#1 India's Top IT Training Institute

×

About Uncodemy

Know more about who we are and what we stand for.

About Us

About Us

Discover our mission to equip individuals with essential IT skills and industry expertise.

Read More →
UnCodeMy Gallery

UnCodeMy Gallery

Explore highlights from our IT training sessions and success stories.

Read More →
×

Free Resources

Learn, practice and plan your career — bilkul free.

Tutorials

Tutorials

Step-by-step written tutorials to learn any technology at your own pace.

Read More →
Free Counselling

Free Counselling

Book a free video counselling session and pick the right course for you.

Read More →
Online Compiler

Online Compiler

Write, run and test your code online — no setup required.

Read More →
🔥 Most Popular in Pune

LLM Engineering Training Course in Pune by Uncodemy

For Hyderabad learners, Uncodemy offers a 5–6 month LLM Engineering program conducted entirely online with live sessions led by instructors. The curriculum introduces LLM APIs, embeddings and vector databases, RAG pipelines, fine-tuning, LLM agents and tool calling, as well as deployment concepts. The program is intended for developers, data scientists/ML engineers and aspiring AI engineers, and features 13 modules, 100+ live classes, 160+ hours of learning and an enterprise LLM capstone. Course fees are ₹17,500 plus 18% GST, making the total ₹20,650. EMI plans begin at ₹4,032/month.

Google4.7/5 (500+)Sulekha5/5 (30+)Just Dial4.7/5 (500+)Facebook5/5Mouthshut4/5 (130+)Trustindex5/5 (54+)
⚡SPECIAL LIMITED TIME OFFER

Special Offer: LLM Engineering Program

Now Pay Only
₹17,500/-
+ 18% GST
No Hidden Charges
100% Transparent
Total ₹20,650
Incl. 18% GST
EMI AVAILABLE
Starting ₹4,032/M*
Fill Your Details
🔒 Your information is safe and secure.

Expert Trainers

Learn from 8+ years experienced professionals

Hands-on Automation Projects

Build real Playwright 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 Pune — 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; Pune 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

Graduates of Uncodemy’s LLM Engineering program build practical skills relevant to today’s AI roles, including LLM APIs, RAG pipelines, fine-tuning, vector databases and LLM agents. Once their training and career preparation are complete, qualified learners may pursue roles such as LLM Engineer, AI Engineer and RAG/AI Application Engineer. Placement information for Pune learners is refreshed regularly — check verified outcomes at uncodemy.com/placement.

What is LLM Engineering?

LLM engineering is the practice of developing, refining and deploying applications powered by large language models. While conventional software engineering is largely based on deterministic programming and data science centres on predictive modelling from available data, LLM engineering deals with probabilistic outputs, prompt engineering, retrieval pipelines and model fine-tuning. It combines principles from software engineering, machine learning and product development to convert the capabilities of language models into robust features that can operate effectively in production.

What does an LLM engineer do? An LLM engineer develops LLM-powered applications by working with APIs and SDKs, creating RAG pipelines with embeddings and vector databases, fine-tuning models for domain-specific requirements, implementing LLM agents and tool calling, evaluating model performance, and managing deployment. Their everyday activities can include Python scripting, prompt engineering, retrieval assessment, API integration, and leveraging frameworks like LangChain to connect models, data and tools into usable application workflows.

LLM Engineering vs Generative AI vs Data Science

LLM Engineering involves building, refining and deploying applications driven by large language models, while Generative AI & Agentic AI highlights autonomous agents and Data Science concentrates 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 5–6 month LLM Engineering program is conducted through live online classes, featuring 100+ sessions and 160+ hours of structured learning. Across 13 modules, learners move from Generative AI foundations through 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 finally a 20-hour Enterprise LLM capstone. Each module pairs theoretical understanding with practical exercises using real development tools, and learners complete hands-on projects, RAG applications and an enterprise-level capstone. The entire course is offered live online to Pune learners and participants 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.
  • Pune-based learners seeking instructor-led live online training with hands-on projects.

Eligibility: Programming fundamentals can be helpful, but learners do not need prior programming experience since Python begins in Module 2. Having some knowledge of basic ML/NLP concepts is useful, with the core concepts introduced in Module 3. Practical classes require a laptop and dependable internet connectivity.

Upcoming LLM Engineering Course Batches for Pune Learners

Find a batch schedule that matches your availability. Live online sessions are delivered using IST timings. You can register for a free demo class to experience the hands-on approach or select an upcoming weekday or weekend live batch — structured with flexible timings and practical learning for students and working professionals.

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 Pune

LLM Engineering Course Syllabus in Pune

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 Pune

On completing the 13-course-module curriculum, required assignments and Enterprise LLM capstone project, learners become eligible for the Uncodemy LLM Engineering Program Certificate. The credential displays the program title, duration, technologies and tools covered, along with the completion date. It is digitally verifiable at certificate.uncodemy.com and acts as a formal record confirming successful completion of the Uncodemy LLM Engineering program.

The certificate is tied to the practical activities performed during training, including RAG application development, fine-tuning tasks and the 20-hour Enterprise LLM capstone. 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 institute providing IT and technology training. The institute brings 14+ years of training experience, physical centres in Delhi and Noida, and live online instruction for learners across India, with programs taught by experienced instructors in emerging technology areas.

As part of the LLM Engineering program, learners work on RAG applications, model fine-tuning, LLM agents with tool calling and an enterprise LLM capstone project. The course focuses on how LLM applications are developed for production, including prompt design, retrieval pipelines, model adaptation and deployment. Learners can explore the complete module-by-module curriculum before deciding to enrol.

