RootAxis Technologies
Regional Hubs: Coimbatore (HQ) Chennai Madurai Salem Trichy Erode Tiruppur
Artificial Intelligence & Data Science 16 Weeks Intensive 8-Week Industry Internship

Generative AI Developer Course in Coimbatore

Build, evaluate and deploy robust LLM systems. Go beyond prompt writing to work with retrieval-augmented generation, tool-enabled workflows, model adaptation, inference, security and production operations. In-person lab stations at our Peelamedu HQ campus in Coimbatore with an 8-week corporate software internship.

Enquire About This Course
Production Repos on GitHub Coimbatore: In-Person Classroom & Workstation Labs (HQ Campus) Verified Certification
Tuition & Schedule
Transparent Pricing
₹40,000 All-Inclusive Tuition
Flexible Installments from ₹13,333/mo (0% Interest)
  • Duration 16 Weeks Intensive
  • Training Mode In-Person Classroom & Workstation Labs (HQ Campus)
  • Capstone Repos 3 Production Builds
  • Mentorship 1-on-1 Code Reviews
  • Internship 8-Week Corporate Work
Enquire & Reserve Batch Slot Chat with Program Advisor
Peelamedu Flagship Campus · Masakalipalayam Rd, Coimbatore
Alternative Pathway Looking for a different depth?

Explore Sibling Track: Generative AI Application Developer (12 Weeks)

AI Product Building & Full-Stack Next.js

View Generative AI Application Developer
Specialization Pathway

Artificial Intelligence & Data Science

RootAxis HQ Flagship Campus (Peelamedu, Coimbatore)

In-Person Classroom & Workstation Labs (HQ Campus)

Hands-on practical training at our sole physical campus in Peelamedu, Coimbatore with air-conditioned computer labs, high-speed developer workstations, in-person mentor code reviews, and daily lab support.

Located on Masakalipalayam Road, 2 minutes from Peelamedu Bus Stop, 5 minutes from CIT and PSG College of Technology, Coimbatore. Admissions Desk: +91 73581 10061
Program Architecture

Engineered for Production Standards

A rigorous curriculum designed around real git pull requests, live architecture reviews, and production-tested toolchains.

Curriculum Blueprint 2026 Production Standard
The Generative AI Developer course at RootAxis Technologies in Peelamedu, Coimbatore is an intensive 16-week deep engineering curriculum (240–320 guided and independent hours) designed for Python developers and software engineers who want to engineer reliable LLM and RAG services. Students go beyond basic prompting to master vector retrieval, RAG evaluation scorecards, tool-calling pipelines, model adaptation (LoRA/QLoRA), local model runners, and containerized FastAPI services. Learners in Coimbatore complete three assessed portfolio repositories and receive an 8-week supervised industry internship.
Lab-to-Lecture Ratio
70% Hands-On Coding / 30% Theory
8-Week Corporate Internship
Real sprint cycles, code reviews & live software deliverables
Coimbatore HQ Campus
In-Person Classroom & Workstation Labs (HQ Campus) · Located on Masakalipalayam Road, 2 minutes from Peelamedu Bus Stop, 5 minutes from CIT and PSG College of Technology, Coimbatore.
1-on-1 Mentorship Live Git Commits
Core Pillars

Key Learning Pillars

Three pillars engineered to bridge academic learning with production engineering teams.

01 // ARCHITECTURE Core Pillar

Advanced RAG & Evaluation

Build hybrid keyword+dense retrieval, reranking, contextual retrieval, and rigorous precision/faithfulness evaluation datasets.

02 // DEPLOYMENT Core Pillar

Model Adaptation & Local Inference

Master LoRA and QLoRA fine-tuning concepts using Hugging Face PEFT, local model runners, and quantization trade-offs.

03 // PORTFOLIO Core Pillar

Security, Tracing & Production Deployment

Implement prompt injection defenses, secret management, audit logs, cost telemetry, and containerized FastAPI services.

Measurable Competencies

What You Will Achieve

Demonstrated competencies validated through production code reviews and verified pull requests.

