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🔥 Most Popular in Coimbatore

LLM Engineering Training Course in Coimbatore by Uncodemy

Uncodemy's 5–6 month instructor-led LLM Engineering program is open to Coimbatore learners through a fully live online format. Participants work through LLM APIs, embeddings & vector databases, RAG, fine-tuning, LLM agents & tool calling, and deployment. Built for developers, data scientists/ML engineers and aspiring AI engineers, the program spans 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.

Google4.7/5 (500+)Sulekha5/5 (30+)Just Dial4.7/5 (500+)Facebook5/5Mouthshut4/5 (130+)Trustindex5/5 (54+)
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Special Offer: LLM Engineering Program

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Total ₹20,650
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EMI AVAILABLE
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 Coimbatore — 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; Coimbatore 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:
15 October 2026

List of Placed Students Trained by Uncodemy

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

What is LLM Engineering?

LLM engineering is the practice of designing, building, fine-tuning and deploying applications that are powered by large language models. Where traditional software engineering relies on deterministic logic and data science centres on predictive modelling from data, LLM engineering deals with probabilistic models, prompt design, retrieval pipelines and model adaptation. It sits at the intersection of software engineering, machine learning and product development, converting raw LLM capabilities into reliable, production-ready features.

What does an LLM engineer do? An LLM engineer’s responsibilities include integrating LLM APIs and SDKs, developing retrieval-augmented generation pipelines with embeddings and vector databases, fine-tuning models for niche domains, architecting LLM agents with tool-calling abilities, measuring model performance, and deploying LLM-based apps. Daily, they script in Python, engineer prompts, evaluate retrieval, integrate APIs, and employ frameworks such as LangChain to connect models, data, and tools into a working product.

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 runs for 5–6 months as a live online program, spanning 100+ live sessions and 160+ hours of learning. It's structured into 13 modules that build 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 concludes with a 20-hour Enterprise LLM capstone. Every 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 completely live online, serving Coimbatore and learners nationwide.

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.
  • Coimbatore-based learners seeking instructor-led live online training with hands-on projects.

Eligibility: Having programming fundamentals helps, but they aren't mandatory — Python gets taught starting Module 2. Comfort with basic ML/NLP topics is a bonus but built during Module 3. A laptop with dependable internet is required for the practical sessions.

Upcoming LLM Engineering Course Batches for Coimbatore Learners

Pick a batch timing that matches your schedule. Live online batches follow IST timings. You can book a free demo class to get a first-hand feel, or join one of our upcoming weekday and weekend live batches — crafted for working professionals and students alike, with flexible timings and hands-on learning.

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 Coimbatore

LLM Engineering Course Syllabus in Coimbatore

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

Module 1: LLM & Generative AI Foundations — 8 Hours

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

Module 2: Python for LLM Engineering — 10 Hours

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

Module 3: Machine Learning & NLP Fundamentals — 10 Hours

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

Module 4: Transformers & LLM Architecture — 12 Hours

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

Module 5: Prompt Engineering & Structured Outputs — 8 Hours

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

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

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

Module 7: Embeddings & Vector Databases — 10 Hours

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

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

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

Module 9: LLM Application Development — 12 Hours

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

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

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

Module 11: LLM Agents & Tool Calling — 15 Hours

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

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

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

Module 13: Enterprise LLM Projects & Capstone — 20 Hours

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

Contacted by

IR

Mr. Irshad

Curriculum & Technical Reviewer

[8+ Years Of Experience]

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

LinkedInProfile

Get Your LLM Engineering Certification In Coimbatore

After completing all 13 modules, the assignments and the Enterprise LLM capstone project, learners are awarded 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 serves as a record of successful completion of the Uncodemy LLM Engineering program.

The certificate is linked 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
Uncodemy MSME registration certificate

Tools and Technologies Covered

Apply Now

Introducing Uncodemy

Operated by Uncodemy Edutech Pvt. Ltd., Uncodemy is a career-focused IT training institute. With 14+ years of training excellence behind it, classroom centres in Delhi and Noida, and live online classes reaching learners all across India, Uncodemy provides instructor-led training in emerging technologies.

In this LLM Engineering training, learners develop RAG applications, fine-tune models, design LLM agents with tool calling, and deliver an enterprise LLM capstone project. The course addresses how LLM-powered applications are designed in production — prompt design, retrieval pipelines, model adaptation and deployment. You can check the full module-by-module curriculum before you enrol.

