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🔥 Most Popular in Kolkata

LLM Engineering Training Course in Kolkata by Uncodemy

Uncodemy presents a 5–6 month live online RAG Engineering certification for Kolkata-based learners, delivered through instructor-led sessions. The curriculum takes you through document ingestion and chunking, embeddings, vector databases, retrieval pipelines, hybrid search, and the deployment of production-ready RAG systems. It is built for developers, data scientists/ML engineers, and aspiring AI engineers. The program comprises 13 modules, 90+ live sessions, 140+ hours of learning, and an enterprise-level RAG capstone. Course fee: ₹17,500 plus 18% GST, amounting to ₹20,650. EMI options begin at ₹4,032 per 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

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100% Transparent
Total ₹20,650
Incl. 18% GST
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 — Live Online Certification Track A practice-driven course built to develop real LLM engineering competencies and get you interview-ready.
A rigorous five-to-six month live online program conducted by instructors that dives into LLM APIs, embeddings & vector databases, RAG, fine-tuning, LLM agents & tool calling, and deployment, complemented by real-world projects, one-on-one mentoring, and career readiness 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 Kolkata — 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; Kolkata learners join live online)
✅ Prior Coding:
Programming fundamentals helpful; Python taught from Module 2 onward. Basic ML/NLP built up in Module 3.
📜 Certificate:
Uncodemy LLM Engineering Program Certificate (verifiable online)
🗓️ Last Reviewed:
3 October 2026

List of Placed Students Trained by Uncodemy

Graduates of the Uncodemy LLM Engineering program emerge with practical, employer-ready capabilities spanning LLM APIs, RAG pipelines, fine-tuning, vector databases, and LLM agents. After training and career preparation conclude, eligible learners can pursue positions such as LLM Engineer, AI Engineer, and RAG/AI Application Engineer. Placement data for Kolkata learners is refreshed periodically — examine verified outcomes at uncodemy.com/placement.

What is LLM Engineering?

LLM engineering is a specialised discipline focused on architecting, constructing, refining, and deploying applications that depend on large language models. Whereas conventional software engineering operates on deterministic logic and data science centres on predictive modelling from data, LLM engineering navigates probabilistic model behaviour, prompt design, retrieval pipelines, and model adaptation. It occupies the crossroads where software engineering, machine learning, and product development intersect, transforming raw LLM capabilities into trustworthy, production-grade features.

What does an LLM engineer do? An LLM engineer works extensively with LLM APIs and SDKs, assembles RAG pipelines with embeddings and vector databases, fine-tunes models to suit particular domains, engineers LLM agents that invoke tools, assesses model outputs, and deploys LLM-driven applications. On any given day, this involves Python scripting, prompt engineering, retrieval evaluation, API integration, and leveraging frameworks like LangChain to bring models, data, and tools together into unified applications.

LLM Engineering vs Generative AI vs Data Science

LLM Engineering centres on creating, refining, and launching applications driven by large language models, whereas Generative AI & Agentic AI places its emphasis on self-governing agents, and Data Science is dedicated to the development of predictive models.

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 program spans 5–6 months and is delivered entirely through live online sessions, offering 100+ live classes and more than 160 hours of learning. It consists of 13 modules that progress from Generative AI basics to Python for LLM engineering, ML & NLP foundations, 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 blends theoretical concepts with practical exercises using real-world tools, and the program finishes with hands-on projects, RAG applications, and an enterprise capstone. Delivery is 100% live online, catering to learners in Kolkata and across the country.

Who should join this course:

  • Developers who wish to specialise in LLM-driven applications and generative AI.
  • Data scientists and ML engineers wanting to upskill into LLM engineering and RAG pipelines.
  • Aspiring AI engineers focused on building production-ready LLM applications.
  • Working professionals moving into GenAI/LLM roles from software or analytics backgrounds.
  • Kolkata-based learners looking for instructor-led live online training with hands-on projects.

Eligibility: Programming fundamentals are beneficial but not required — Python is introduced from Module 2 onward. Familiarity with basic ML/NLP concepts is an advantage but is covered in Module 3. A laptop with a stable internet connection is necessary for practical sessions.

