Agentic AI Course in Bangalore
Built for engineers, developers, AI builders, and technical product professionals who want more than lightweight GenAI demos, this 16-week live online program focuses on how real agent systems are designed, evaluated, traced, and deployed. You will work across LangChain, LangGraph, LangSmith, Langtrace, CrewAI, AutoGen, LangFlow, MCP, Agentic RAG, AWS, Playwright, evals, and production-minded implementation patterns. Next cohort 13 Apr, 2026.
Designed for Busy Professionals
Classes are live, mentor-led, and structured. The goal is not just content access, but real teaching, discussion, and technical clarity.
The format is built for people managing demanding jobs. You can learn seriously without depending on offline attendance or city commutes.
When the material gets technical, access matters. You get instructor support for questions, design thinking, and implementation decisions.
The program stays focused on system design, evaluation, debugging, and delivery - the parts that matter once the demo phase is over.
What You'll Actually Learn
Agent Frameworks in Practice
Work with LangChain, LangGraph, CrewAI, and AutoGen to understand when each orchestration pattern is useful, where it breaks, and how to design agent flows that stay explainable.
Tooling, Interfaces, and Automation
Use MCP, LangFlow, and Playwright to think clearly about tool contracts, browser workflows, and maintainable agent integrations rather than loose demo wiring.
Observability, Retrieval, and Evals
Build grounded retrieval workflows and evaluate them with LangSmith, Langtrace, tracing, reranking, citation-aware outputs, and quality loops that make system behavior reviewable.
AWS and Deployment Thinking
Inspect traces, review tool calls, understand failure paths, and move agent systems toward practical local or AWS-based deployment workflows with stronger operational thinking.
Explore the full curriculum
This page gives you the Bangalore-specific view. If you want the complete module breakdown, project scope, and certification details, the main course page gives you the broader program view.
No signup required — explore at your own pace
What you'll find on the main page
Full Module View
See the complete structure of the course beyond the city-specific page.
Project Scope
Review the broader project mix and capstone direction in one place.
Certification Details
See how certification fits into the overall program structure.
Complete Program View
Use the flagship page when you want the broad, non-city version of the course.
Why Live Online Works Here
For many serious learners, the challenge is not motivation. It is finding a technically strong program that still fits around full-time work.
That is where the live online format matters. You keep the advantages of mentor-led teaching, technical discussion, and direct feedback without depending on travel or self-paced learning alone. For many professionals in Bangalore, that balance is one of the main reasons this format works.
What Sets This Program Apart
The difference is not branding. It is the level of technical seriousness.
| Features | School of Core AI | Other Institutes |
|---|---|---|
| Teaching Model | ✓Live mentor-led sessions with structure, discussion, and technical guidance. | ✗Often a mix of videos, light interaction, or unclear live support. |
| Technical Depth | ✓LangGraph, MCP, Agentic RAG, evals, tracing, and deployment taught as one connected workflow. | ✗Often limited to prompt patterns, basic demos, or isolated tool walkthroughs. |
| What Gets Built | ✓Projects focus on tool use, grounded retrieval, debugging, and explainable architecture choices. | ✗Projects often stay at the demo level and are hard to defend in serious interviews. |
| How Quality Is Handled | ✓Quality is treated as measurable through evals, trace reviews, and regression thinking. | ✗Evaluation is often missing, which makes it hard to move beyond prototypes. |
| Working Professional Fit | ✓Designed for people who need strong teaching and technical access without offline attendance. | ✗Support and schedule quality are often not designed around serious full-time professionals. |
| Interview and Portfolio Value | ✓You leave with systems and tradeoffs you can explain clearly in interviews and project discussions. | ✗Learners often finish with surface-level examples that do not travel well into technical evaluation. |
Live mentor-led sessions with structure, discussion, and technical guidance.
Often a mix of videos, light interaction, or unclear live support.
LangGraph, MCP, Agentic RAG, evals, tracing, and deployment taught as one connected workflow.
Often limited to prompt patterns, basic demos, or isolated tool walkthroughs.
Projects focus on tool use, grounded retrieval, debugging, and explainable architecture choices.
Projects often stay at the demo level and are hard to defend in serious interviews.
Quality is treated as measurable through evals, trace reviews, and regression thinking.
