India's Most Current AI & Automation Program — 2025

Artificial Intelligence & Automation Build. Deploy. Automate. Get Hired.

INFONEXUS IT Institute's AI & Automation course covers the tools shaping the future right now — LangChain, Agentic AI, n8n, RAG pipelines, LLM fine-tuning, GPT APIs, and no-code automation — across three progressive levels designed to make you industry-ready.

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⚡ What You'll Master

The Complete
AI & Automation Stack

From prompt engineering fundamentals to deploying autonomous AI agents in production — INFONEXUS covers every layer of the modern AI ecosystem.

// core_skill_001
🧠

LangChain, LlamaIndex & RAG Pipelines

Build Retrieval-Augmented Generation systems that answer questions from your own documents. Index PDFs, databases, and APIs into vector stores (Pinecone, ChromaDB, Weaviate) and query them with LangChain chains and LlamaIndex agents.

LangChain 0.3LlamaIndexPineconeChromaDBRAG
// live_code
from langchain import
  ChatOpenAI, RAG
 
llm = ChatOpenAI(
  model="gpt-4o"
)
# Build RAG chain
chain = RAG.from_docs(
  docs, llm=llm
)
🤖

Agentic AI & Multi-Agent Systems

Design autonomous AI agents using AutoGen, CrewAI, and LangGraph that plan, use tools, and execute multi-step workflows without human intervention.

AutoGenCrewAILangGraph
⚙️

n8n, Make & Zapier Automation

Build powerful no-code/low-code automation workflows — connect 500+ apps, trigger AI actions from webhooks, automate emails, CRMs, and business processes.

n8nMakeZapier
🎯

Prompt Engineering Mastery

Advanced prompt techniques: chain-of-thought, few-shot, ReAct, self-consistency, Tree-of-Thoughts — extracting maximum performance from any LLM.

GPT-4oClaude 3.5Gemini
🏗️

RPA with UiPath & Power Automate

Automate repetitive desktop and web tasks using Robotic Process Automation — screen scraping, form filling, data extraction, ERP automation, and attended/unattended bot deployment for enterprise workflows.

UiPathPower AutomateBlue Prism
🔬

LLM Fine-Tuning & Local AI Deployment

Fine-tune open-source models (Llama 3, Mistral, Phi-3) using LoRA and QLoRA on your own datasets. Deploy local AI with Ollama — run GPT-quality models on-premises for privacy-critical enterprise use cases.

LoRAOllamaLlama 3Mistral
AI and automation training at INFONEXUS IT Institute Indore — LangChain RAG and Agentic AI course
6 Mo.Full Program
📋 Program Overview

From AI User to
AI Builder to AI Entrepreneur

The INFONEXUS AI & Automation program is structured as three progressive stages — each one unlocking a new tier of capability: from understanding AI tools, to building AI products, to deploying autonomous AI systems at scale.

GPT-4oClaude 3.5LangChainAutoGenCrewAIn8nUiPathPineconeOllamaFastAPI
📚 Course Curriculum

18 Modules.
3 Levels. Built for 2025.

Every module is benchmarked against real AI job descriptions from top tech companies and AI startups — covering tools and skills that employers actively hire for right now.

AI automation course INFONEXUS IT Institute — LangChain Agentic AI n8n training Indore

AI & Automation — Full Program

// 6 months · 3 levels · 18 modules · 48+ AI tools · real-world projects

🟢 basic_level — AI Tools Mastery & No-Code Automation
⏱ 6 Weeks
🤖 5 Real AI Projects
🎓 No Coding Required
📜 Foundation Certificate
01

AI Fundamentals & The Modern AI Landscape

  • Understanding AI, ML, and Generative AI — how LLMs like GPT-4o and Claude 3.5 work
  • The AI ecosystem in 2025: foundation models, fine-tuned models, open-source vs proprietary
  • Types of AI tools: content creation, code generation, image/video AI, voice AI, data analysis
  • AI governance & ethics: hallucinations, bias, data privacy, GDPR implications for AI tools
  • Identifying AI use cases: business process analysis, ROI calculation, automation opportunity mapping
  • Overview of current AI platforms: OpenAI, Anthropic, Google Gemini, Meta Llama, Mistral AI
02