Explain trade-offs between prompting, RAG, and fine-tuning with empirical evaluation data.
Design and implement high-precision retrieval pipelines with hybrid search and reranking.
Build evaluated RAG systems with curated question sets, faithfulness metrics, and regression testing.
Implement controlled tool use, stateful workflows, bounded loops, and human-in-the-loop checkpoints.
Conduct PEFT (LoRA/QLoRA) model adaptation experiments and local inference latency benchmarking.
Deploy secure, containerized FastAPI services with Docker, health checks, and budget safeguards.
Phase-by-Phase Roadmap

Complete Course Syllabus

Every module is fully crawlable, structured, and calibrated to 2026 industry standards.

Build clean, typed Python services with production hygiene. Focuses on modules, typing, virtual environments, Git, HTTP, JSON, Pydantic, exceptions, and testing basics.

Modules & Core Topics Covered:
Python engineering foundations & clean module architecture Type hints, static analysis & Pydantic data modeling Virtual environments, dependency locks & Git workflows HTTP clients, REST protocols & JSON parsing Exception hierarchies & deterministic pytest basics Practical Output: Typed service calling model API with README and tests

Understand tokens, embeddings, transformer/attention mechanisms, context windows, inference parameters, and modern model families.

Modules & Core Topics Covered:
Tokens, subword tokenizers (BPE) & token limits Vector embeddings geometry & distance metrics Transformer architecture: multi-head self-attention & feed-forward layers Context windows, temperature, top-p & top-k generation parameters Model families: proprietary vs open weights (GPT-4o, Claude 3.5, Llama 3) Practical Output: Notebook comparing tokenization, embeddings & generation settings

Master provider SDKs, prompt templates, system instructions, few-shot examples, structured outputs, streaming, and cost budgeting.

Modules & Core Topics Covered:
OpenAI, Anthropic & Google provider SDK architectures Prompt templates, system instructions & developer roles Few-shot demonstration design & edge case handling Structured outputs with JSON schema enforcement Streaming response handling & token/cost budgeting calculators Practical Output: Reusable model gateway with config & structured response validation

Engineer robust production services with tool calling, schema validation, timeouts, retries, fallbacks, rate limits, and unit tests.

Modules & Core Topics Covered:
Function calling specifications & parameter validation Deterministic retry strategies & exponential backoff Fallback providers & graceful degradation patterns Rate limiting, concurrency semaphores & timeout controls Prompt versioning & deterministic unit testing with mock providers Practical Output: Tool-enabled service with safe input validation & failure handling

Build access-aware document pipelines. Covers document loading, PDF/HTML/text parsing, cleaning, metadata extraction, and chunk boundaries.

Modules & Core Topics Covered:
Document parsing: unstructured text, PDF extraction & HTML parsing Text cleaning, normalization & unicode handling Metadata extraction & structural document tagging Chunking strategies: fixed size, sliding window, semantic & sentence boundary Access-aware document pipelines with permission filtering Practical Output: Ingestion pipeline with traceable source metadata & repeatable tests

In-depth vector search and semantic indexing. Covers similarity metrics, embedding choices, vector indexing (HNSW, IVFFlat), metadata filters, and database integration.

Modules & Core Topics Covered:
Embedding model comparison: OpenAI, Voyage, BGE & open-weights Vector similarity metrics: Cosine, Euclidean & Dot Product Vector database architectures: PostgreSQL with pgvector, Qdrant, ChromaDB Index types: HNSW vs IVFFlat trade-offs in recall and latency Metadata filtering & hybrid query preparation Practical Output: Search service with a chunking/retrieval comparison report

Implement hybrid keyword+dense retrieval, cross-encoder reranking, query rewriting, contextual retrieval, citations, and source filtering.

