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LLM Engineering Training Course in Mumbai by Uncodemy

Mumbai learners can enrol in Uncodemy's 5–6 month instructor-led LLM Engineering program, offered as a fully live online course. The curriculum journeys through LLM APIs, embeddings & vector databases, RAG, fine-tuning, LLM agents & tool calling, and deployment. It is built for developers, data scientists/ML engineers and aspiring AI engineers, and includes 13 modules, 100+ live sessions, 160+ hours and an enterprise LLM capstone. Fee: ₹17,500 + 18% GST, total ₹20,650. EMI starting from ₹4,032/month.

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Learn from 8+ years experienced professionals

Hands-on Automation Projects

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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 Mumbai — 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; Mumbai 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:

25 September 2026

List of Placed Students Trained by Uncodemy

Learners who complete Uncodemy's LLM Engineering program develop useful, applied skills in LLM APIs, RAG pipelines, fine-tuning, vector databases and LLM agents. Once the training and career preparation wrap up, eligible learners can chase roles such as LLM Engineer, AI Engineer and RAG/AI Application Engineer. Placement records for Mumbai learners are refreshed regularly — view verified outcomes at uncodemy.com/placement.

What is LLM Engineering?

LLM engineering is the craft of shaping, developing, tuning and releasing applications whose engine is a large language model. Conventional software engineering relies on deterministic logic, and data science revolves around predictive modelling from data — LLM engineering instead works with probabilistic outputs, prompt design, retrieval pipelines and model adaptation. It occupies the territory where software engineering, machine learning and product development meet, converting raw LLM capabilities into dependable, production-grade features.

What does an LLM engineer do? An LLM engineer deals with LLM APIs and SDKs, wires up RAG pipelines with embeddings and vector databases, fine-tunes models for specific domains, engineers LLM agents with tool calling, evaluates model outputs, and deploys LLM-powered applications. Daily responsibilities span Python scripting, prompt engineering, retrieval evaluation, API integration, and using frameworks such as LangChain to tie models, data and tools into coherent applications.

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

The LLM Engineering course unfolds over 5–6 months as a live online program, covering 100+ live sessions and 160+ hours of learning. It is organised into 13 modules that grow from Generative AI foundations into 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 finishes with a 20-hour Enterprise LLM capstone. Each module pairs theory with practical exercises using real tools, and the program wraps up with hands-on projects, RAG applications and an enterprise capstone. Delivery is entirely live online, catering to Mumbai and learners across the country.

Who should join this course:

Developers who want 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.
Mumbai-based learners seeking instructor-led live online training with hands-on projects.

Eligibility: Programming fundamentals are helpful but not mandatory — Python is taught from Module 2 onward. Comfort with basic ML/NLP concepts is a plus but built up in Module 3. A laptop with stable internet is required for practical sessions.

Upcoming LLM Engineering Course Batches for Mumbai Learners

Pick a batch slot that works for you. Live online batches run in IST timings. Book a free demo class for a preview, or enrol in one of our upcoming weekday or weekend live batches — designed for working professionals and students alike, with flexible timing and hands-on training.

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 Mumbai

LLM Engineering Course Syllabus in Mumbai

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 Mumbai

After successfully finishing all 13 modules, the assignments and the Enterprise LLM capstone project, you will be presented with the Uncodemy LLM Engineering Program Certificate. The certificate records the program name, duration, tools covered and completion date. It can be verified online at certificate.uncodemy.com and stands as a formal record of successful completion of the Uncodemy LLM Engineering program.

The certificate is anchored to the practical work completed during the program — including 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 is a career-oriented IT training institute, run by Uncodemy Edutech Pvt. Ltd. Boasting 14+ years of training excellence, physical training centres in Delhi and Noida, and live online classes that reach learners across India, Uncodemy provides instructor-led training in emerging technologies.

