Agentic AI Course Bangalore
Learn to build AI agents and agentic workflows using LLMs, tool calling, LangGraph, CrewAI, MCP, RAG and production-ready AI workflow patterns with Technovids from Bengaluru.
Agentic AI Course Bangalore — Quick Facts
| Item | Details |
|---|---|
| Course | Agentic AI Course Bangalore — AI agents and agentic workflows |
| Location served | Bangalore (Bengaluru), Karnataka, India |
| Office support | HSR Layout, Bengaluru — counselling and consultation |
| Delivery mode | Live online instructor-led · Blended learning |
| Best suited for | Developers, Python learners, AI engineers, data scientists, technical managers, corporate AI teams |
| Key topics | AI agents, agentic workflows, LangGraph, CrewAI, tool calling, MCP, RAG with agents, multi-agent systems, guardrails |
| Tools covered | LangGraph, CrewAI, MCP, LangChain, OpenAI/Anthropic APIs, Python |
| Projects / exercises | Multi-agent research assistant, RAG-powered agent, MCP-connected assistant, document review agent, human approval workflow |
| Corporate option | Yes — customised corporate Agentic AI training for Bangalore teams |
| Contact | corporate@technovids.com · +91 86183 46384 · WhatsApp available |
Why Learn Agentic AI in Bangalore?
Bangalore teams are moving beyond chatbots to AI systems that act
Developers and product teams across Bangalore have experimented with ChatGPT and basic LLM APIs. The next step is building AI systems that plan, use tools, delegate subtasks, and operate across multi-step workflows — which requires structured agentic AI training.
Agentic AI powers enterprise automation, not just Q&A
AI agents are useful for research automation, customer support triage, document review, internal operations, and workflow orchestration. Understanding agent design — tool calling, state management, guardrails, and evaluation — is essential for building reliable AI-powered systems.
LangGraph, CrewAI, and MCP are the tools Bangalore teams are adopting
Indian product and engineering teams are evaluating LangGraph for stateful agent workflows, CrewAI for multi-agent systems, and MCP for tool integration. Hands-on training with these frameworks closes the gap between exploring demos and shipping production agentic AI systems.
Guardrails, evaluation, and safe agentic patterns matter in production
Building an agent prototype is approachable. Building one that is reliable, auditable, and safe in production requires structured knowledge of guardrails, human-in-the-loop patterns, scope constraints, and evaluation. That's what this training covers.
What You Will Learn
A practical, code-first agentic AI curriculum — from agent fundamentals through production deployment patterns.
AI Agents Fundamentals
What AI agents are, how they differ from chatbots and simple LLM calls, and where they are useful in real systems.
Agentic AI Workflows
Design agent pipelines that perceive inputs, decide actions, call tools, and produce outputs across multi-step workflows.
AI Agents vs Chatbots
Understand the architectural and capability differences — when a basic LLM call is enough and when an agent is required.
Tool Calling
Implement function/tool calling with OpenAI and Anthropic APIs — structured outputs, tool definitions, and agent loops.
Planner / Executor Patterns
Build agentic systems with a planning layer that decomposes goals and an executor layer that carries out subtasks.
Multi-Agent Workflows
Design systems with multiple agents that have distinct roles, communicate through shared state or message passing, and collaborate on complex tasks.
LangGraph Basics
Build stateful agent workflows as directed graphs — nodes, edges, state objects, conditional branching, and loops using LangGraph.
CrewAI Basics
Build multi-agent crews with roles, goals, tasks, and agent-to-agent delegation using the CrewAI framework.
RAG with Agents
Integrate retrieval-augmented generation into agent workflows — agents that search, retrieve, and reason over documents.
MCP and Tool Integrations
Use Model Context Protocol to connect agents to external tools, APIs, databases, and file systems in a standardised way.
Human-in-the-Loop Workflows
Design agent pipelines with approval gates, escalation steps, and human intervention points for high-stakes tasks.
