AI Course in Bangalore
with Real-World Projects
📍 Training Center Located
Location 1: JP Nagar, Bangalore
Location 2: BTM Layout, Bangalore
Location 3: Koramangala, Bangalore
Launch your AI career with job-focused training built around real industry expectations.
Work on hands-on projects and gain the practical skills needed to become job-ready
Entry Level AI
Start your AI journey with confidence. Learn the fundamentals of Artificial Intelligence, Generative AI, prompt engineering, and practical AI tools to improve productivity and everyday work
AI Engineering Courses
Move beyond AI usage to AI implementation. Learn how AI models work, integrate AI through APIs, understand embeddings, and build simple AI-powered solutions using modern tools and techniques.
Advance level Ai
Master enterprise-grade AI development and deployment. Gain expertise in Production RAG, Agentic AI solutions, multi-tenant architectures, system deployment, scalability, security, and real-world AI implementation..
Entry level AI course
Course Name: Entry level AI
Duration: 2 Months
Mode: Online / Offline / Hybrid
Class Schedule: Weekend Batches/ Evening Classes everyday
Target Audience: Business Owners, Managers, Entrepreneurs
Prerequisites: No Technical Background Required
Certification: Yes
Projects: 1 Real-World Business AI Use Cases
Language: English
Location: Bangalore / Online
Class Method: Live Instructor-Led Sessions + Hands-on Workshops
Course outcome
LLM Foundations : Gain a strong understanding of Large Language Models (LLMs), how they work, their capabilities, limitations, and the role they play in modern AI applications.
Prompt Engineering :Learn how to design effective prompts that generate accurate, relevant, and high-quality outputs from AI models for various business and development use cases.
LLM API Integration :Understand how to connect and interact with AI models through APIs, enabling seamless integration of AI capabilities into web, mobile, and enterprise applications.
Basic RAG (Retrieval-Augmented Generation) :Explore the fundamentals of RAG, a technique that enhances AI responses by retrieving relevant information from external knowledge sources, improving accuracy and context.
Intro to AI Backend Development :Learn the core concepts of building AI-powered backend systems, including managing AI workflows, handling data, and deploying scalable AI applications.
What Sucess Looks like : 1) Build Final Year AI Projects , 2) Applied AI Developer
AI Engineering Courses
Course Name: AI Engineering Courses
Duration: 4 months
Mode: Online / Offline / Hybrid
Class Schedule: Weekend Batches/ Evening Classes everyday
Target Audience: Business Owners, Managers, Entrepreneurs
Prerequisites: No Technical Background Required
Certification: Yes
Projects:1 Real-World Business AI Project
Language: English
Location: Bangalore / Online
Class Method: Live Instructor-Led Sessions + Hands-on Workshops
Course outcome
All the features of the entry level AI+
Embeddings and Basic RAG :Explore how embeddings transform data into meaningful vector representations and learn the fundamentals of Retrieval-Augmented Generation (RAG) for building context-aware AI solutions.
Intro to AI Backbend Dev: Understand the core principles of AI backend development, including managing AI services, data pipelines, application logic, and deployment workflows for scalable AI systems.
What Success Looks like : 1) AI engineer , 2) Applied AI Developer
Advanced AI System Design Courses
Course Name: Advanced AI System Design Courses
Duration: 5 Months
Mode: Online / Offline / Hybrid
Class Schedule: Weekend Batches/ Evening Classes everyday
Target Audience: Business Owners, Managers, Entrepreneurs
Prerequisites: Technical Background Required
Certification: Yes
Projects: 1 Real-World Business Advance AI Project
Language: English
Location: Bangalore / Online
Class Method: Live Instructor-Led Sessions + Hands-on Workshops
Course outcome
Production Grade RAG :Learn how to design and implement enterprise-ready Retrieval-Augmented Generation (RAG) systems that deliver accurate, scalable, and reliable AI-powered knowledge retrieval and response generation.
Agentic Solutions:Explore the development of AI agents capable of reasoning, planning, decision-making, and executing multi-step tasks autonomously to solve complex business problems.
Multi-Tenant Basics: Understand the fundamentals of multi-tenant architecture, enabling AI applications to securely serve multiple users, teams, or organizations from a single platform.
Systems Deployment: Gain practical knowledge of deploying AI applications into production environments, including infrastructure setup, scalability, monitoring, security, and performance optimisation
What Sucess Looks like : 1) AI engineer , 2) Applied AI Developer 3)Agentic Systems Specialist 4) RAG Developer
Solutions
Transforming enterprises with next-gen IT services.
Consulting
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