In this LLM Engineering program, learners build RAG applications, fine-tune models, design LLM agents with tool calling, and complete an enterprise LLM capstone project. The training covers how LLM-powered applications are engineered in production — prompt design, retrieval pipelines, model adaptation and deployment. You can read the full module-by-module curriculum before you enrol.

Alongside training, Uncodemy provides instructor-led sessions, practical assignments, project-based learning, interview preparation and career support. What that support includes — and what it does not — is set out in our career support policy, along with the eligibility conditions published before enrolment rather than after payment.

Other courses for Mumbai learners

If you are still deciding on a direction, Uncodemy also runs Generative AI , Data Science and Playwright Automation Testing courses for Mumbai and Maharashtra 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 keeps two functions apart that most institutes blend together. Trainers conduct the live sessions. Domain reviewers — independent specialists who don't teach the batch — verify that 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 ensures the person teaching a course isn't the only person checking whether its content is correct.

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

Enroll in Our LLM Engineering Training for Mumbai Learners Today!

Register for Uncodemy's LLM Engineering course customised for Mumbai learners. Via live, instructor-led online sessions, you'll acquire hands-on capability in LLM APIs, RAG pipelines, fine-tuning and LLM agents — reinforced by real-world projects and an enterprise LLM capstone. Launch your LLM engineering journey with structured training and career preparation.

LLM Engineer Jobs and Career Scope in Mumbai+

Mumbai, India's financial and commercial nerve centre, hosts an unmatched concentration of BFSI, fintech, media, entertainment, retail and enterprise SaaS companies, alongside a fast-maturing startup ecosystem. Firms across BKC, Lower Parel, Powai, Andheri East, Malad and Navi Mumbai are embedding LLM features into their platforms — virtual assistants for customer service, RAG-driven knowledge systems, document-processing workflows and multi-agent automations — pushing demand for engineers skilled in LLM APIs, retrieval architectures, fine-tuning trade-offs and production deployment. Banking, insurance, capital markets, fintech, healthcare, media and retail verticals in Mumbai are also adopting GenAI at pace, and they want engineers who can ship production-grade LLM-powered applications rather than throwaway demos. Mumbai interviews lean heavily on system design for LLM applications, RAG pipeline architecture and debugging, evaluation strategy, and fine-tuning trade-offs. Candidates with software engineering or data/ML experience combined with LLM engineering skills are particularly well-placed 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 Mumbai — Role-wise+

Salaries in Mumbai 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 Mumbai+

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 Mumbai specifically, LLM engineering demand is emerging in:

BFSI, fintech and capital markets — BKC, Lower Parel and Andheri East, using LLMs for risk, fraud, underwriting and advisory
Media, entertainment and gaming — LLMs for content generation, personalization and localization
Product companies and SaaS firms — building assistants, agents and RAG-driven features
Retail, e-commerce and D2C — LLMs for personalization, customer support and merchandising
Healthcare, logistics and enterprise services — LLMs for documentation, triage and operational intelligence

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 Mumbai+

Mumbai 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; Mumbai learners typically join live online. 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 Mumbai-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. What is the duration of the LLM Engineering course in Mumbai?▼

The course runs for 5–6 months and provides 160+ hours of training across 100+ live sessions. Both weekday and weekend options are available.

2. Do I need to know Python or ML before joining?▼

You don't need prior experience. Programming basics help but aren't mandatory — Python is introduced from Module 2 onward, and fundamental ML/NLP topics are covered in Module 3. A laptop with stable internet is required.

3. What tools does the course cover?▼

The course covers 15+ tools, including 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 cover fine-tuning and LLM agents?▼

Yes. Fine-Tuning & Model Adaptation is a dedicated 15-hour module (Module 10), and LLM Agents & Tool Calling is covered in Module 11 (15 hours). Both include hands-on work.

5. What will I build for the capstone project?▼

The capstone (Module 13: Enterprise LLM Projects & Capstone, 20 hours) involves building a complete LLM-powered application that integrates RAG, fine-tuning, agents and deployment.