Modules & Core Topics Covered:
Hybrid search: combining BM25 lexical search with dense vector embeddings Cross-encoder reranking using Cohere & open-source rerankers Query expansion, sub-query decomposition & hypothetical document embeddings (HyDE) Contextual retrieval & chunk enrichment techniques Source citations & evidence attribution verification Practical Output: Grounded knowledge assistant with citations & retrieval diagnostics

Measure retrieval and answer accuracy. Build curated question sets, calculate precision/recall, faithfulness, answer relevance, and regression tests.

Modules & Core Topics Covered:
Curating domain golden evaluation question-and-answer test sets Retrieval evaluation: Hit Rate, Mean Reciprocal Rank (MRR), Precision@K Generation evaluation: Faithfulness, Answer Relevance & Hallucination rate Evaluation frameworks: Ragas & TruLens implementation Automated regression testing in CI pipelines for prompt and chunk updates Practical Output: Evaluation dataset and repeatable scorecard with failure mode report

Compose modular pipelines, connectors, prompt/data flows, and state. Compare custom code implementations with orchestration frameworks.

Modules & Core Topics Covered:
Orchestration concepts: pipelines, connectors, prompt chains & state LangChain Expression Language (LCEL) & runnable primitives LlamaIndex query engines, routers & index abstractions Custom composable Python code vs heavy framework trade-offs Architectural boundary design for long-term maintainability Practical Output: Modular RAG pipeline with at least two source types & clean interfaces

Implement stateful steps, routing, memory, bounded execution loops, checkpoints, human approval gates, and failure recovery.

Modules & Core Topics Covered:
Stateful execution graphs & conditional routing logic Memory persistence & conversation thread serialization Bounded execution loops & recursion depth safeguards Checkpoints, state snapshotting & time-travel debugging Human-in-the-loop manual approval gates & tool permission limits Practical Output: Controlled workflow with logs, human approval step & failure tests

Process complex visual documents. Covers image and PDF understanding, OCR integration, structured extraction, and field validation.

Modules & Core Topics Covered:
Vision-language models: GPT-4o Vision, Claude 3.5 Sonnet & Gemini Flash OCR pipelines: Tesseract, AWS Textract & PyMuPDF integration Extracting structured key-value data from invoices, receipts & technical tables Bounding box verification & visual element grounding Schema validation & fallback correction for uncertain fields Practical Output: Document extraction API with validation report & sample error cases

Understand when to prompt, RAG, or fine-tune. Master dataset preparation, train/validation split, LoRA/QLoRA concepts, and hands-on PEFT.

Modules & Core Topics Covered:
Decision matrix: Prompting vs RAG vs Fine-Tuning trade-offs Instruction dataset curation, cleaning & formatting (Alpaca/ShareGPT format) Train/validation/test splits & data leakage prevention Parameter-Efficient Fine-Tuning (PEFT): LoRA and QLoRA mathematics & concepts Hands-on lab: fine-tuning a small open model with Hugging Face SFTTrainer Practical Output: Small adaptation experiment or documented fine-tuning feasibility study

Run models locally without cloud dependencies. Master local model runners, quantization concepts (GGUF, AWQ), throughput, and memory trade-offs.

Modules & Core Topics Covered:
Local model runners: Ollama, vLLM, llama.cpp & Hugging Face TGI Quantization principles: FP16 vs INT8 vs INT4 (GGUF, AWQ, EXL2) Hardware requirements: GPU VRAM, CPU memory bandwidth & compute utilization Batching strategies, KV cache optimization & concurrency throughput Benchmarking hosted cloud APIs against local self-hosted inference Practical Output: Benchmark report comparing hosted model with local inference option

Defend against prompt injections and data leaks. Master access control, secret management, audit logs, tracing, and guardrails.

Modules & Core Topics Covered:
Direct & indirect prompt injection threat modeling PII detection, redaction & sensitive enterprise data handling Secret management, API key rotation & role-based access control LLM observability: trace dashboards, OpenTelemetry & LangSmith logging Guardrails implementations: NeMo Guardrails & Llama Guard Practical Output: Threat model, abuse test suite, trace dashboard & budget safeguards

Ship containerized LLM microservices to cloud environments. Master FastAPI design, Docker containerization, CI checks, and caching.

