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🔥 Most Popular in Thiruvananthapuram

LLM Engineering Training Course in Thiruvananthapuram by Uncodemy

Thiruvananthapuram learners can enrol in Uncodemy's instructor-led LLM Engineering program, delivered fully live online over 5–6 months. The syllabus walks through LLM APIs, embeddings & vector databases, RAG, fine-tuning, LLM agents & tool calling, and deployment. It is designed for developers, data scientists/ML engineers and aspiring AI engineers, and includes 13 modules, 100+ live sessions, 160+ hours and an enterprise LLM capstone. Course fee: ₹17,500 + 18% GST, total ₹20,650. EMI starting at ₹4,032/month.

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Starting ₹4,032/M*
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Expert Trainers

Learn from 8+ years experienced professionals

Hands-on Automation Projects

Build real LLM test suites, not just theory

Lifetime Access

Get lifetime access to recorded sessions & materials

Dedicated Career & Placement Assistance

Resume Building, Mock Interviews & Job Support

Certified Course

Certificate of Completion from Uncodemy

Flexible Batches

Weekday & Weekend Online & Offline

Why Choose
Uncodemy?

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

Program Details

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

LLM Engineering Course in Thiruvananthapuram — 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; Thiruvananthapuram 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 the Uncodemy LLM Engineering program build practical, applied expertise in LLM APIs, RAG pipelines, fine-tuning, vector databases and LLM agents. After training and career preparation, eligible learners can apply for roles such as LLM Engineer, AI Engineer and RAG/AI Application Engineer. Placement records for Thiruvananthapuram learners are refreshed regularly — check verified outcomes at uncodemy.com/placement.

What is LLM Engineering?

LLM engineering involves designing, building, fine-tuning and deploying applications that leverage large language models. Where traditional software engineering depends on deterministic logic and data science focuses on predictive modelling, LLM engineering deals with probabilistic models, prompt design, retrieval pipelines and model adaptation. It sits at the crossroads of software engineering, machine learning and product development, turning raw LLM capabilities into dependable, production-ready features.

What does an LLM engineer do? By working with LLM APIs and SDKs, an LLM engineer develops RAG pipelines that use embeddings and vector databases, fine-tunes models to meet domain-specific demands, designs LLM agents that support tool calling, evaluates model outputs, and deploys LLM-powered applications. Their everyday work includes Python scripting, prompt engineering, retrieval evaluation, API integration, and using frameworks such as LangChain to join models, data, and tools into a functioning app.

LLM Engineering vs Generative AI vs Data Science

LLM Engineering focuses on building, fine-tuning and deploying LLM-powered applications, while Generative AI & Agentic AI emphasises autonomous agents and Data Science focuses on predictive modelling.

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

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

Course Overview

Delivered entirely live online, this LLM Engineering program spans 5–6 months and packs 100+ live sessions with 160+ hours of learning. The 13 modules move step-by-step from Generative AI foundations into Python for LLM engineering, ML & NLP fundamentals, transformer architecture, prompt engineering, LLM APIs & SDKs, embeddings & vector databases, RAG, LLM application development, fine-tuning, LLM agents & tool calling, evaluation & deployment, and finally a 20-hour Enterprise LLM capstone. Theory in each module is paired with hands-on exercises using real tools, and the program finishes with practical projects, RAG applications and an enterprise capstone. The format is fully online, serving Thiruvananthapuram and learners across India.

Who should join this course:

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

Eligibility: Familiarity with programming basics is helpful but not required — Python is taught from Module 2 onward. Comfort with basic ML/NLP concepts is a bonus but built in Module 3. A laptop with stable internet is required for practicals.

Upcoming LLM Engineering Course Batches for Thiruvananthapuram Learners

Choose a live online batch timing that suits your routine — all sessions run on IST. You can start with a free demo class for a first-hand look, then pick from the upcoming weekday or weekend batches. The schedule is built for working professionals and students, with flexible timings and practice-first learning.

Weekdays

Date Time Trainer Seats Left
16oct 07:30 PM – 08:30 PM Mr. Irshad 01Seat
22oct 02:00 PM – 03:00 PM Mr. Upendra Kumar Tiwari 02Seats
26oct 10:30 AM – 11:30 AM Mr. Irshad 01Seat
30oct 12:00 PM – 01:00 PM Mr. Upendra Kumar Tiwari 02Seats

Weekends

Date Time Trainer Seats Left
27oct 03:00 PM – 05:00 PM Mr. Irshad 02Seats

8+ new batches start every month. All timings are in IST. Seats are limited and updated daily.

