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Agentic AI Course in Hyderabad

Built for engineers, AI builders, and technical product professionals in Hyderabad who want to move beyond lightweight GenAI demos, this live online program focuses on how real agent systems are designed, evaluated, traced, and deployed. You can take the deeper engineering route, or a more product-led track if your role is closer to AI feature planning and delivery.

Design Agent Systems
Orchestration, tools, and workflow logic
Build Grounded Retrieval
Agentic RAG with measurable quality
Debug with Traces
Review failures and improve reliability
Ship with More Confidence
From demo stage to deployment thinking

Designed for Serious Working Professionals

Technical Depth Without Self-Paced Drift

Live mentor-led sessions keep the learning serious and structured, which matters when the work moves from prompting into orchestration, evals, tracing, and deployment.

Built for Working Professionals

The format is designed for full-time professionals who need live teaching, recordings, and enough structure to keep momentum without depending on offline attendance.

Two Practical Learning Routes

The engineering route goes deeper into frameworks, tool use, and systems design. The product-led route stays focused on AI feature thinking, guardrails, evaluation, and delivery quality.

Built Around Real Project Work

Projects focus on grounded retrieval, agent workflows, evaluation loops, and production-aware implementation instead of one-off demo builds.

Learning Format
Live Online with Recordings
Course Duration
16 Weeks
Next Cohort starts
13 Apr, 2026

What You Will Learn in Practice

Agent Frameworks in Practice

Work with LangChain, LangGraph, CrewAI, and AutoGen to understand which orchestration patterns fit which systems and where they tend to fail.

Tooling, Contracts, and Execution

Use MCP and practical tool-interface thinking to build clearer integrations, safer tool usage, and workflows that are easier to maintain.

Retrieval, Evals, and Observability

Build Agentic RAG systems with grounding, reranking, citations, trace review, and evaluation loops that make quality easier to inspect.

Deployment and Runtime Thinking

Move beyond notebooks into serving, operational tradeoffs, runtime behavior, and release decisions that matter once a system is used by others.

Main Course Page

Explore the full curriculum

This page gives you the Hyderabad-specific view. For the complete module breakdown, project scope, tool coverage, 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

Complete Module View

See the full curriculum structure beyond the Hyderabad-specific narrative.

Project Scope

Review the broader project mix and capstone depth in one place.

Certification Details

Understand how the certificate fits into the overall program structure.

Flagship Program View

Use the main page when you want the full non-city version of the course.

Industry-Recognized CertificationLive Mentor-Led SessionsPlacement Assistance4.9 ★ Average Rating

Why This Context Matters

Hyderabad is one of India's strongest enterprise-tech and GCC hubs, which makes it a practical city context for learning agent systems that need to work beyond prototypes.

Public industry summaries from IBEF note that Telangana's IT exports reached Rs. 2,68,233 crore in FY24, and Hyderabad has long been positioned as a major technology hub. That matters because many product teams, enterprise platforms, and GCC environments now need people who can reason about grounded outputs, measurable quality, trace review, and deployment decisions rather than just prompt results.

What Sets This Program Apart

The difference is not just the list of frameworks. It is the focus on system quality, reviewability, and delivery.

Feature
Outcome
School of Core AI

Deployable agent systems with evals and traces

Other Institutes

Prompt demos and simple bots

Feature
Tracks
School of Core AI

AI Engineer track plus PM no-code track

Other Institutes

One-size-fits-all

Feature
Evaluation
School of Core AI

Eval harnesses and regressions built into projects

Other Institutes

No measurable quality loop

Feature
Observability
School of Core AI

Tracing, tool logs, failure analysis workflows

Other Institutes

Little debugging discipline

Feature
Serving
School of Core AI

Local and cloud serving patterns

Other Institutes

Deployment often skipped

Feature
Support
School of Core AI

Mentor reviews, office hours, capstone checkpoints

Other Institutes

Limited feedback

How Learning Happens Here

01

Live Mentor-Led Sessions

Weekly live classes focused on building real agent systems, not slides. Learn concepts while implementing production-style workflows.

02

Recordings and Flexible Learning

All sessions are recorded so working professionals can revisit builds, debug steps, and architecture explanations anytime.

03

Hands-On Projects

Progress through structured projects covering multi-agent workflows, Agentic RAG, evaluation loops, and deployment basics.

04

Design and Trace Reviews

Mentors review system design, tool usage, grounding quality, and traces so you learn how real teams debug AI systems.

05

Mock Interviews and Portfolio Prep

Practice agent architecture discussions, RAG design reasoning, and troubleshooting scenarios aligned to real hiring rounds.

