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🔥 Most Popular in Hyderabad

LLM Engineering Training Course in Hyderabad 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+)
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Starting ₹4,032/M*
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Expert Trainers

Learn from 8+ years experienced professionals

Hands-on Automation Projects

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Lifetime Access

Get lifetime access to recorded sessions & materials

Dedicated Career & Placement Assistance

Resume Building, Mock Interviews & Job Support

Certified Course

Certificate of Completion from Uncodemy

Flexible Batches

Weekday & Weekend Online & Offline

Why Choose
Uncodemy?

14+
Years of Training Excellence
850+
Companies in Our Hiring Network
54,000+
Learners Trained
200+
Corporate Associations
100%
Placement Support
Online & Offline Classes
Weekend & Weekday Batches
100% Practical Training
Affordable Fees
EMI Options Available
Dedicated Support

Program Details

LLM Engineering Course — Live Online Program Hands-on learning that focuses on practical LLM engineering skills and interview preparation.
A comprehensive 5–6 month instructor-led live online program covering LLM APIs, embeddings & vector databases, RAG, fine-tuning, LLM agents & tool calling, and deployment along with practical projects, mentoring and career support.
📚 Learning:
160+ Hours of Learning
⏱️ Program Duration:
5–6 Months
🎓 Live Training:
100+ Live Sessions
🛠️ Technology Coverage:
15+ Tools & Technologies
💼 Practical Learning:
Hands-on Projects, RAG Applications & AI Case Studies
💰 Program Fee:
₹17,500 + 18% GST
💰 Total Fee:
₹20,650
💳 EMI:
Starting From ₹4,032/Month*
🚀 Career Support:
Dedicated Career & Placement Assistance
🏢 Hiring Network:
850+ Companies in Our Hiring Network
🎯 Career Support Includes:
Resume Building & LinkedIn Optimization, Mock Interviews & Interview Preparation, Career Guidance & Job Opportunity Assistance

LLM Engineering Course in Hyderabad — 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; Hyderabad 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

Learners completing Uncodemy’s LLM Engineering course gain hands-on, job-focused expertise in areas including LLM APIs, RAG pipelines, fine-tuning, vector databases and LLM agents. Following their technical training and career preparation, eligible participants can apply for positions such as LLM Engineer, AI Engineer and RAG/AI Application Engineer. Placement results for Hyderabad learners are updated regularly — see verified outcomes at uncodemy.com/placement.

What is LLM Engineering?

LLM engineering involves creating, developing, adapting, fine-tuning and deploying applications that use large language models. Traditional software engineering typically works through defined logic, while data science concentrates on predictive modelling using datasets; LLM engineering instead addresses probabilistic behaviour, prompt design, retrieval systems and model adaptation. The discipline sits at the intersection of software engineering, machine learning and product development, helping transform general-purpose LLM capabilities into reliable, production-ready application features.

What does an LLM engineer do? An LLM engineer uses LLM APIs and SDKs, builds RAG systems around embeddings and vector databases, adapts models through fine-tuning, develops LLM agents with tool-calling capabilities, evaluates generated outputs, and deploys LLM-based solutions. Day-to-day tasks commonly involve Python scripting, prompt engineering, retrieval evaluation, API integration, and frameworks such as LangChain to connect models with data and external tools into complete applications.

LLM Engineering vs Generative AI vs Data Science

LLM Engineering is concerned with creating, adapting and deploying LLM-powered applications, while Generative AI & Agentic AI focuses on autonomous agents and Data Science primarily addresses predictive modelling.

Aspect LLM Engineering Generative AI Data Science
Core focus Building, fine-tuning & deploying LLM-powered applications Building GenAI apps + autonomous AI agents/multi-agent systems Predictive modelling from data
Coding depth High Moderate to High High
Typical entry salary ₹6–10 LPA (Entry-Level LLM Engineer) [CONFIRM per GenAI course sheet] ₹4–8 LPA (per Data Science course sheet)
Uncodemy program duration 5–6 months ~3–4 months (indicative) 8–9 months

Salary ranges are indicative and vary by role, skills, experience, location and employer.