Modules & Core Topics Covered:
Production FastAPI design patterns: async endpoints & dependency injection Docker containerization: multi-stage builds, slim Python bases & GPU drivers Continuous Integration checks & automated testing workflows Semantic caching with Redis to reduce duplicate API latency and cost Asynchronous task workers (Celery/ARQ) for heavy document jobs Practical Output: Containerized service deployed to test environment with health checks

Final review and technical interview preparation. Covers architecture hardening, test coverage, evaluation evidence, and portfolio defense.

Modules & Core Topics Covered:
Comprehensive architectural review & threat analysis End-to-end integration test coverage verification Compiling evaluation evidence and benchmark scorecards Production documentation, architecture diagrams & OpenAPI specs Technical interview practice: explaining system trade-offs & live demo defense Practical Output: Final production repository, deployed demo, system diagram & presentation
Portfolio Engineering

Production Capstone Projects

Every project is built directly on GitHub with branch protections, automated testing, and live cloud deployment.

rootaxis-labs / model-gateway-evaluation-lab Public Staging

Model Gateway & Evaluation Lab

Production provider abstraction layer with structured JSON validation, automatic retries, fallbacks, latency benchmarking, and token budget analytics.

Python 3.12 FastAPI Pydantic pytest Redis Docker
rootaxis-labs / enterprise-rag-knowledge-service Public Staging

Enterprise RAG Knowledge Service

High-precision hybrid retrieval engine supporting PDF ingestion, pgvector vector search, Cohere reranking, source citations, and automated Ragas evaluation.

FastAPI PostgreSQL pgvector LangChain Ragas Docker
rootaxis-labs / specialization-capstone-document-intelligence-model-adaptation Public Staging

Specialization Capstone: Document Intelligence & Model Adaptation

Comprehensive enterprise application integrating multimodal document intelligence, PEFT fine-tuning evaluation, local inference serving, and observability tracing.

PyTorch Hugging Face PEFT Ollama FastAPI Qdrant Docker
Industry Toolchain

Tools & Frameworks Mastered

Master the standard developer toolchain requested by hiring engineering teams.

Python 3.12 FastAPI Pydantic pytest PostgreSQL pgvector Qdrant Hugging Face PEFT Docker Ollama vLLM
Learner Eligibility

Who Should Join & Prerequisites

Clear entry criteria designed for student success and job-market outcomes.

Target Audience Profile

Best for Python developers, backend engineers, AI/ML learners, and technically strong graduates in Coimbatore and Tamil Nadu who want to build, evaluate, and operate production-grade LLM infrastructure.

  • College students & fresh graduates seeking job-readiness
  • Working professionals upskilling into modern tech stacks
  • Final-year students preparing for placement seasons

Technical Prerequisites

Basic familiarity with computer operations and any programming language is helpful but not mandatory. We start with foundational programming logic and progressively transition into advanced system architecture.

Non-CS / Beginner Friendly: We offer 2 weeks of preparatory bridge modules covering programming basics, Git workflows, and command line tools for non-IT learners.
Transparent Terms

Tuition Investment & Batch Schedules

Clear educational investment with zero hidden admission fees, fine print, or surprises.

All-Inclusive Tuition
₹40,000 Total Program Fee

Covers all hands-on modules, live cloud sandbox access, mentorship, code reviews, and the 8-week corporate internship certificate.

  • Flexible installment splits (2 to 3 monthly payments)
  • Zero-cost EMI plans from ₹13,333 / month
  • No registration charges, hidden taxes, or exam fees
Check Eligibility & Reserve Slot

Cohort Batch Timings & Frequency

Cohorts start on the first and third Monday of each month. Choose the schedule that fits your routine:

Weekday Regular (Morning Batch)
Monday to Friday · Hands-on classroom lab & project sprints
9:30 AM – 1:30 PM
Weekday Evening (Working Professionals)
Monday to Thursday · Ideal for developers and college finalists
6:00 PM – 8:30 PM
Weekend Intensive Masterclass
Saturday & Sunday · Deep-dive project workshops & code reviews
10:00 AM – 4:30 PM
Campus: First Floor, Masakalipalayam Rd, Peelamedu, Coimbatore | Hybrid live stream available
Engineering Mentorship

Mentorship the Way Engineering Teams Work

No generic recorded videos or unmonitored lectures. You learn alongside experienced software engineers.