Prompt Engineering — From Basics to Advanced Techniques

  • Zero-shot, one-shot, and few-shot prompting — when and why each technique works
  • Chain-of-thought (CoT) prompting: step-by-step reasoning for complex tasks
  • Role prompting, persona prompting, and system message design for GPT-4o and Claude
  • ReAct framework: combining reasoning and action in prompts for agent-like behavior
  • Tree-of-Thoughts (ToT) and self-consistency prompting for accurate complex outputs
  • Prompt templates and prompt libraries for business: marketing, HR, legal, technical writing
03

ChatGPT, Claude & Gemini — AI Power User Mastery

  • ChatGPT Advanced Data Analysis: uploading CSVs, generating charts, statistical insights
  • Custom GPTs: creating, configuring, and deploying custom GPT assistants on ChatGPT Plus
  • Claude 3.5 Sonnet: long-context documents, artifact creation, coding tasks, analysis
  • Google Gemini 1.5 Pro: 1M token context, multimodal (image+text+audio) workflows
  • Perplexity AI for research automation: sourced research reports, follow-up chains
  • AI productivity stack: building personal AI workflows with 10+ tools in a daily routine
04

Zapier, Make & n8n — No-Code Workflow Automation

  • Zapier fundamentals: triggers, actions, filters, formatters — building your first AI Zap
  • Make (formerly Integromat): visual workflow builder, iterators, aggregators, error handling
  • n8n open-source automation: self-hosted setup, nodes, expressions, AI agent nodes
  • Connecting AI to business: auto-email generation, CRM updates, Slack notifications with AI
  • AI content pipeline: new blog post brief → ChatGPT → Google Docs → email → social post
  • Project 1: Complete business automation — lead capture → AI qualification → CRM → follow-up
05

AI for Content, Marketing & Business Operations

  • AI content creation stack: Jasper, Copy.ai, Claude for long-form — workflow templates
  • AI image generation: Midjourney V6, DALL-E 3, Stable Diffusion for business graphics
  • AI video tools: Runway Gen-3, Sora, HeyGen avatars, Synthesia — creating video at scale
  • AI for SEO: Surfer SEO + ChatGPT pipeline, automated keyword research, content briefs
  • AI in sales automation: personalized outreach at scale, AI SDR tools, CRM intelligence
  • AI for customer support: chatbot setup with Tidio/Intercom + AI knowledge base integration
06

AI Voice, Transcription & Document Intelligence

  • Whisper AI: automatic speech recognition, multi-language transcription, speaker diarization
  • ElevenLabs & Murf: voice cloning, text-to-speech for content production and automation
  • Document AI with Adobe Acrobat AI + ChatGPT: extract, summarize, and query PDF documents
  • Microsoft Copilot in Excel, Word, PowerPoint — enterprise AI productivity workflows
  • AI meeting tools: Otter.ai, Fireflies, Fathom — automated notes, summaries, action items
  • Project 2: End-to-end document intelligence pipeline — upload → extract → summarize → notify

🟢 Basic Outcome: Students automate 5 real business workflows using no-code AI tools and build a complete AI-powered content and operations system — ready for AI Specialist, Automation Analyst, and Prompt Engineer roles.

🔵 advanced_level — Python AI, LangChain, RAG & API Development
⏱ 9 Weeks
🤖 4 AI Product Projects
🎓 Prerequisite: Basic Level
📜 Advanced Certificate
07

Python for AI — From Scripting to AI Applications

  • Python AI essentials: virtual environments, pip, Jupyter notebooks, Google Colab setup
  • NumPy, Pandas, Matplotlib — data manipulation and visualization for AI projects
  • OpenAI Python SDK: chat completions, function calling, streaming, embeddings API
  • Anthropic SDK: Messages API, Claude integration, multi-turn conversations with Python
  • API key management, rate limiting, retry logic, cost tracking for LLM API calls
  • Building a Python CLI chatbot with conversation history and token counting
08