Course Overview

The LLM Engineering program is delivered over 5–6 months through live online instruction, with 100+ live classes and more than 160 hours of learning. Its 13 modules begin with Generative AI fundamentals and progress through Python for LLM engineering, ML & NLP basics, transformer architecture, prompt engineering, LLM APIs & SDKs, embeddings & vector databases, RAG, LLM application development, fine-tuning, LLM agents & tool calling, evaluation & deployment, before ending with a 20-hour Enterprise LLM capstone. The modules combine theoretical concepts with hands-on exercises using practical tools, while the overall program includes projects, RAG applications and an enterprise capstone. Training takes place fully online for Hyderabad learners as well as students across India.

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

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

Upcoming LLM Engineering Course Batches for Hyderabad Learners

Pick a batch timing that fits comfortably into your daily schedule. All live online sessions follow IST timings. Learners can reserve a free demo class for a practical introduction or choose from upcoming weekday and weekend batches — offering flexible schedules and hands-on learning for students as well as 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 Hyderabad

LLM Engineering Course Syllabus in Hyderabad

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 Hyderabad

Learners who complete all 13 modules, finish the required assignments and successfully complete the Enterprise LLM capstone project are awarded the Uncodemy LLM Engineering Program Certificate. It records the program name, training duration, tools covered and date of completion. The credential is available for online verification at certificate.uncodemy.com and serves as formal documentation of successful completion of the Uncodemy LLM Engineering program.

This certificate is supported by the practical work undertaken during the program, including RAG application projects, fine-tuning exercises and the 20-hour Enterprise LLM capstone project. Training involves 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

Uncodemy Edutech Pvt. Ltd. operates Uncodemy as a career-oriented IT training institute. With more than 14 years of training experience, physical learning centres in Delhi and Noida, and live online programs accessible across India, Uncodemy conducts instructor-led training focused on emerging technology skills.

The LLM Engineering program enables learners to create RAG applications, perform model fine-tuning, develop LLM agents with tool calling and complete an enterprise-level LLM capstone. Learners study the production engineering of LLM applications, covering areas such as prompt design, retrieval pipelines, model adaptation and deployment. The full module-by-module curriculum is available for review before enrolment.

In addition to technical training, the program offers instructor-led classes, practical assignments, project-based learning, interview preparation and career support. Details regarding the scope of career assistance and its limitations are provided in the career support policy, along with the eligibility requirements shared before payment and enrolment.

Other courses for Hyderabad learners

If you are still deciding on a direction, Uncodemy also runs Generative AI , Data Science and Playwright Automation Testing courses for Hyderabad and Telangana 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 separates the responsibilities of trainers and domain reviewers, rather than placing both roles with the same person. Trainers handle the live instruction, while independent domain specialists who do not teach the batch review the curriculum to help maintain technical accuracy and current content. For this program, Mr. Irshad provides curriculum and technical content review, supported by an additional review from Mr. Upendra Kumar Tiwari. As a result, the trainer is not the only person involved in checking the technical content of the course.

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 Hyderabad Learners Today!

Join Uncodemy’s LLM Engineering program created for Hyderabad learners. Through live online instruction led by experienced trainers, you will gain practical knowledge of LLM APIs, RAG pipelines, fine-tuning and LLM agents, strengthened through hands-on projects and an enterprise LLM capstone. Begin developing your LLM engineering skills with structured training and career preparation.

LLM Engineer Jobs and Career Scope in Hyderabad+

Hyderabad stands as India's most prominent technology and startup centre, housing a dense concentration of product companies, global capability centres, AI-first startups, SaaS firms and fintech leaders. Organisations across HITEC City, Gachibowli, Madhapur, Kondapur, Kukatpally, Banjara Hills and Uppal 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 Hyderabad 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 Hyderabad — Role-wise+

Salaries in Hyderabad 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 Hyderabad+

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 Hyderabad specifically, LLM engineering demand is emerging in:
  • Product companies and global capability centres — HITEC City, Gachibowli and Madhapur, 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 Hyderabad+

Hyderabad 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; Hyderabad 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 Hyderabad-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 Hyderabad 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 Hyderabad 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 Hyderabad?▼

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 Hyderabad?▼

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