11 (15 hours). Both are hands-on.

5. What kind of capstone will I complete?▼

The capstone corresponds to Module 13: Enterprise LLM Projects & Capstone (20 hours). You will develop a full end-to-end LLM-driven application integrating RAG, fine-tuning, agents and deployment.

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

All 100+ sessions are conducted live and instructor-led. Recorded versions are provided after each session for revision at any time.

7. What does the LLM Engineering course in Delhi cost?▼

The fee is ₹17,500 plus 18% GST, totalling ₹20,650. This fee is identical across all cities and delivery formats.

8. Are EMI payment options offered?▼

Yes, EMI begins at ₹4,032 per month. The exact figure, tenure and eligibility depend on your chosen payment or financing option — a counsellor can confirm the details.

9. Can I attend a demo session first?▼

Of course. A demo session is available where you can see the teaching approach, speak with the trainer and review the curriculum before deciding. Contact us to book a slot.

10. Do you provide career and placement assistance?▼

We offer Dedicated Career & Placement Assistance — resume building, LinkedIn optimisation, portfolio review, interview preparation, mock interviews and opportunity sharing through our 850+ company hiring network. That said, employment is not guaranteed.

11. Can I begin my career as an entry-level LLM Engineer after this course?▼

Entry-level LLM Engineer roles in the current market offer roughly ₹6–10 LPA (indicative). Actual outcomes depend on skills, experience, employer and market conditions. Uncodemy does not guarantee any specific salary or employment outcome.

12. What does an LLM Engineer earn in Delhi?▼

Indicative market ranges: Entry-Level ₹6–10 LPA, Mid-Level ₹15–25 LPA, Senior ₹20–35 LPA, Lead ₹25–45 LPA. Actual offers depend on role, skills, experience, employer and market conditions. Uncodemy does not guarantee any specific salary.

13. Which roles can I apply for after completing this course?▼

Typical 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 the ideal candidate for this LLM Engineering course?▼

The course fits developers wanting to specialise in LLM-powered applications, data scientists and 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?▼

All data points come from Uncodemy's internal records and publicly available review platforms. Placement and salary outcomes vary by learner, skills, experience, location, employer and market conditions. Career and placement assistance is not a guarantee of employment or a specific salary package.

16. Can I attend classroom training in Delhi?▼

Yes — Delhi is home to one of Uncodemy's physical training centres at 2nd & 3rd Floor, Maa Katyayni Complex, MB-1E, Madhuban Rd, next to DSEU Ambedkar College, Laxmi Nagar, Shakarpur Extension, Shakarpur, Delhi, 110092.

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

No. It is a standalone Uncodemy certificate. 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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Classroom Training Centres in Delhi

Uncodemy offers this LLM Engineering program for learners across Delhi and Delhi NCR through two convenient learning options: live online classes that can be attended from anywhere, and classroom training at Uncodemy's Delhi centre, located at 2nd & 3rd Floor, Maa Katyayni Complex, MB-1E, Madhuban Rd, next to DSEU Ambedkar College, Laxmi Nagar, Shakarpur Extension, Shakarpur, Delhi, 110092. Delhi learners can also join the same batches online or attend classes at the Noida centre, with experienced trainers, structured learning and a consistent curriculum across all formats.

Open now

Delhi Centre (this course's home campus)

2nd & 3rd Floor, Maa Katyayni Complex, MB-1E, Madhuban Rd, next to DSEU Ambedkar College, Laxmi Nagar, Shakarpur Extension, Shakarpur, Delhi, 110092

Phone9818366550

Websiteuncodemy.com

Free demo classWalk-ins welcomeWheelchair accessible

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📍 Delhi (Laxmi Nagar, Shakarpur Extension) — Open in Google Maps

⇧

LLM Engineering Training Course in Delhi by Uncodemy

Special Offer: LLM Engineering Program

Expert Trainers

Hands-on Projects & RAG Applications

Lifetime Access

Dedicated Career & Placement Assistance

Certified Course

Flexible Batches

Why ChooseUncodemy?

Program Details

LLM Engineering Course in Delhi — Quick Facts

List of Placed Students Trained by Uncodemy

What is LLM Engineering?

LLM Engineering vs Generative AI & Agentic AI vs Data Science

Course Overview

Weekdays

Weekends

Curriculum for LLM Engineering Training Course in Delhi

LLM Engineering Course Syllabus in Delhi

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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Frequently Asked Questions

1. How many months is the LLM Engineering course in Delhi?▼

2. Is prior Python or ML knowledge essential to join?▼

3. Which tools does the curriculum include?▼

4. Are fine-tuning and LLM agents included in the course?▼

5. What kind of capstone will I complete?▼

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

7. What does the LLM Engineering course in Delhi cost?▼

8. Are EMI payment options offered?▼

9. Can I attend a demo session first?▼

10. Do you provide career and placement assistance?▼

11. Can I begin my career as an entry-level LLM Engineer after this course?▼

12. What does an LLM Engineer earn in Delhi?▼

13. Which roles can I apply for after completing this course?▼

14. Who is the ideal candidate for this LLM Engineering course?▼

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

16. Can I attend classroom training in Delhi?▼

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

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