A Major Shift in Agentic AI Is HereFeatured

Be Among the First to Learn Amazon Bedrock (AgentCore Focused).

The Next Era of Agentic AI Is Here.

Get hands-on with the latest Amazon Bedrock AgentCore technology and learn how to build, deploy, and operate production-ready AI agents through a live, enterprise-focused program.

Learn it early. Build with it first. Stay ahead of the Agentic AI shift.

WITHMr. Vimal Daga17–23 August 2026Live Online20 Hours
₹4,999₹20,00048-Hour Launch OfferSave ₹15,000
Save ₹15,000 — Register NowView Complete Curriculum
Build→Secure→Evaluate→Deploy→Scale

0

Hours

Live Technical Training

0

Days

17–23 August 2026

0%

Hands-on

Build in every session

0

Major Builds

Hands-on projects

0

Capstone

Enterprise AI Capstone

Curriculum

20 hours. 7 days. One production build.

Approximately 3 hours daily, with 2 hours on the final day.

Enterprise Generative AI

  • —Generative AI vs Traditional ML
  • —Foundation Models & LLMs
  • —Enterprise AI Architecture
  • —Why enterprises use managed GenAI platforms
  • —Where Amazon Bedrock fits in the enterprise AI stack

Amazon Bedrock Architecture

  • —Amazon Bedrock overview
  • —Foundation Model access
  • —Model selection
  • —Bedrock APIs
  • —AWS SDK integration
  • —Console vs API-based development
  • —Inference fundamentals

Foundation Models

  • —Model selection strategy
  • —Capability vs cost considerations
  • —Text generation
  • —Summarization
  • —Classification
  • —Information extraction
  • —Multimodal possibilities

Prompt Engineering

  • —Zero-shot prompting
  • —Few-shot prompting
  • —Role-based prompting
  • —Structured outputs
  • —Prompt templates
  • —Context management
  • —Prompt optimization

Hands-on 1

Bedrock AI Application

Invoke a foundation model through Bedrock and build a simple Enterprise Document / Text Intelligence application.

Why RAG?

  • —LLM knowledge limitations
  • —Enterprise / private data
  • —Hallucination problem

RAG Architecture

  • —Retrieval
  • —Context
  • —Generation

Embeddings & Semantic Retrieval

  • —Embeddings
  • —Chunking strategies
  • —Vector representations
  • —Similarity search
  • —Metadata
  • —Retrieval quality
Documents→Chunking→Embeddings→Vector Retrieval→Context→LLM→Answer

Amazon Bedrock Knowledge Bases

  • —Knowledge Base architecture
  • —Data sources
  • —Data ingestion
  • —Parsing
  • —Chunking
  • —Embeddings
  • —Retrieval
  • —Reranking
  • —Metadata filtering

Hands-on 2

Enterprise RAG Application

Build an application that answers questions from a private document repository using Knowledge Bases / RAG.

  • HR Knowledge Assistant
  • Technical Documentation Assistant
  • Policy Assistant
  • Product Knowledge Assistant
  • Developer Documentation Search

From Chatbots to AI Agents

  • —AI Assistants vs AI Agents
  • —Agentic AI architecture
  • —Reasoning & orchestration
  • —Tool calling
  • —Function / API invocation
  • —Context and memory concepts

Amazon Bedrock Agent Capabilities

  • —Agent architecture
  • —Instructions
  • —Action groups
  • —API integration
  • —Lambda integration
  • —Knowledge Base integration
  • —Workflow orchestration
Understand→Decide→Retrieve→Invoke Tool→Execute→Respond

Responsible Enterprise AI

  • —AI security fundamentals
  • —Data privacy
  • —Sensitive information
  • —Prompt injection
  • —Unsafe responses
  • —Responsible AI

Amazon Bedrock Guardrails

  • —Guardrail architecture
  • —Content filters
  • —Denied topics
  • —Sensitive information filters
  • —Word filters
  • —Input / output protection
  • —Applying guardrails to models, Knowledge Bases and Agents

AI Evaluation

  • —Response quality
  • —Groundedness
  • —Relevance
  • —Retrieval quality
  • —Model evaluation
  • —RAG evaluation

Hands-on 3

Enterprise AI Agent

Build an AI IT Support Agent that understands a problem, searches enterprise documentation, identifies an action, invokes an API/tool and generates a response.