6. Are classes live or recorded?▼

Every one of the 100+ sessions is live and led by an instructor. Recordings are provided for later revision.

7. What is the fee for the LLM Engineering course in Mumbai?▼

The program fee is ₹17,500 + 18% GST, making the total ₹20,650. This pricing is consistent across all cities and modes of delivery.

8. Are EMI plans offered?▼

Yes, EMI plans start from ₹4,032 per month. The exact amount, tenure and eligibility depend on the payment or financing option you select — a counsellor can confirm the details.

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

Yes. You can book a demo session to observe the teaching style, meet the trainer and review the curriculum before making a decision. Contact us to schedule a demo.

10. Is placement assistance available?▼

Yes, we provide Dedicated Career & Placement Assistance — resume building, LinkedIn optimisation, portfolio review, interview prep, mock interviews and opportunity sharing via our network of 850+ companies. We do not guarantee employment.

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

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

12. What is the salary for an LLM Engineer in Mumbai?▼

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

13. What roles can I apply for after the 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 should consider this LLM Engineering course?▼

The course suits developers looking 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?▼

The figures are based on 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. Is classroom training available in Mumbai?▼

This course is delivered fully live online for learners across India, including Mumbai. Classroom training for other courses is available at our Delhi and Noida centres. Mumbai learners typically join live online.

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

No. 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 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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The LLM Engineering course is delivered fully live online. Mumbai learners typically join live online, and our nearest classroom training centres for other courses are in Delhi and Noida. Uncodemy's Delhi centre sits on the 2nd & 3rd Floor, Maa Katyayni Complex, MB-1E, Madhuban Road, Shakarpur Extension — a 10–15 minute walk from Nirman Vihar Metro Station and Laxmi Nagar Metro Station. Uncodemy's Noida centre is at B 14-15, Udhyog Marg, Block B, Sector 1, Noida.

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Delhi Centre

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

Noida Centre

B, 14-15, Udhyog Marg, Block B, Sector 1, Noida, Uttar Pradesh 201301

Phone+91 9818366550 / +91 8766313646

Emailinfo@uncodemy.com

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LLM Engineering Training Course in Mumbai by Uncodemy

Special Offer: LLM Engineering Program

Expert Trainers

Hands-on Automation Projects

Lifetime Access

Dedicated Career & Placement Assistance

Certified Course

Flexible Batches

Why ChooseUncodemy?

Program Details

LLM Engineering Course in Mumbai — Quick Facts

List of Placed Students Trained by Uncodemy

What is LLM Engineering?

LLM Engineering vs Generative AI vs Data Science

Course Overview

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Curriculum for LLM Engineering Training Course in Mumbai

LLM Engineering Course Syllabus in Mumbai

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 Mumbai

Key Benefits of Our LLM Engineering Certification:

Tools and Technologies Covered

Introducing Uncodemy

Other courses for Mumbai learners

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LLM Engineer Jobs and Career Scope in Mumbai+

Job Roles After This Course+

LLM Engineer Salary in Mumbai — Role-wise+

Top Sectors Hiring LLM Engineers in Mumbai+

How to Become an LLM Engineer — Step by Step+

How This Course Compares to Other AI Courses in Mumbai+

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

Is this course right for you?+

Frequently Asked Questions

1. What is the duration of the LLM Engineering course in Mumbai?▼

2. Do I need to know Python or ML before joining?▼

3. What tools does the course cover?▼

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

5. What will I build for the capstone project?▼

6. Are classes live or recorded?▼

7. What is the fee for the LLM Engineering course in Mumbai?▼

8. Are EMI plans offered?▼

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

10. Is placement assistance available?▼

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

12. What is the salary for an LLM Engineer in Mumbai?▼

13. What roles can I apply for after the course?▼

14. Who should consider this LLM Engineering course?▼

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

16. Is classroom training available in Mumbai?▼

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

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