Evaluation is often missing, which makes it hard to move beyond prototypes.
Designed for people who need strong teaching and technical access without offline attendance.
Support and schedule quality are often not designed around serious full-time professionals.
You leave with systems and tradeoffs you can explain clearly in interviews and project discussions.
Learners often finish with surface-level examples that do not travel well into technical evaluation.
Who This Is For
Software Engineers
For developers who want to build agent systems with structured orchestration, tool use, and measurable reliability.
AI and ML Builders
For practitioners who know the basics and now want practical depth in orchestration, retrieval, evaluation, and deployment.
Technical Product Professionals
For PMs and technical product leaders who need to understand agent architecture, failure modes, and implementation tradeoffs.
Working Professionals
For learners with full-time roles who need live sessions, recordings, and a format that works around demanding schedules.
Builders Who Want More Than Demos
For people who are done with superficial chatbot tutorials and want to build more credible, production-aware systems.
Technical Career Switchers
For professionals from engineering-heavy backgrounds who want to move toward applied AI, agent engineering, or AI product roles.
What You Will Build
You will leave with project work that looks like systems engineering, not just AI prompting.
Expect builds such as a multi-step assistant with tool calls, an Agentic RAG workflow with grounded retrieval, evaluation harnesses for testing output quality, trace-driven debugging setups, and a deployment-ready capstone that shows how your system behaves beyond the notebook stage.
The Stack and Tools You'll Work With
LangChain, LangGraph, CrewAI, AutoGen
Agent frameworks for orchestration, multi-step flow design, tool routing, memory, branching, and team-style agent patterns.
MCP, LangFlow, Playwright
Tool contracts, visual workflow experimentation, browser automation, and cleaner integration patterns for agents that need to act beyond a prompt box.
LangSmith, Langtrace, Agentic RAG, Evals
Tracing, observability, retrieval, reranking, grounding, test sets, and measurable quality loops so systems can be reviewed and improved.
AWS and Deployment
Debugging workflows, runtime thinking, local and cloud deployment patterns, and practical release-minded implementation for agent systems.
How the 16 Weeks Unfold
Foundation
- Core concepts
- Tools & setup
- Hands-on intro
Build
- Advanced techniques
- Guided projects
- Industry tools
Specialise
- Elective tracks
- Capstone project
- Peer reviews
Launch
- Portfolio prep
- Mock interviews
- Placement drive
Certification
Earn a verifiable certificate after completing the program and project reviews, with demonstrated work across agent frameworks, observability tooling, Agentic RAG, evals, tracing, and deployment workflows.
Certificate of Completion
Issued by School of Core AI upon successful completion of the programme
Our Learner Community
Built for Working Professionals
Our Alumni Network
What Learners Actually Say
Hiring Partners
Career Opportunities for Agentic AI in Bangalore
Bangalore's product, GCC, and applied AI ecosystem is hiring for people who can move beyond prompt experiments and contribute to real agent systems.
The useful signal today is not basic GenAI familiarity. It is whether you can explain orchestration, grounding, evaluation, tracing, and deployment choices clearly.
Build multi-step agent workflows with tools, orchestration logic, trace review, and stronger reliability discipline inside real products.
Own retrieval-heavy systems with grounding, reranking, citations, evaluation loops, and clear reasoning about output quality.
Support runtime behavior, deployment patterns, observability, cost awareness, and release-minded thinking for agent systems.
Define agent features, guardrails, evaluation plans, rollout expectations, and collaboration patterns with engineering teams.
Use tools, browser workflows, retrieval, and workflow automation to build useful internal systems that are easier to explain and maintain.
Related Paths
If you are comparing agent engineering with broader GenAI or deployment-focused paths, start here.
Fees and Next Cohort
Single transparent fee covering complete training, real-world projects, certification and placement support. EMI and part-payment options are available with our counsellor.
Final fee, EMI plans and any ongoing offers will be confirmed by your counsellor based on your batch, mode and payment preference.
Common Questions Before You Join
You will learn how to design, evaluate, debug, and deploy agent systems instead of stopping at prompt engineering or simple chatbot demos. The program covers orchestration, tool use, grounded retrieval, observability, evaluation, and production-minded implementation through live teaching and project work.