  • IT Helpdesk Agent
  • Customer Support Agent
  • Developer Assistant
  • Financial Operations Assistant
  • Internal Business Process Agent

Monitoring & Cost Optimization

  • —Token consumption
  • —Latency
  • —Logging
  • —Monitoring
  • —Cost considerations
  • —Model selection for cost / performance

Enterprise AI Architecture & Integration

  • —Amazon S3
  • —AWS Lambda
  • —API Gateway
  • —DynamoDB / RDS concepts
  • —CloudWatch
  • —IAM

Production Considerations

  • —Security
  • —Scalability
  • —Cost optimization
  • —Model selection
  • —Access control
  • —Monitoring
  • —Governance
  • —Application lifecycle
  • —Production readiness
Build→Attack→Guard→Evaluate→Improve

Hands-on 4 — Final Capstone

Secure and Evaluate the RAG Application

Then build an Enterprise GenAI Assistant combining Foundation Model, Prompt Engineering, Knowledge Base / RAG, Semantic Retrieval, Guardrails, AI Agent, Tool/API Integration and Enterprise Application.

Register Now

Hands-on Projects

You don’t just learn it. You build it.

Four major builds culminating in a production-oriented Enterprise GenAI capstone.

Project 01

Bedrock AI Application

Foundation Model + Prompt Engineering

01
App→Bedrock→Foundation Model→Response
Technologies
Amazon BedrockBedrock APIsAWS SDKPrompt Templates
Skills developed
Model selectionPromptingStructured outputs

OutcomeAn Enterprise Document / Text Intelligence application.

Project 02

Enterprise RAG Application

Knowledge Base + Embeddings + Semantic Retrieval

02
Documents→Chunking→Embeddings→Retrieval→LLM
Technologies
Bedrock Knowledge BasesEmbeddingsVector Retrieval
Skills developed
Chunking strategyMetadata filteringRetrieval quality

OutcomeQ&A over a private enterprise document repository.

Project 03

Enterprise AI Agent

Agent + Tool/API Integration + Enterprise Knowledge

03
Agent→Knowledge Base→Action Group→Lambda / API
Technologies
Bedrock AgentsAction GroupsAWS Lambda
Skills developed
OrchestrationTool callingWorkflow design

OutcomeAn AI IT Support Agent that acts, not just answers.

Project 04

Production-Ready Enterprise GenAI Capstone

RAG + Agent + Guardrails + Evaluation + Integration

04
Build→Attack→Guard→Evaluate→Improve
Technologies
GuardrailsEvaluationCloudWatchIAMS3
Skills developed
SecurityGroundednessObservabilityCost awareness

OutcomeA secured, evaluated end-to-end Enterprise GenAI Assistant.

Register Now

Platform Shift

AWS just changed the game.The era of AI agents is moving forward.

Amazon Bedrock Agents Classic is no longer open to new customers starting July 30, 2026. AWS is moving toward Amazon Bedrock AgentCore for building, connecting, securing, observing, evaluating and scaling production AI agents.

Amazon Bedrock continues to be available

Bedrock Foundation Models continue to matter

Bedrock Knowledge Bases continue to matter

Bedrock Guardrails continue to matter

Legacy layerBedrock Agents Classic is the legacy orchestration layer.

Modern layerAgentCore is the modern production-oriented agent platform.

Transition path

AgentCore — the new era of production AI agents

  1. 01Bedrock Foundation Models
  2. 02Prompt Engineering
  3. 03RAG / Knowledge Bases
  4. 04AI Agents
  5. 05AgentCore
  6. 06Secure
  7. 07Observe
  8. 08Evaluate
  9. 09Production

The Shift

From using AI to building Enterprise AI.

A practical, use-case-driven and production-oriented learning journey for professionals and students who want to understand how enterprise AI applications are built, integrated, secured, evaluated and deployed.

Before

“I know how to use AI.”

  • Prompts
  • Chat interfaces
  • AI tools
  • Basic API calls
build

After

“I know how to build Enterprise AI.”

  • Foundation Models
  • RAG
  • Knowledge Bases
  • Agents
  • Tool Integration
  • Guardrails
  • Evaluation
  • Observability
  • Production Architecture
Register Now

Market Demand

The market is hiring. Are you ready?