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

Other courses for Coimbatore learners

If you are still deciding on a direction, Uncodemy also runs Generative AI , Data Science and Playwright Automation Testing courses for Coimbatore and Tamil Nadu 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
Google Reviews
4.7/5500+ Google Reviews
Sulekha Reviews
5/530+ Sulekha Reviews
Just Dial Reviews
4.7/5500+ Just Dial Reviews
Facebook Reviews
5/5Facebook Reviews
Mouthshut Reviews
4/5130+ Mouthshut
Trustindex Reviews
5/554+ Trustindex Reviews

Instructors

The people who actually teach this course

Uncodemy keeps two roles apart that most institutes merge together. Trainers handle the live sessions. Domain reviewers — separate experts who don't teach the batch — ensure the curriculum is technically accurate and current. For this program, curriculum and technical content are reviewed by Mr. Irshad, with additional review by Mr. Upendra Kumar Tiwari. This means the person teaching a course is not the only person checking if its content is correct.

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

Enroll in Our LLM Engineering Training for Coimbatore Learners Today!

Join Uncodemy's LLM Engineering course designed for Coimbatore learners. Through live online, instructor-led sessions, you'll develop hands-on capability in LLM APIs, RAG pipelines, fine-tuning and LLM agents — supported by real projects and an enterprise LLM capstone. Begin your LLM engineering path with structured training and career preparation.

LLM Engineer Jobs and Career Scope in Coimbatore+

Coimbatore is emerging as a strong technology and engineering hub in Tamil Nadu, anchored by a mature manufacturing and textile base and a fast-growing IT and SaaS ecosystem. Organisations in Peelamedu, Saravanampatti, Ramanathapuram, Saibaba Colony and Gandhipuram are adding LLM capabilities — customer-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. Manufacturing-tech, textile-tech, healthcare, BFSI, edtech and e-commerce sectors in Coimbatore are also adopting GenAI, and they need engineers who can ship reliable LLM-powered applications rather than one-off prototypes. Interviews in Coimbatore 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 plus 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 Coimbatore — Role-wise+

Salaries in Coimbatore 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 Coimbatore+

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 Coimbatore specifically, LLM engineering demand is emerging in:
  • IT services and global capability centres — Peelamedu, Saravanampatti and Ramanathapuram, integrating LLMs into enterprise applications
  • 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
  • Manufacturing, textile-tech and automotive — LLMs for diagnostics, documentation and predictive maintenance
  • Healthcare, edtech and e-commerce — 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 Coimbatore+

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

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

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

Offline classroom is available at our Delhi and Noida centres; Coimbatore 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 Coimbatore-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 long is the LLM Engineering course in Coimbatore?▼

The course runs across 5–6 months and covers 160+ hours through 100+ live sessions. You can choose between weekday and weekend batch timings.

2. Is prior Python or ML experience necessary?▼

While basic programming familiarity is useful, it's not mandatory — Python is introduced starting in Module 2. Fundamental ML/NLP topics are covered in Module 3. A laptop with a reliable internet connection is required.

3. Which tools are taught in this course?▼

You'll work with 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, along with Git & GitHub.

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

Yes. Module 10 covers Fine-Tuning & Model Adaptation (15 hours), and Module 11 covers LLM Agents & Tool Calling (15 hours). Both are treated as core, hands-on modules.

5. What does the capstone project involve?▼

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

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

Every one of the 100+ sessions is instructor-led and live. Recordings are made available after each session so you can revise at your own pace.

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

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

8. Are EMI plans available?▼

EMI plans start from ₹4,032 per month. The precise amount, tenure and eligibility vary based on the payment or financing option selected — your counsellor can confirm the exact plan.

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

Yes, absolutely. Attending a demo session lets you observe the teaching style, interact with the trainer and review the curriculum before you commit. Reach out to us to schedule one.

10. Do you offer placement assistance?▼

Yes — we offer Dedicated Career & Placement Assistance that includes resume building, LinkedIn optimisation, portfolio review, interview preparation, mock interviews and opportunity sharing via our network of 850+ companies. That said, we do not guarantee employment.

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

Entry-level LLM Engineer positions typically fall in the ₹6–10 LPA range (indicative). Actual 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 Coimbatore?▼

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

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

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

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

This course suits developers who want to specialise in LLM-powered applications, data scientists and ML engineers looking to upskill 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 figures come from Uncodemy's internal records and publicly available review platforms. Placement and salary results vary based on the 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 Coimbatore?▼

The course runs fully live online across India, including for Coimbatore learners. Classroom training is available for other courses at our Delhi and Noida centres. Coimbatore learners typically attend 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
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Written by:Mr. Rahul

Reviewed by: Mr. Upendra Kumar Tiwari

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

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