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Read More →Visakhapatnam learners can now join Uncodemy's LLM Engineering program in a fully live online, instructor-led format spanning 5–6 months. The syllabus covers LLM APIs, embeddings & vector databases, RAG, fine-tuning, LLM agents & tool calling, and deployment. It's designed for developers, data scientists/ML engineers and aspiring AI engineers, with 13 modules, 100+ live sessions, 160+ hours and an enterprise LLM capstone. Fee: ₹17,500 + 18% GST, total ₹20,650. EMI from ₹4,032/month.
Learn from 8+ years experienced professionals
Build real LLM test suites, not just theory
Get lifetime access to recorded sessions & materials
Resume Building, Mock Interviews & Job Support
Certificate of Completion from Uncodemy
Weekday & Weekend Online & Offline
Learners who complete 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 candidates can pursue roles such as LLM Engineer, AI Engineer and RAG/AI Application Engineer. Placement records for Visakhapatnam learners are updated regularly — see verified outcomes at uncodemy.com/placement.
Placed at:Cognizant
LLM engineering is the practice of designing, building, fine-tuning and deploying applications powered by large language models. Unlike traditional software engineering, which relies on deterministic logic, or data science, which focuses on predictive modelling, LLM engineering works with probabilistic models, prompt design, retrieval pipelines and model adaptation. It sits at the intersection of software engineering, machine learning and product development, converting raw LLM capabilities into dependable, production-ready features.
What does an LLM engineer do? An LLM engineer handles LLM APIs and SDKs, creates RAG pipelines with embeddings and vector databases, fine-tunes models for domain-specific requirements, builds LLM agents with tool-calling abilities, assesses model outputs, and deploys LLM-driven applications. Their routine encompasses Python scripting, prompt engineering, retrieval assessment, API integration, and using frameworks like LangChain to connect models, data, and tools into a working application.
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.
Visakhapatnam learners can join this LLM Engineering program as a fully live online, instructor-led course spanning 5–6 months. It includes 100+ live sessions, 160+ hours of learning, and 13 structured modules covering Generative AI foundations, 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 a 20-hour Enterprise LLM capstone. Each module blends theory with hands-on exercises using real tools, and the program concludes with portfolio-ready projects, RAG applications and an enterprise-grade capstone. Delivery is completely online, serving Visakhapatnam and learners across India.
Who should join this course:
Eligibility: Programming fundamentals are helpful but optional — Python is taught from Module 2 onward. Comfort with basic ML/NLP concepts is a plus but developed in Module 3. A laptop with stable internet access is required for the practical sessions.
Choose a live online batch that fits your schedule — all batches follow IST timings. You can book a free demo class first to get a feel for the trainer and the curriculum. Then pick from the upcoming weekday or weekend batches, designed for working professionals and students, with flexible timings and a hands-on approach.
| 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 |
| 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.
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 | 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 | |
After completing all 13 modules, the assignments and the Enterprise LLM capstone project, learners receive the Uncodemy LLM Engineering Program Certificate. It records the program name, duration, tools covered and completion date. The certificate can be verified online at certificate.uncodemy.com and serves as an official record of successful completion of the Uncodemy LLM Engineering program.
The certificate reflects the practical work completed during the program — 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.
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_2.webp)
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LLM APIs & SDKs
LangChain
Vector Databases
Python
Hugging Face
Prompt Engineering
Fine-Tuning
Evaluation/Observability
Git & GitHub
Uncodemy, run by Uncodemy Edutech Pvt. Ltd., is a career-focused IT training institute with 14+ years of experience. It delivers instructor-led training through physical classroom centres in Delhi and Noida, and live online classes for learners across India, covering emerging technologies.
In this LLM Engineering program, participants construct RAG applications, fine-tune models, design LLM agents with tool calling, and complete an enterprise LLM capstone project. The course describes how LLM-powered applications are built in production — prompt design, retrieval pipelines, model adaptation and deployment. You can check the full module-by-module curriculum before you enrol.
Besides training, Uncodemy provides instructor-led sessions, practical assignments, project-based learning, interview preparation and career support. What this support includes — and what it does not — is clearly stated in our career support policy, along with the eligibility conditions published before enrolment rather than after payment.
If you are still deciding, Uncodemy also runs Generative AI , Data Science and Playwright Automation Testing courses for Visakhapatnam and Andhra Pradesh 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.
The people who actually teach this course
Uncodemy treats two roles separately that most institutes combine into one. Trainers conduct the live sessions. Domain reviewers — separate experts who don't teach the batch — verify that the curriculum is technically accurate and current. For this program, curriculum and technical content are reviewed by Mr. Irshad, with extra review by Mr. Upendra Kumar Tiwari. This means the person teaching a course is not the only person checking if its content is correct.
Every trainer and domain reviewer connected with Uncodemy is published by name, with their domain and background — you can look them up before you enrol rather than after.
Senior Data Science Trainer
Expertise15+ years of industry experience building production machine learning systems for retail, telecom and consulting teams.
Modelling security breaches in iOS apps, dormant customer prediction and factor analysis, last-mile delivery optimisation, and credit card fraud detection.
Data Analytics & AI Trainer
ExpertisePython · SQL · Machine Learning · Tableau · Artificial Intelligence · Deep Learning · Power BI · MLOps
8+ years across consulting and public-sector analytics, with deep hands-on work in AI and MLOps delivery.
Built an OCR model, a disease-prediction model, and a fraud-control model deployed across every Indian state under the Ministry of Health & Welfare.