Enroll Now

Curriculum for LLM Engineering Training Course in Thiruvananthapuram

LLM Engineering Course Syllabus in Thiruvananthapuram

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 Thiruvananthapuram

Once you complete all 13 modules, the assignments and the Enterprise LLM capstone project, you receive the Uncodemy LLM Engineering Program Certificate. The certificate carries the program name, duration, tools covered and completion date. It is verifiable online at certificate.uncodemy.com and acts as a formal record of successful completion of the Uncodemy LLM Engineering program.

The certificate is tied to the practical work completed during the program — including hands-on RAG applications, fine-tuning exercises and the 20-hour Enterprise LLM capstone project. Learners work with LLM APIs & SDKs (OpenAI/Gemini/Claude-style), LangChain, Vector Databases (FAISS/Chroma/Pinecone), Python, Hugging Face Transformers, prompt engineering tools, fine-tuning frameworks and evaluation/observability tools.

Key Benefits of Our LLM Engineering Certification:

  • Program Completion :Provides a record of successful completion of the LLM Engineering program.
  • Online Verification :Certificate is verifiable online at certificate.uncodemy.com.
  • Practical Learning :Training includes hands-on RAG applications, fine-tuning work and an enterprise capstone.

This is an independent Uncodemy certificate. It is not affiliated with, endorsed by, or a credential of OpenAI, Google, Anthropic or any other LLM/vendor provider whose APIs are taught in this course. Certificate verification process pending confirmation.

Uncodemy Certificate Verification Online Certificate Verification & Download certificate.uncodemy.com
IIBA Endorsed Education Provider certificate — Uncodemy
Uncodemy LLM Engineering Program Certificate
Uncodemy MSME registration certificate

Tools and Technologies Covered

Apply Now

Introducing Uncodemy

Uncodemy, run by Uncodemy Edutech Pvt. Ltd., is a career-oriented IT training institute. It brings 14+ years of training excellence, physical classroom centres in Delhi and Noida, and live online classes that reach learners throughout India — delivering instructor-led training across emerging technologies.

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

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

Other courses for Thiruvananthapuram learners

If you are still weighing your options, Uncodemy also runs Generative AI , Data Science and Playwright Automation Testing courses for Thiruvananthapuram and Kerala 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 two roles that most institutes merge together. Trainers lead the live sessions. Domain reviewers — independent specialists who don't teach the batch — confirm the curriculum is technically accurate and current. For this program, curriculum and technical content are reviewed by Mr. Irshad, with further review by Mr. Upendra Kumar Tiwari. This means the person teaching a course is not the only person checking whether its content is correct.

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

Enroll in Our LLM Engineering Training for Thiruvananthapuram Learners Today!

Start your LLM engineering journey with Uncodemy's course designed for Thiruvananthapuram learners. Instructor-led live online sessions help you build real skills in LLM APIs, RAG pipelines, fine-tuning and LLM agents — supported by practical projects and an enterprise LLM capstone. Structured training and career preparation, all from one program.

LLM Engineer Jobs and Career Scope in Thiruvananthapuram+

Thiruvananthapuram has steadily grown into a technology and research hub, anchored by Technopark — one of India's largest IT parks — and a strong base of government IT bodies, space-tech institutes, deep-tech startups and product companies. Organisations in Kazhakkoottam, Pallipuram, Vazhuthacaud, Pattom, Kowdiar and Sasthamangalam are adding LLM-powered features such as support chatbots, RAG-based knowledge assistants, document-processing flows and agentic workflows, creating demand for engineers who can work with LLM APIs, retrieval pipelines, fine-tuning trade-offs and deployment. Government-tech, space-tech, healthcare, edtech, BFSI and e-commerce sectors in Thiruvananthapuram are also adopting GenAI, and they need engineers who can ship reliable LLM applications rather than demo prototypes. Interviews in the city often weight system design for LLM applications, RAG pipeline design and debugging, and fine-tuning trade-offs most heavily. 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 Thiruvananthapuram — Role-wise+

Salaries in Thiruvananthapuram 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 Thiruvananthapuram+

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 Thiruvananthapuram specifically, LLM engineering demand is emerging in:
  • IT services and global capability centres — Technopark, Kazhakkoottam and Pallipuram, integrating LLMs into enterprise applications
  • Product companies and SaaS startups — building chatbots, AI assistants and RAG-based features
  • Government-tech and public-sector IT bodies — LLM-driven document processing, citizen support and knowledge systems
  • Space-tech and deep-tech research — LLMs for research assistance, documentation and knowledge retrieval
  • Healthcare, edtech, BFSI and e-commerce — LLMs for personalization, content and customer service
Each of these sectors tends to weight skills slightly differently, so as you get closer to placement, it helps to tailor your capstone project toward the one or two sectors you're most interested in.