Learners also receive live instructor-led training, practical assignments, project-based activities, interview preparation and career support. The career support policy explains what assistance covers and its limitations, while the eligibility conditions are communicated before enrolment and payment.

Other courses for Pune learners

If you are still deciding on a direction, Uncodemy also runs Generative AI , Data Science and Playwright Automation Testing courses for Pune 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
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 distinguishes between teaching and curriculum review instead of assigning both responsibilities to one role. Trainers deliver the live learning sessions, whereas independent domain reviewers, who are separate from the batch instructors, examine the curriculum for technical accuracy and current relevance. The LLM Engineering program has its curriculum and technical material reviewed by Mr. Irshad, along with an additional review by Mr. Upendra Kumar Tiwari. This provides an additional layer of technical review beyond the person conducting the classes.

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 Pune Learners Today!

Start with Uncodemy’s LLM Engineering course tailored for Pune learners. In live, instructor-led online classes, you will gain hands-on experience with LLM APIs, RAG pipelines, fine-tuning and LLM agents, along with practical projects and an enterprise LLM capstone. Take the next step in LLM engineering through structured training and focused career preparation.

LLM Engineer Jobs and Career Scope in Pune+

Pune stands as India's most established technology and startup hub, home to a dense concentration of product companies, global capability centres, AI-first startups, SaaS firms and fintech leaders. Organisations across Hinjawadi, Kharadi, Baner, Wakad, Viman Nagar, Magarpatta and Hadapsar are embedding LLM features into their products — conversational assistants, RAG-based knowledge systems, document-intelligence pipelines and multi-agent workflows — creating strong demand for engineers who understand LLM APIs, retrieval architectures, fine-tuning trade-offs and production deployment. BFSI, healthcare, edtech, e-commerce, gaming and enterprise SaaS sectors in Pune are also adopting GenAI rapidly, and they want engineers who can ship dependable LLM-powered applications at scale rather than quick demos. Interviews here 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 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 Pune — Role-wise+

Salaries in Pune 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 Pune+

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 Pune specifically, LLM engineering demand is emerging in:
  • Product companies and global capability centres — Hinjawadi, Kharadi and Baner, integrating LLMs into enterprise products
  • AI-first startups and SaaS firms — building assistants, agents and RAG-based features
  • BFSI and fintech — deploying LLMs for risk, fraud detection, underwriting and customer support
  • Healthcare and life sciences — LLMs for clinical documentation, diagnostics and patient engagement
  • E-commerce, edtech and gaming — LLMs for personalization, content, recommendation 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 Pune+

Pune 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; Pune 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 Pune-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 does the LLM Engineering course in Pune span?▼

It runs for 5–6 months, delivering 160+ hours of learning through 100+ live sessions. Weekday and weekend batch options are both provided.

2. Must I already know Python or ML to join?▼

Not required. Programming familiarity helps but is optional — Python is introduced from Module 2, and fundamental ML/NLP concepts are covered in Module 3. A laptop and reliable internet are needed.

3. What tools does this course cover?▼

Over 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. Will I learn fine-tuning and LLM agents?▼

Yes, both are central to the syllabus. Module 10 (15 hours) is dedicated to Fine-Tuning & Model Adaptation, and Module 11 (15 hours) to LLM Agents & Tool Calling. Each involves practical exercises.

5. What does the capstone project consist of?▼

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

6. Are sessions taught live or recorded?▼

All 100+ sessions are live and led by an instructor. Recordings are provided afterwards so you can revise whenever needed.

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

The program costs ₹17,500 + 18% GST, for a total of ₹20,650. The same pricing applies across every city and delivery mode.

8. Is EMI available?▼

Yes, EMIs start at ₹4,032 per month. Exact amount, duration and eligibility depend on the chosen payment or financing option — your counsellor can confirm the plan.

9. Can I attend a demo class first?▼

Absolutely. A demo session lets you experience the teaching approach, meet the trainer and preview the curriculum before you commit. Contact us to book one.

10. Does Uncodemy offer placement assistance?▼

Yes — Dedicated Career & Placement Assistance includes resume development, LinkedIn optimisation, portfolio review, interview preparation, mock interviews, and opportunity sharing through our network of 850+ companies. Employment is not guaranteed.

11. Could I land an entry-level LLM Engineer role after the course?▼

Entry-level LLM Engineer positions in the market typically sit around ₹6–10 LPA (indicative). Actual outcomes vary by skills, background, employer and market conditions. Uncodemy does not guarantee any specific salary or employment outcome.

12. How much does an LLM Engineer earn in Pune?▼

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

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

Common 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?▼

Ideal candidates include developers looking to specialise in LLM-powered applications, data scientists and ML engineers upskilling into LLM engineering, aspiring AI engineers, and working professionals moving into GenAI/LLM roles.

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

These figures 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. Is physical classroom training available in Pune?▼

The LLM Engineering course is delivered fully live online across India, including for Pune learners. Classroom training for other courses is available at our Delhi and Noida centres. Pune 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
  • Review counts verified against respective third-party platforms
  • Last reviewed:

Written by:Mr. Rahul

Reviewed by: Mr. Upendra Kumar Tiwari

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

Application Form
Visit Us

Nearest Classroom Training Centres

Open now
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
Free demo classWalk-ins welcomeWheelchair accessible
Delhi Map Noida Map
⇧