LangChain — Chains, Agents & Memory Systems

  • LangChain 0.3 architecture: Runnables, LCEL (LangChain Expression Language), chains
  • Prompt templates: ChatPromptTemplate, StructuredOutputParser, Pydantic output parsing
  • Memory systems: ConversationBufferMemory, SummaryMemory, VectorStoreMemory
  • LangChain Tools: DuckDuckGoSearch, ArxivAPI, Wikipedia, custom tool creation
  • LangChain Agents: ReAct agent, OpenAI functions agent, structured chat agent
  • LangSmith: observability, tracing, evaluations, debugging LangChain applications
09

Vector Databases & RAG Pipeline Architecture

  • Embeddings deep-dive: text-embedding-3-small, Cohere embed, sentence-transformers
  • Pinecone: index creation, upsert, similarity search, metadata filtering for RAG
  • ChromaDB: local vector store, persistent storage, collection management
  • Weaviate: multi-tenancy, hybrid search (vector + BM25), schema management
  • RAG pipeline optimization: chunk sizing, overlap strategies, re-ranking with Cohere
  • Project 3: Custom knowledge base chatbot — RAG over company docs with source citations
10

LlamaIndex & Advanced RAG Techniques

  • LlamaIndex data connectors: PDF, CSV, Notion, Confluence, Google Drive, web scraping
  • Index types: VectorStoreIndex, SummaryIndex, KnowledgeGraphIndex — when to use each
  • Query engines: vector query, keyword query, hybrid retrieval, sub-question decomposition
  • Multi-document RAG: routing queries across multiple knowledge bases
  • Evaluation with RAGAS: faithfulness, answer relevancy, context recall metrics
  • Advanced RAG: HyDE, parent-child chunking, corrective RAG (CRAG), self-RAG patterns
11

FastAPI AI Backend — Building & Deploying AI APIs

  • FastAPI fundamentals: routes, request models (Pydantic), response models, middleware
  • Streaming LLM responses with FastAPI: SSE (Server-Sent Events) for real-time AI output
  • Background tasks, async endpoints, and database integration (PostgreSQL + SQLAlchemy)
  • Authentication: JWT with FastAPI, API key validation for AI endpoints
  • Docker containerization: Dockerfile for FastAPI + LangChain app, docker-compose
  • Deployment: Render, Railway, AWS Lambda, Modal — deploying AI APIs to production
12

RPA with UiPath — Enterprise Process Automation

  • UiPath Studio basics: recording activities, variables, data tables, flow control
  • UI automation: web scraping, form filling, application automation (SAP, ERP)
  • UiPath Document Understanding: invoice extraction, form processing, ML classification
  • Attended vs unattended bots: Orchestrator setup, scheduling, queue management
  • UiPath AI Integration: invoking OpenAI APIs within UiPath workflows for intelligent RPA
  • Project 4: Intelligent RPA bot — auto-extract invoices → validate → update ERP → email report

🔵 Advanced Outcome: Students build and deploy 4 AI products — a RAG chatbot, a knowledge base API, an AI automation pipeline, and an intelligent RPA bot — production-ready on cloud infrastructure.

🟣 professional_level — Agentic AI, LLM Fine-tuning & AI Product Launch
⏱ 9 Weeks
🤖 3 Capstone Projects
🎓 Prerequisite: Advanced Level
📜 Industry Certificate + LOR
13

Agentic AI — AutoGen, CrewAI & LangGraph

  • Agentic AI principles: planning, tool use, memory, reflection — the agent loop explained
  • Microsoft AutoGen: multi-agent conversations, code-executing agents, human proxy agents
  • CrewAI: role-based agents, tasks, tools, crews — building collaborative AI teams
  • LangGraph: stateful graph-based agent workflows, cycles, conditional edges, checkpointing
  • Agent tools: web search (Tavily, Serper), code execution, browser use, file system
  • Project 5: Autonomous research agent — searches web, reads papers, synthesizes reports
14