How to Become an LLM Engineer — Step by Step+

Becoming an LLM engineer is a step-by-step skill build, not a single course, and skipping steps usually shows up later as gaps in interviews or on the job.
  • Python fundamentals— syntax, data structures, APIs and environment management.
  • ML/NLP basics— supervised learning, text preprocessing, embeddings.
  • Transformer architecture— attention, positional encoding, pre-training vs fine-tuning.
  • Prompt engineering— design patterns, structured outputs, evaluation.
  • LLM APIs & embeddings— API integration, streaming, vector databases.
  • RAG & application development— retrieval pipelines, LangChain, chat interfaces.
  • Fine-tuning, agents & deployment— LoRA, tool calling, evaluation and production deployment.
Typical timeline: 5–6 months of consistent study to reach interview-ready standard, assuming focused hours most days rather than occasional binge sessions.

How This Course Compares to Other AI Courses in Thiruvananthapuram+

Thiruvananthapuram 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; Thiruvananthapuram learners typically join live online. Live online delivers the same instructor-led experience without any commute, and all sessions are recorded for revision. Offline works well for learners near Delhi or Noida who prefer in-person interaction. Hybrid is not currently offered for this program. For Thiruvananthapuram-based working professionals, live online is usually the most practical route — real-time doubt clearing, hands-on labs and lifetime access to recordings, without travelling.

Is this course right for you?+

If you want... Recommend
Full LLM Engineering career transition This program
Quick prompt-engineering upskilling only Consider AI Testing or GenAI course
Already strong in traditional ML, want to specialise in LLMs This program
Building AI agents specifically Consider Generative AI & Agentic AI course

Frequently Asked Questions

1. How long is the LLM Engineering course in Thiruvananthapuram?▼

It's a 5–6 month program with 160+ hours delivered across 100+ live sessions. Weekday and weekend batch options are both open.

2. Is prior Python or ML experience necessary?▼

Not mandatory. Module 2 starts Python from the fundamentals, so beginners can follow along; basic ML/NLP concepts come in Module 3. You'll need a laptop and stable internet connection.

3. Which tools are taught in this course?▼

15+ tools across the program — 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. Are fine-tuning and LLM agents part of the syllabus?▼

Yes — Module 10 is Fine-Tuning & Model Adaptation (15 hours) and Module 11 is LLM Agents & Tool Calling (15 hours). Both are hands-on and central to the program.

5. What does the capstone project involve?▼

Module 13 (Enterprise LLM Projects & Capstone, 20 hours) is where you build a full LLM-powered application — combining RAG, fine-tuning, agents and deployment in one integrated project.

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

All 100+ sessions are live and instructor-led. Session recordings are shared after each class so you can revisit anything at your own pace.

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

The course fee is ₹17,500 + 18% GST, which comes to ₹20,650 in total. This pricing is the same in every city and for every delivery mode.

8. Are EMI plans available?▼

Yes, EMI begins at ₹4,032 per month. Actual amount, tenure and eligibility depend on the financing partner you choose — a counsellor can walk you through the exact options.

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

Yes — a demo class is a good way to get a feel for the trainer, the pace and the curriculum before committing. Get in touch with our team to schedule yours.

10. Do you offer placement assistance?▼

We do. Our Dedicated Career & Placement Assistance covers resume building, LinkedIn optimisation, portfolio review, interview preparation, mock interviews and sharing openings from our 850+ company network. To be clear, we do not guarantee employment.

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

Entry-level LLM Engineer roles usually sit in the ₹6–10 LPA band (indicative market range). What you actually get depends on your skills, prior experience, employer and market conditions. Uncodemy does not promise a specific salary or job.

12. What is the salary of an LLM Engineer in Thiruvananthapuram?▼

Indicative ranges: Entry-Level ₹6–10 LPA, Mid-Level ₹15–25 LPA, Senior ₹20–35 LPA, 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 target after this 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 eligible for this LLM Engineering course?▼

Developers wanting 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 placement records and publicly available review platforms. 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.

16. Is classroom training available in Thiruvananthapuram?▼

This course is delivered live online across India, including for Thiruvananthapuram. Our classroom centres in Delhi and Noida host other courses. Thiruvananthapuram learners typically join live online.

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

No. This is an independent Uncodemy certificate — it is not affiliated with, endorsed by, or a credential of OpenAI, Google, Anthropic or any other LLM/vendor whose APIs are covered in this course.

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