Guardrails and Safe Usage
Apply input/output guardrails, intent filters, scope constraints, and safe agent patterns to reduce risk and misuse.
Evaluation and Monitoring Basics
Measure agent task success, trace agent steps, log tool calls, and monitor agentic pipelines in production.
Practical Agentic AI Projects and Exercises
Every module is reinforced with a working agentic AI project you can extend for your own use case.
Multi-Agent Research Assistant
Build a multi-agent system where a planner agent decomposes research tasks and executor agents gather and synthesise information from multiple sources.
Learn more →AI Support Triage Workflow
Design a customer support triage agent that classifies incoming queries, routes them to the appropriate handler, and drafts suggested responses.
RAG-Powered AI Agent
Build an agent that answers questions by retrieving relevant documents from a vector store and reasoning over retrieved context with citations.
Learn more →MCP-Connected Productivity Assistant
Connect an LLM agent to external tools via MCP — file system access, API calls, and structured data retrieval — using the Model Context Protocol.
Learn more →Document Review Agent
Create an agentic pipeline that reads, analyses, and summarises multiple documents, flags key clauses, and produces a structured review report.
Human Approval Workflow
Implement a LangGraph agent workflow with a human-in-the-loop checkpoint — the agent pauses, presents a decision for human review, and resumes on approval.
Learn more →Agent Workflow with LangGraph or CrewAI
Build a complete agentic workflow using either LangGraph (stateful graph) or CrewAI (role-based crew), comparing the experience of each approach.
Learn more →Who Should Join in Bangalore?
Designed for technical learners and teams — basic Python knowledge is recommended for the practical projects.
Software Developers
Build AI agent systems on top of your existing development skills — from Python and APIs to full agentic workflows.
Python Developers
Apply your Python skills to build working agent pipelines with LangGraph, CrewAI, and MCP from day one.
AI Engineers
Deepen agentic AI expertise — multi-agent orchestration, tool calling, MCP, evaluation, and production deployment patterns.
Data Scientists
Extend data science workflows with AI agents that can retrieve data, call tools, and coordinate multi-step analysis tasks.
Data Engineers
Build intelligent data workflows where agents orchestrate pipelines, handle exceptions, and adapt to runtime conditions.
Technical Managers
Understand agentic AI deeply enough to architect enterprise AI projects, evaluate vendor solutions, and guide technical teams.
Product Managers (Technical)
Learn the capabilities and limits of AI agents to design better AI-powered products and write informed product specifications.
Corporate AI Teams
Train your Bangalore team to build agentic AI systems that automate workflows, handle operations, and power enterprise AI assistants.
Startup Founders (Technical)
Build the agentic backbone of your AI product — autonomous workflows, research assistants, and multi-step AI systems.
Agentic AI Course Bangalore vs AI Engineering Course Bangalore
Focused agent depth vs the full AI engineering curriculum — choose based on your immediate goal.
| Criteria | Agentic AI Course Bangalore | AI Engineering Course Bangalore |
|---|---|---|
| Audience | Developers, AI engineers, technical managers | Developers, engineers, Python learners |
| Scope | Agentic AI focused deep dive | Full AI engineering curriculum |
| Agent depth | Complete — all agent and workflow modules | Agents as one of several core modules |
| Other AI topics | None — agents and workflows only | Prompt engineering, RAG, LangChain, FastAPI, deployment |
| Tools | LangGraph, CrewAI, MCP, tool calling | LangChain, LangGraph, MCP, RAG, FastAPI, cloud |
| Project complexity | Agentic systems — multi-agent, RAG-agent, MCP-agent | 5 production AI systems including agentic workflows |
| Best suited for | Teams building agent systems and workflows now | Developers wanting the full AI engineering stack |
| Natural next step | AI Engineering Course Bangalore for broader AI skills | Production AI Engineering programme |
Want the full AI engineering curriculum? Explore the AI Engineering Course Bangalore →
Agentic AI Course Bangalore vs Agentic AI Explained
Structured training vs a free informational guide — different purposes for different needs.