Data Analytics & AI Trainer
ExpertiseExcel, SQL, Python, statistics, Power BI, Tableau and Generative AI
7+ years turning aviation and enterprise data into forecasting models, dashboards and AI assistants.
AI agent chat/voice bot, AI-driven data analysis, a sales-forecasting ML model, NPS data model evaluation, and a face-recognition model for biometrics.
Data Analytics Trainer
ExpertisePython · SQL · Excel · Power BI · Tableau · ML · DL · NLP · Time Series · IoT Devices · Prompt Engineering · Chatbots
5+ years in logistics and consumer-brand analytics, with a strong focus on time series, NLP and applied automation.
Speech-to-text using core NLP (T2S), talent acquisition research, and product launch & CMS work on keventers.com using Sparktech.
Data Analytics Trainer
ExpertiseAdvanced Excel · SQL · Power BI · Tableau · Python · Data Visualisation · Statistics
Trainer for the analytics and business intelligence track at Uncodemy, working with learners on Excel, SQL and BI tooling from first principles to interview-ready projects.
Guides classroom capstones on sales and customer dashboards, KPI reporting and end-to-end data cleaning workflows.
Data Analytics Trainer
Expertise
Data Analytics Trainer
Expertise
MD & CEO
ExpertiseFounder, MD & CEO of Uncodemy and GS Net Academy, with experience in education, technology leadership, research, mentorship and career development.
Leads strategic direction, academic initiatives, technology-driven education programs and mentorship across Uncodemy and GS Net Academy.
Data Analytics Trainer
Expertise
MD & CEO
ExpertiseFounder, MD & CEO of Uncodemy and GS Net Academy, with experience in education, technology leadership, research, mentorship and career development.
Leads strategic direction, academic initiatives, technology-driven education programs and mentorship across Uncodemy and GS Net Academy.
CEO & Founder
ExpertiseCEO & Founder of GvCloud Secure and Uncodemy with 14+ years of professional experience building scalable web, mobile and AI-driven solutions for clients across India, USA, UK, Canada, Australia and Singapore.
Leads technology strategy, scalable web and mobile solutions, AI-driven products and EdTech initiatives across Uncodemy and GvCloud Secure.
Kickstart your LLM engineering career with Uncodemy's course tailored for Visakhapatnam learners. Through live online instructor-led sessions, you'll gain practical expertise in LLM APIs, RAG pipelines, fine-tuning and LLM agents — supported by real projects and an enterprise LLM capstone. Structured training and career preparation, all in one program.
| 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 |
| 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 |
| Factor | This Program |
|---|---|
| Duration | 5–6 months |
| Learning hours | 160+ |
| Live sessions | 100+ |
| Tools | 15+ |
| Fine-tuning module | Dedicated 15-hour module |
| Capstone | 20-hour Enterprise LLM project |
| Career support | Dedicated Career & Placement Assistance |
| 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 |
The program runs for 5–6 months and includes 160+ hours of learning across 100+ live sessions. Weekday and weekend batches are both available.
No prior experience is needed. Python is introduced in Module 2 from the basics, and Module 3 covers foundational ML/NLP. You will need a laptop with a stable internet connection.
You'll learn 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.
Yes. Module 10 covers Fine-Tuning & Model Adaptation (15 hours) and Module 11 focuses on LLM Agents & Tool Calling (15 hours). Both are core, hands-on components.
The capstone is Module 13: Enterprise LLM Projects & Capstone (20 hours). You'll build a complete LLM-powered application integrating RAG, fine-tuning, agents and deployment.
All 100+ sessions are live, instructor-led classes. Recordings are provided after each session for revision.
The fee is ₹17,500 + 18% GST, which totals ₹20,650. This fee applies uniformly across all cities and delivery modes.
Yes, EMI starts at ₹4,032 per month. The exact amount, tenure and eligibility depend on the financing option you choose — a counsellor can confirm the details.
Yes, you can book a free demo class to experience the teaching style and review the syllabus. Contact us to schedule one.
We provide Dedicated Career & Placement Assistance: resume building, LinkedIn optimisation, portfolio review, interview preparation, mock interviews and opportunity sharing through our 850+ company network. Employment is not guaranteed.
Entry-level LLM Engineer roles typically offer ₹6–10 LPA (indicative). Real outcomes depend on your skills, experience, employer and market conditions. Uncodemy does not guarantee any specific salary or employment outcome.
Indicative market ranges: Entry-Level ₹6–10 LPA, Mid-Level ₹15–25 LPA, Senior ₹20–35 LPA, Lead ₹25–45 LPA. Offers vary by role, skills, experience, employer and market conditions. Uncodemy does not guarantee any specific salary.
You can target roles including LLM Engineer, AI Engineer, RAG/AI Application Engineer, Generative AI Engineer, ML Engineer (LLM-focused) and AI Solutions Architect (Junior).
The course suits developers wanting to specialise in LLM-powered applications, data scientists/ML engineers upskilling into LLM engineering, aspiring AI engineers, and working professionals moving into GenAI/LLM roles.
No. These figures come from Uncodemy's records and publicly available review platforms. Outcomes vary by learner, skills, experience, location, employer and market conditions. Career support is not a guarantee of employment or a specific salary.
The course is delivered live online across India, including for Visakhapatnam learners. Classroom training for other courses is available at our Delhi and Noida centres. Visakhapatnam learners typically join live online.
No. The certificate is issued independently by Uncodemy and 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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