Upcoming LLM Engineering Course Batches for Kolkata Learners

Secure a batch slot that fits your schedule. Live online batches run in IST. You can book a free demo class for a preview, or join an upcoming weekday or weekend live batch — designed for working professionals and students alike, with flexible timings and practical 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 Kolkata

LLM Engineering Course Syllabus in Kolkata

The syllabus spans 13 modules and 160 hours. Its sequence mirrors how LLM engineering is practised in the field: foundations → Python → ML/NLP essentials → transformer architecture → prompt engineering → LLM APIs → embeddings/vector DBs → RAG → application development → fine-tuning → agents & tool calling → evaluation/deployment → capstone. Every module includes practical work with real tools, and the program finishes 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 Kolkata

After successfully finishing all 13 modules, the assignments and the Enterprise LLM capstone project, you will be awarded the Uncodemy LLM Engineering Program Certificate. The certificate mentions the program name, duration, tools covered and the date of completion. It remains verifiable online at certificate.uncodemy.com and serves as an official record of your successful completion of the Uncodemy LLM Engineering program.

The certificate reflects the practical work you carry out during the program — including hands-on RAG applications, fine-tuning exercises and the 20-hour Enterprise LLM capstone project. Across the program, you will be working 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 :Offers a record of successful completion of the LLM Engineering program.
  • Online Verification :Certificate can be verified online at certificate.uncodemy.com.
  • Practical Learning :Training covers 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 Kolkata
Uncodemy LLM Engineering Program Certificate — Kolkata
Uncodemy MSME registration certificate — Kolkata

Tools and Technologies Covered

Apply Now

Introducing Uncodemy

Uncodemy is a career-focused IT training institute run by Uncodemy Edutech Pvt. Ltd. With more than 14 years of training excellence, physical classroom centres in Delhi and Noida, and live online sessions that connect with learners throughout India, Uncodemy delivers instructor-led training in emerging technologies.

Through this LLM Engineering program, participants create RAG applications, fine-tune models, design LLM agents with tool calling, and finish an enterprise LLM capstone project. The training explores how LLM-powered applications are engineered in production — from prompt design and retrieval pipelines to model adaptation and deployment. You can explore the full module-by-module curriculum before enrolling.

Beyond training, Uncodemy offers instructor-led sessions, practical assignments, project-based learning, interview preparation and career support. The specifics of what that support covers — and what it does not — are detailed in our career support policy, together with the eligibility conditions published before enrolment rather than after payment.

Other courses for Kolkata learners

If you are still deciding on a direction, Uncodemy also runs Generative AI , Data Science and Playwright Automation Testing courses for Madurai and Tamil Nadu learners.

Portfolio/capstone project review:Your practical RAG applications, fine-tuning work and enterprise LLM capstone are reviewed and polished into a portfolio that carries weight in interviews.

Resume & LinkedIn:We craft your resume around LLM engineering keywords and measurable outcomes, and tune your LinkedIn profile to align with it.

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 fix.

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 treats two roles as deliberately distinct that many institutes collapse into one. Trainers conduct the live sessions. Domain reviewers — independent specialists who don't teach the batch — check that 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 verifying 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 Kolkata Learners Today!

Sign up for Uncodemy's LLM Engineering course built for Kolkata learners. Through live, instructor-led online sessions, you will sharpen practical command of LLM APIs, RAG pipelines, fine-tuning and LLM agents — reinforced by genuine projects and an enterprise LLM capstone. Kickstart your LLM engineering journey with structured training and career preparation.

LLM Engineer Jobs and Career Scope in Kolkata+

Kolkata remains one of eastern India's most significant commercial and technological hubs, anchored by IT services majors, BFSI back-offices, consulting firms, media houses, edtech players and a growing cluster of AI and SaaS startups. Organisations across Salt Lake Sector V, New Town, Rajarhat, Park Street, Salt Lake and Behala are integrating LLM capabilities into their products — virtual assistants, RAG-powered knowledge systems, document processing pipelines and multi-agent workflows — fuelling demand for engineers familiar with LLM APIs, retrieval architectures, fine-tuning trade-offs and production deployment. BFSI, insurance, media, healthcare, edtech and e-commerce sectors across Kolkata are also adopting GenAI at pace, and they want engineers who can ship dependable LLM-powered applications at scale rather than quick demos. Interviews here emphasise system design for LLM applications, RAG pipeline architecture and debugging, evaluation strategy, and fine-tuning trade-offs. Candidates combining software engineering or data/ML backgrounds with LLM engineering skills are especially well-positioned for these roles.