| Criteria | Agentic AI Course Bangalore | Agentic AI Explained |
|---|---|---|
| Page type | Commercial training page — enrol and learn | Free informational guide — read and understand |
| Purpose | Structured training programme with projects | Conceptual explanation of Agentic AI |
| Audience | Learners ready to build agentic systems | Anyone wanting to understand what Agentic AI is |
| Content | Curriculum, projects, tools, frameworks | Definition, examples, use cases, comparisons |
| Schema | Course + CourseInstance + LocalBusiness | Article + FAQPage |
| Outcome | Certificate of completion + practical projects | Better understanding of Agentic AI concepts |
| Best suited for | Developers and teams ready to train | Researchers, decision-makers, curious learners |
Just exploring the concept first? Read Agentic AI Explained →
Book Your Free Agentic AI Course Consultation
Tell us your background, current tech stack, and what you want to build with agentic AI. We will get back within one business day to schedule your free 30-minute consultation.
- Free 30-minute consultation — no obligation
- Weekend cohorts for Bangalore working professionals
- Live instructor-led sessions with session recordings
- Local office support at HSR Layout, Bengaluru
- Corporate Agentic AI training available for Bangalore teams
Local Learning Options for Bangalore
Flexible Agentic AI training delivery for individuals, teams, and corporate clients.
Live Online Cohort
Weekend instructor-led sessions. Recordings within 24 hours. Open to all Bangalore learners.
HSR Layout Office Support
Visit our Bengaluru office for in-person consultation and course guidance before or during training.
Blended Learning
Live online sessions with optional in-person consultation at HSR Layout for Bangalore-based participants.
Corporate Agentic AI Training Bangalore
Customised on-site or online Agentic AI training for Bangalore engineering and AI teams. Scoped to your use cases.
Learn more →1:1 AI Engineering Mentorship
Personalised project guidance, agent architecture review, and AI engineering mentorship for advanced learners.
Learn more →National Agentic AI Training
Also available as a national programme for learners across India outside Bangalore.
Learn more →Find Technovids in Bangalore
Office
Technovids Consulting Pvt. Ltd.
2nd Floor, Chandrodaya Complex
19/19 24th Main Rd, 1st Sector
HSR Layout, Bengaluru
Karnataka 560102, India
Hours
Monday – Friday, 9 AM – 6 PM IST
Weekend cohorts available for working professionals
Related Courses and Learning Resources
Deepen your agentic AI and AI engineering knowledge with these Technovids resources.
All Technovids AI courses for Bangalore learners
Full AI engineering curriculum for Bangalore developers
Custom AI training for Bangalore corporate teams
RAG training — embeddings, vector databases and LangChain
Free guide — what agentic AI is and how it works
How AI agents work — tools, memory, planning and action
Which agentic framework to choose for your project
LangGraph for stateful, graph-based agent workflows
Model Context Protocol — how agents connect to tools
All Technovids AI guides and references
Frequently Asked Questions — Agentic AI Course Bangalore
Common questions from Bangalore developers, AI professionals and corporate clients.
Do you offer an Agentic AI Course in Bangalore?+
Where is Technovids located in Bangalore?+
Is the Agentic AI Course suitable for software developers?+
Does the course cover LangGraph and CrewAI?+
Does the course cover MCP and tool calling?+
What is the difference between Agentic AI Course Bangalore and AI Engineering Course Bangalore?+
Do you offer corporate Agentic AI training in Bangalore?+
Can I visit the HSR Layout office before enrolling?+
Does the course include multi-agent AI workflows?+
How do I contact Technovids for the Agentic AI Course Bangalore?+
Start Learning Agentic AI from Bangalore
Build production-ready AI agents and agentic workflows using LangGraph, CrewAI, MCP, tool calling, RAG, and human-in-the-loop patterns.
Exploring all AI courses in Bangalore? Browse all AI courses in Bangalore — GenAI, AI Engineering, RAG training and more.