1-on-1 Code Reviews

Mentors review every Git commit and Pull Request, teaching clean code, modular architecture, and edge-case handling.

Live Lab Assistance

In-person lab stations and interactive remote screenshare debugging so you never remain stuck on technical errors.

Weekly Sprint Standups

Experience real agile sprint cycles, standups, and retrospective meetings mimicking modern software teams.

Corporate Internship

Official 8-week corporate software development experience certificate verifying production repo commits.

Market Alignment

Target Roles & Career Support

Aligned with current hiring requirements across modern software and AI companies.

₹6.5 - ₹13.0 LPA
Industry Salary Range
₹22.0 LPA
Mock Interview Rounds
High
Hiring Demand
Qualified Career Roles:
GenAI Engineer LLM Systems Architect RAG Engineer AI Backend Engineer AI Infrastructure Engineer
Dedicated Placement & Career Services

RootAxis Technologies maintains relationships with 50+ software and IT hiring partners across Coimbatore, Chennai, and Bangalore. We provide end-to-end career enablement to ensure you succeed in technical interviews:

Resume & Portfolio Engineering: Transform your GitHub profile and CV to highlight tangible production repositories and metrics.
Technical Mock Interviews: Rigorous 1-on-1 coding challenges and architectural system design drills with senior tech leads.
Direct Hiring Partner Referrals: Fast-track interview scheduling directly with tech firms hiring for full stack and AI talent.
Corporate Internship Letter: Official verified credential attesting to your 8-week production repository contributions.
SUPPORT CENTER

Frequently Asked Questions

Direct answers regarding curriculum, batch timings, hands-on lab projects, and placement assistance in Coimbatore.

Need help choosing a course?
Free 1-on-1 counseling available Mon–Sat
Talk to a Career Counselor
The total fee is ₹40,000 all-inclusive at RootAxis Peelamedu, Coimbatore. We offer flexible zero-cost installment options starting from ₹13,333 per month (3 installments). The fee covers all 16 weeks of guided engineering labs, API tokens, compute resources, code reviews, and the 8-week corporate software development internship.
The GenAI Developer track (16 weeks) is a Python-first, deep systems engineering program focusing on LLM architecture, vector retrieval, RAG evaluation metrics, PEFT fine-tuning, local inference, and production backend operations. The GenAI Application Developer track (12 weeks) is a product-first course focusing on building full-stack web applications with React 19/Next.js, FastAPI, and business workflow integrations.
Learners should know Python fundamentals, Git, basic SQL, and HTTP/REST protocols. RootAxis provides an explicit 2-3 week coding bridge for candidates who need to strengthen their Python and API foundations before diving into LLM engineering.
No. RootAxis provides lab compute access and cloud API keys for all student exercises. Fine-tuning and local inference modules are conducted as structured, bounded labs on our dedicated workstations and managed cloud sandbox instances.
Explore Specialized Tracks

Related Industrial Tracks

Full Stack & AI Development
Cybersecurity & Ethical Hacking
Artificial Intelligence & Data Science
Cloud Computing
Mobile App Development
UI/UX Design
Digital Marketing
Frontend Internship
Admissions Open 2026

Ready to Master
Generative AI Developer?

Connect directly with our engineering program advisors to discuss your background, batch schedules, and flexible payment options.

  • Dedicated Placement Assistance with 50+ Partners
  • 8-Week Industry Internship Certificate
  • 1-on-1 Code Reviews on GitHub
  • Peelamedu Classroom Lab & Live Hybrid
+91 73581 10061
info@rootaxis.in

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Generative AI Developer
₹40,000 All-Inclusive
Generative AI Developer
₹40,000
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