LLM Fine-Tuning with LoRA & QLoRA

  • Fine-tuning fundamentals: when to fine-tune vs RAG vs few-shot — decision framework
  • Dataset preparation: instruction-tuning format (Alpaca, ShareGPT), data curation tools
  • LoRA (Low-Rank Adaptation): rank, alpha, target modules — efficient fine-tuning theory
  • QLoRA on consumer GPUs: 4-bit quantization with bitsandbytes, Google Colab A100
  • Hugging Face Transformers + PEFT: training pipeline, evaluation, model merging
  • Deploying fine-tuned models: Hugging Face Hub, Ollama local, Modal serverless GPU
15

Local AI & Private Deployment with Ollama

  • Ollama setup: running Llama 3.1, Mistral 7B, Phi-3, Gemma 2 locally on CPU and GPU
  • Open WebUI: self-hosted ChatGPT-like interface for teams and enterprises
  • Building local RAG with Ollama + ChromaDB: fully offline, privacy-first AI system
  • LM Studio: GUI for local model management, API server mode for local integrations
  • Private AI deployment for enterprises: on-premise setup, access control, audit logging
  • Project 6: Private enterprise AI assistant — local RAG + auth + REST API + dashboard
16

AI Product Development & Prompt-to-Product

  • AI product ideation: identifying AI-solvable problems, TAM analysis, competitor mapping
  • Streamlit for AI apps: rapid prototyping, custom components, LangChain + Streamlit integration
  • Gradio: building shareable AI interfaces, Hugging Face Spaces deployment
  • Full-stack AI: Next.js + Vercel AI SDK for streaming chat interfaces, auth, payments
  • OpenAI Assistants API: thread management, file search, code interpreter, function calling
  • Monetizing AI products: SaaS pricing, API metering, freemium models, Stripe integration
17

AI Evaluation, Safety & Production Monitoring

  • LLM evaluation frameworks: RAGAS, TruLens, DeepEval — automated quality testing
  • A/B testing AI: prompt versioning, model comparison, latency vs quality trade-offs
  • AI safety: prompt injection attacks, jailbreak detection, content moderation with Llama Guard
  • Guardrails AI: NeMo Guardrails — validating LLM inputs and outputs programmatically
  • Production observability: LangSmith, Arize Phoenix, Helicone — cost, latency, quality
  • AI cost optimization: caching with Semantic Cache, model routing (small vs large LLM)
18

Capstone, Career Launch & AI Entrepreneurship

  • Capstone Project: full autonomous AI system — multi-agent + RAG + API + deployed product
  • AI portfolio building: GitHub, Hugging Face Spaces, Product Hunt launch strategy
  • Resume for AI roles: AI Engineer, ML Engineer, AI Product Manager, Automation Specialist
  • Freelancing with AI: Upwork AI niche, AI consulting packages, agency model (₹1–5L/month)
  • AI startup path: turning your AI project into a business, MVP, and funding strategy
  • INFONEXUS placement network: AI companies, tech MNCs, and AI startup connections

🟣 Professional Outcome: Students build and launch a complete autonomous AI system — agentic + RAG + fine-tuned + production-deployed — plus a career launch plan targeting AI Engineer, ML Engineer, and AI Entrepreneur paths.

💼 Career Outcomes

Roles You'll Land
After INFONEXUS AI

AI and Automation is the fastest-growing career category globally. INFONEXUS graduates are hired at tech companies, consulting firms, AI startups, and remote-first companies worldwide.

🤖
AI Engineer
₹8–20 LPA
🧠
ML Engineer
₹12–28 LPA
⚙️
Automation Analyst
₹6–14 LPA
🔬
AI Product Manager
₹15–35 LPA
🎯
Prompt Engineer
₹8–18 LPA
🚀
AI Entrepreneur
Unlimited
👩‍💻 Our Faculty

Trained by People
Actually Building with AI

Every INFONEXUS AI trainer is an active practitioner — shipping AI products, running AI automation businesses, or working at AI-first companies right now.

Arjun Mehta — Lead AI & LangChain Trainer INFONEXUS

Arjun Mehta

// Lead AI Engineer Trainer

Ex-OpenAI Partner · LangChain Expert · 10+ Yrs
⭐ Student Success

3500+ AI Practitioners.
All Building. All Earning.