Enterprise AI and Agentic AI roles are exploding across India. Companies are actively hiring professionals who can build, deploy, and manage production AI agents with AWS Bedrock.

12,000+

Active GenAI Jobs in India

₹15–50 LPA

Average Salary Range

3x

Growth in AI Agent Roles (2025–26)

Live Job Listings — GenAI & AI Agent Roles in India (August 2026)

AWS AI Architect - Amazon Bedrock & Generative AI role
Software Engineer - Amazon Bedrock, Amazon Q, AI Agents
AI Architect with Amazon Bedrock Experience
GenAI Professionals - Amazon Bedrock
Solutions Architect - AWS AI/ML

These roles demand hands-on Bedrock & AgentCore skills.

This training builds exactly what the market is paying for.

Why This Training

This is not a “watch and learn” course.

A practical, use-case-driven and production-oriented learning experience designed around building, testing, securing, evaluating and understanding Enterprise GenAI applications.

01

Build

Build real AI applications.

02

Integrate

Connect AI with enterprise data and APIs.

03

Secure

Understand Guardrails, privacy and responsible AI.

04

Productionize

Understand architecture, observability, scalability and cost.

Outcomes

What you will walk away with

  • Foundation Models
  • Bedrock APIs & SDK
  • Prompt Engineering
  • Embeddings
  • RAG
  • Knowledge Bases
  • Semantic Retrieval
  • AI Agents
  • Tool / API Integration
  • Guardrails
  • AI Evaluation
  • Observability
  • Enterprise AI Architecture
  • Production Considerations
  • End-to-End GenAI Capstone

Who Should Join

Built for people building the next generation of AI.

  • AI / GenAI Engineers
  • Cloud Engineers
  • DevOps Engineers
  • Software Developers
  • Data Scientists
  • ML Engineers
  • Solution Architects
  • MLOps / LLMOps Engineers
  • Working IT Professionals
  • Engineering Students interested in Enterprise AI
Mr. Vimal Daga

Mentor

Learn from a World-Record-Holding Technology Mentor.

Mr. Vimal Daga

  • World Record Holder
  • Enterprise Technology Architect
  • Corporate Trainer & Technology Evangelist
  • 23+ Years of Technology Experience
  • Expertise across 155+ Tools & Technologies

The complete 20-hour live program is personally delivered by Mr. Vimal Daga, combining 23+ years of technology expertise with practical, enterprise-focused training. Every session is hands-on, use-case driven, and focused on building real-world Generative AI solutions with AWS Bedrock.

Learn directly from a mentor who has worked across a vast technology landscape and knows 155+ tools and technologies — bringing that breadth of experience into every practical session.

No passive learning. No theory-only sessions. Just live implementation, real workflows, and production-oriented GenAI skills.

Join the Live Training

Pricing

Launch offer

Launch Offer: ₹4,999 inclusive of applicable taxes, available only for the first 48 hours from launch. Thereafter, the regular price of ₹6,999 inclusive of applicable taxes will apply.

48-Hour Launch OfferSave ₹15,000
₹4,999₹20,000

All inclusive of applicable taxes

  • 20 hours of live hands-on training
  • 7 days · 17–23 August 2026
  • 4 major hands-on builds
  • Enterprise GenAI capstone
  • Live guidance from Mr. Vimal Daga
Save ₹15,000 — Register NowView Curriculum

AWS cloud usage / Bedrock model consumption charges, if applicable, are separate from the training fee.

The launch offer won't last.

₹4,999→₹6,999 · First 48 hours only

Claim launch offer

FAQ

Questions, answered.

Register Now

Don't just use AI.Build what enterprises run on.

Move from “I know how to use AI” to “I know how to build Enterprise AI.”

Prompt→Model→RAG→Agent→Secure→Evaluate→Integrate→Production

17–23 August 2026 · Live with Mr. Vimal Daga · ₹4,999 for the first 48 hours

Save ₹15,000 — Register NowView Curriculum

Have questions?

Live Online | 17–23 August 2026

977220144993510 09002Talk to our team

₹4,999₹20,000

17–23 Aug 2026 · Live

Register Now