06

Career Guidance and Referrals

Resume refinement, project storytelling, and role mapping support aligned to Hyderabad product teams, GCCs, and AI startups.

What You Will Build

Build projects you can explain clearly in interviews, reviews, and real product discussions.

The goal is not to finish with another chatbot demo. It is to leave with work that reflects how agent systems are actually designed: grounded retrieval, tool use, evaluation, trace-based debugging, and deployment-minded implementation.

What You Will Be Able to Do

01

Ship Agent Features in Products

Build agents that plan, use tools, retrieve knowledge, follow constraints, and behave reliably in real usage.

02

Make Quality Measurable

Create evaluation loops, regression checks, and trace reviews so improvements are repeatable.

03

Operate With Confidence

Learn serving basics, monitoring signals, cost control, and safe rollouts for real deployments.

04

Build a Strong Portfolio

Graduate with projects you can explain clearly in interviews, including tradeoffs and trace-driven debugging.

How the 16 Weeks Unfold

1

Foundation

  • Core concepts
  • Tools & setup
  • Hands-on intro
2

Build

  • Advanced techniques
  • Guided projects
  • Industry tools
3

Specialise

  • Elective tracks
  • Capstone project
  • Peer reviews
4

Launch

  • Portfolio prep
  • Mock interviews
  • Placement drive

Agentic AI Certification in Hyderabad

Earn a verifiable certificate after project reviews and final evaluation, demonstrating agent design, grounded RAG, evaluation literacy, and deployment readiness.

Certificate of Completion

Issued by School of Core AI upon successful completion of the programme

The Learning Community Around the Program

Learn with developers, AI practitioners, and product professionals in live cohorts. The community value comes from mentor reviews, shared repos, mock interviews, and peer conversations that stay useful after class hours.

Built for Hyderabad Working Professionals

Live mentor access and recordings
Live mentor access and recordings
Peer learning and reviews
Peer learning and reviews
Shared repos and feedback loops
Shared repos and feedback loops
Mock interviews and prep groups
Mock interviews and prep groups
Referrals guidance and hiring signals
Referrals guidance and hiring signals
Learners and alumni work across product teams, GCCs, consulting environments, and enterprise AI groups in Hyderabad and beyond.

Where Learners and Alumni Work

What Learners Actually Say

The biggest upgrade for me was learning evaluation and trace debugging. My project went from something that looked good in a demo to something I could explain properly as a system.
RK
Ramesh K.
Applied AI Engineer
The product-led track helped me write much better specs, guardrails, and acceptance criteria for agent features. It made discussions with engineering more concrete and less vague.
FS
Fatima S.
Product Manager
Tool contracts, retries, and budgets changed how I build. It was one of the first courses where reliability was treated like part of the work rather than an afterthought.
SR
Sandeep R.
Machine Learning Engineer
Capstone reviews were strong. I got much better at explaining design decisions, tradeoffs, and failure cases instead of just presenting final outputs.
PM
Priyanka M.
GenAI Developer

Hiring Partners

Career Opportunities for Agentic AI in Hyderabad

Across Hyderabad product teams, enterprise platforms, GCC environments, and AI-first startups, the useful hiring signal is shifting toward people who can build systems that are reviewable, grounded, and deployable.

That makes skills like orchestration, retrieval quality, evaluation, tracing, and rollout thinking more valuable than surface-level GenAI familiarity alone.

AI Engineer (Agents)

Design and build agent workflows with tool schemas, memory, safety gates, evaluation loops, and trace-based debugging.

Applied AI / RAG Engineer

Own retrieval-first systems with chunking, hybrid retrieval, reranking, grounding, citations, and evaluation pipelines.

LLMOps / Platform

Support runtime behavior, telemetry, deployment patterns, cost awareness, and safer releases for AI systems in production.

Product Manager (AI)

Own AI feature specs, evaluation plans, guardrails, and rollout strategy, and work closely with engineering on trace-driven iteration.

AI Safety / Governance

Support safe deployments through risk reviews, red-teaming inputs, monitoring signals, and policy guardrails.

Related Paths

If you are comparing agent engineering with broader GenAI, deployment, or AI application tracks, start here.

Agentic AI Course Fees in Hyderabad

Single transparent fee covering complete training, real-world projects, certification and placement support. EMI and part-payment options are available with our counsellor.

Total Course Fee
35,000

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

It is live online with recordings. There are no offline classes attached to this Hyderabad page. This page is the Hyderabad-specific view of the same flagship program.