Job Roles After This Course+

LLM Engineer, AI Engineer, RAG/AI Application Engineer, Generative AI Engineer, ML Engineer (LLM-focused) and AI Solutions Architect (Junior) are the roles this course maps to. Each role involves building, fine-tuning or deploying LLM-powered applications, but they differ in the specific LLM components and tools used.
Role Core Tools
LLM Engineer LLM APIs, LangChain, Python, Vector DBs
AI Engineer Python, Hugging Face, RAG, Fine-Tuning
RAG/AI Application Engineer LangChain, Vector DBs, Embeddings
Generative AI Engineer LLM APIs, Prompt Engineering, Python
ML Engineer (LLM-focused) Hugging Face, Fine-Tuning, Evaluation Tools
AI Solutions Architect (Junior) LangChain, Deployment Tools, Python
Most graduates start as an LLM Engineer, AI Engineer or RAG/AI Application Engineer and move into the others with two to four years of experience, as they build depth in a specific LLM component or domain. Progression typically involves owning larger systems, leading projects, and specialising in fine-tuning, agents or deployment architecture.

LLM Engineer Salary in Kolkata — Role-wise+

Salaries in Kolkata 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 Kolkata+

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 Kolkata specifically, LLM engineering demand is emerging in:
  • IT services and global capability centres — Salt Lake Sector V, New Town and Rajarhat, integrating LLMs into enterprise workflows
  • Product companies and SaaS firms — building assistants, agents and RAG-powered features
  • BFSI, insurance and consulting — deploying LLMs for risk, fraud detection and customer support
  • Media, healthcare and life sciences — LLMs for content, documentation and research support
  • E-commerce, edtech and enterprise SaaS — 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 Kolkata+

Kolkata 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; Kolkata 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 Kolkata-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 length of the LLM Engineering course in Kolkata?▼

The course extends over 5–6 months and delivers 160+ hours of learning through 100+ live sessions. Learners can choose between weekday and weekend batches.

2. Must I know Python or ML before I enrol?▼

No prior exposure is mandatory. Basic programming awareness assists but isn't required — Python is introduced from Module 2 onward, and essential ML/NLP concepts are covered in Module 3. A laptop with steady internet is needed.

3. Which tools will the course cover?▼

The course covers 15+ tools — LLM APIs & SDKs (OpenAI/Gemini/Claude-style), LangChain, Vector Databases (FAISS/Chroma/Pinecone), Python, Hugging Face Transformers, prompt engineering tools, fine-tuning frameworks, evaluation/observability tools, and Git & GitHub.

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

Yes, both sit at the core of the syllabus. Fine-Tuning & Model Adaptation is covered in Module 10 (15 hours), and LLM Agents & Tool Calling in Module 11 (15 hours). Both are hands-on modules.

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

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

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

Every one of the 100+ sessions is live and led by an instructor. Recordings are shared afterwards so learners can revisit any topic at their own pace.

7. How much does the LLM Engineering course in Kolkata cost?▼

The fee is ₹17,500 plus 18% GST, bringing the total to ₹20,650. This is the same across all cities and delivery formats.

8. Do you offer EMI for the fee?▼

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

9. Can I try a demo class before I commit?▼

Yes. A demo session lets you experience the teaching style, meet the trainer and review the curriculum before making a decision. Reach out to us to schedule one.

10. Is career and placement assistance included?▼

Yes — Dedicated Career & Placement Assistance includes resume building, LinkedIn optimisation, portfolio review, interview preparation, mock interviews and opportunity sharing via our 850+ company hiring network. However, employment is not guaranteed.

11. Can this course help me start as an entry-level LLM Engineer?▼

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

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

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

13. What roles can I target after this 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 enrol in this LLM Engineering course?▼

The course suits developers wanting to specialise in LLM-powered applications, data scientists and ML engineers upskilling into LLM engineering, aspiring AI engineers, and working professionals transitioning into GenAI/LLM roles.

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

All figures are drawn from Uncodemy's internal records and publicly available review platforms. Placement and salary results 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 Kolkata?▼

The LLM Engineering course is delivered fully live online across India, including for Kolkata learners. Classroom training for other courses is available at our Delhi and Noida centres. Kolkata learners typically attend live online.

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

No — it 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

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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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