Verified outcomes from INFONEXUS AI & Automation graduates working at AI companies, automation agencies, and running their own AI products.

★★★★★
"

The LangChain + RAG module at INFONEXUS is the most practical I've found anywhere. Within a week of the course, I built a custom chatbot for a real estate client that reads PDFs and answers questions. Client loved it, and I charged ₹80,000 for the project. The agentic AI module with CrewAI is next-level.

Vivek INFONEXUS alumni
Vivek Sharma
// AI Freelancer · Indore
₹50k/Month
★★★★★
"

I was a traditional software developer with no AI experience. After INFONEXUS Professional level, I completely pivoted my career. The AutoGen multi-agent module and the fine-tuning with LoRA sections were unlike anything I found online. Landed an AI Engineer role at a Bengaluru startup with remote work option.

Ananya INFONEXUS alumni
Ananya Krishnan
// AI Engineer · Bengaluru Startup
₹12 LPA
★★★★★
"

The n8n + AI automation module transformed my business. I run a digital marketing agency and now offer AI automation as a premium service — charging ₹30,000–₹1,50,000 per automation workflow setup. INFONEXUS taught me both the technical setup and how to sell it to enterprise clients. Game-changer.

Rahul INFONEXUS alumni
Rahul Joshi
// AI Automation Agency Owner
₹30k/Month
❓ FAQ

Questions About
the AI Course

Honest answers to everything students ask before joining INFONEXUS IT Institute's AI & Automation program.

No programming experience is required for the Basic level. The Basic curriculum covers no-code and low-code AI tools — ChatGPT, Claude, Zapier, Make, n8n, and AI productivity tools — that anyone can learn regardless of technical background. Python for AI is introduced in the Advanced level with full guidance from scratch. Business professionals, marketers, entrepreneurs, and complete beginners all successfully complete the program.
INFONEXUS covers the latest 2024–2025 AI stack: GPT-4o, Claude 3.5 Sonnet, Gemini 1.5 Pro, LangChain 0.3, LlamaIndex, ChromaDB, Pinecone, Weaviate, AutoGen, CrewAI, LangGraph, n8n, Make, Zapier, UiPath RPA, Ollama (Llama 3.1, Mistral, Phi-3), Hugging Face Transformers, LoRA/QLoRA fine-tuning, FastAPI, Docker, and AI deployment on AWS, Render, and Modal. Course content is updated monthly to keep pace with the AI landscape.
Agentic AI refers to AI systems that can autonomously plan, use tools, and execute multi-step tasks without human input at each step. INFONEXUS teaches AutoGen (Microsoft), CrewAI, and LangGraph — the leading frameworks for building AI agents in 2025. Agentic AI skills are among the most in-demand and highest-paying AI specializations, with companies paying ₹20–40 LPA for engineers who can build reliable production AI agent systems.
Absolutely. INFONEXUS alumni run successful AI freelancing businesses earning ₹1–5 lakhs per month. Common services include: RAG chatbot development (₹50,000–₹3,00,000 per project), n8n/Make automation workflows (₹20,000–₹1,50,000 per build), AI content automation pipelines (₹30,000–₹2,00,000), and AI consulting retainers. The Professional level's dedicated entrepreneurship module covers exactly how to find clients, price services, and scale an AI automation agency.
INFONEXUS offers both live online classes (Zoom) and offline classes at the Indore campus. All sessions are recorded with 12-month playback access. Multiple batch timings accommodate working professionals: weekday evening batches (7–9 PM) and weekend batches (10 AM–2 PM). Every student gets cloud compute access for GPU-intensive modules like LLM fine-tuning and gets hands-on API credits for OpenAI, Anthropic, and Pinecone to practice on real AI tools.
⚡ Next Batch Starting Soon — Seats Limited

Start Building with
AI Today.

Join 3500+ INFONEXUS AI practitioners building with LangChain, AutoGen, n8n, and production AI systems. Your free demo class costs zero.

✓ LangChain + RAG ✓ Agentic AI ✓ n8n Automation ✓ LLM Fine-tuning → No Coding Required to Start
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