SkillPlus Academy

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Python & Generative AI Engineering: From Basics to AI Agents

SkillPlus Academy is Surat's leading institute for AI & Python training, offering hands-on Generative AI Engineering, RAG Pipelines, and AI Agent development - available both offline in Surat and live online worldwide. Our industry-aligned curriculum covers real-world tools like LangGraph, Docker, and OpenAI/Gemini API integration, giving you the practical skills to build scalable AI solutions. With an included Internship and Placement support, we ensure you are job-ready for the future of tech - whether you are a Surat student, or joining online from Ahmedabad, Vadodara, or Rajkot.
Regular Offer
Start Learning Today
Limited seats per batch • Seats filling fast
Duration: 12 Weeks Mode: Live Online
Real Classroom Feel 1-on-1 Personal Guidance Projects & Assignments Industry + Job Ready
Local Students
₹24,999
NRI Students
$349

Master Python & Generative AI

SkillPlus Academy is Surat's most advanced Generative AI training institute, specializing in Python programming, RAG Pipelines, and AI Agent development with hands-on labs and live industrial projects. Our mentor-driven curriculum is optimized for 2026 tech standards, covering LangGraph workflows, Docker containerization, and Model Context Protocol (MCP) to prepare you for high-impact roles like AI Engineer and LLM Developer. Unlike generic coaching centers, our AI Engineering course in Surat focus exclusively on building production-ready intelligent systems-ensuring every module, from Pydantic to Vector Databases, is dedicated to making you a professional Python & AI Solutions expert.

Python, RAG & AI Agents Curriculum

Phase 1 · Modern Python & Engineering Foundations
Module 1
Advanced Python & Pydantic
Mastering Clean Code & Logic
Python FundamentalsMastering Lists, Dicts, Generators, and Asynchronous Programming (asyncio)
Pydantic & Data ValidationBuilding robust data models and handling Type Hints for AI pipelines
OOP for AIClasses, Objects, and Design Patterns for modular AI systems
Module 2
Engineering Essentials (Git & Docker)
Production-Ready Environments
Version ControlMastering Git workflows, Branching, and Collaborative coding on GitHub
DockerizationContainerizing AI apps for consistent deployment across cloud environments
Phase 2 · LLM Implementation & RAG Systems
Module 3
LLM Foundations & Prompt Engineering
Interacting with Foundation Models
LLM ArchitecturesUnderstanding Transformers, Attention mechanisms, and Tokenization
Advanced PromptingFew-shot, Chain-of-Thought, and System Prompts for OpenAI & Gemini
Local LLMs with OllamaRunning and integrating open-source models (Llama 3, Mistral) locally
Module 4
Retrieval-Augmented Generation (RAG)
Building Private Knowledge AI
Vector DatabasesUnderstanding Pinecone, ChromaDB, and Embedding models
Document ProcessingChunking strategies, Metadata filtering, and knowledge retrieval logic
ProjectDeveloping a "Talk to your PDF" Private AI System
Phase 3 · Agentic AI & MCP Protocol
Module 5
LangGraph & AI Agents
Stateful Multi-Agent Workflows
Autonomous AgentsBuilding loops and reasoning systems that can use external tools
LangGraph WorkflowsDeveloping state-managed graphs for complex, multi-step AI tasks
Module 6
Model Context Protocol (MCP) & Deployment
Connecting AI to Everything
MCP IntegrationBuilding MCP Servers to connect LLMs with Databases, APIs, and OS tools
Cloud DeploymentDeploying AI Agents on Cloud platforms for production scaling
Final CapstoneBuild and Present a Fully Autonomous AI Solution

AI Engineer Career Path 2026

Master the future of Tech - move from Python Developer to AI Solutions Architect with structured industry stages.

01
Entry · 0–2 Years

Python Developer / Associate AI Engineer

Starting Your AI Engineering Journey
Expected Salary*
₹5–9L
Glassdoor & Industry Data (2026)

Build robust applications using Python & Pydantic, manage environments with Docker, and integrate basic LLM APIs (OpenAI/Gemini) for automation tasks.

Python OOP Docker API Integration
02
Professional · 2–5 Years

Gen AI Engineer / LLM Specialist

Mastering RAG & Agentic Workflows
Expected Salary*
₹10–22L
LinkedIn & AmbitionBox (2026)

Develop advanced RAG pipelines, build stateful AI agents using LangGraph, and implement vector databases for long-term AI memory and knowledge retrieval.

LangGraph RAG Systems AI Agents
03
Expert · 5+ Years

AI Solutions Architect / Head of AI

Leading Enterprise AI Strategy
Expected Salary*
₹25–55L+
Industry Trends (2026)

Design scalable AI architectures, lead multi-modal AI projects, and implement Model Context Protocol (MCP) for enterprise-wide tool integration and AI governance.

MCP Protocol Enterprise AI AI Governance

*Salary ranges are indicative for AI Engineering roles as of 2026. Actual compensation depends on your technical expertise in LangGraph, RAG, and Cloud Deployment.

Python & Gen AI: FAQs

Prerequisites

No prior experience is needed. We start from Python fundamentals and gradually move to advanced Generative AI concepts like RAG Pipelines and AI Agents.

Curriculum

The course covers Advanced Python, Pydantic, Docker, LLM Prompt Engineering, RAG Systems, Vector Databases, LangGraph, AI Agents, and Model Context Protocol (MCP) for production deployment.

Mode

Yes. The course is available both offline at our Surat campus and live online for students from Ahmedabad, Vadodara, Rajkot, and anywhere worldwide.

Course Comparison

This course focuses on building LLM-powered applications, AI Agents, and RAG Pipelines. Data Science focuses on predictive modeling and machine learning algorithms. They are separate specializations that complement each other.

Tools

You will work with OpenAI and Gemini APIs, LangGraph, Docker, Pinecone, ChromaDB, Ollama for local LLMs, and Model Context Protocol (MCP) for enterprise AI integration.

Placement

We provide a mandatory Industry Internship, portfolio development, mock interviews, and alumni network connections to help you land roles like AI Engineer or LLM Developer.

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