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Building Agentic AI System with Bedrock

IntermediateLevel
2761+Students Enrolled
40 MinsDuration
4.9Average Rating

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About this Course
Learning Outcomes
Who Should Enroll
Course Curriculum
Instructors

About this Course

Trace Bedrock’s shift from basic prompt calls to RAG and multi-agent blueprints, showing why agentic patterns beat static orchestration in real apps.
Apply Bedrock Guardrails to filter risky content, enforce data privacy, and log reasoning, then package configs for secure rollout across enterprise environments
Finish by benchmarking agent precision, latency, and cost, and setting up CI/CD that version-controls prompts, tests, and deployments for repeatable releases.

Learning Outcomes

Agentic Design Shift

Explain how gen-AI evolved from prompt calls to collaborative agents.

Bedrock Agent Setup

Configure knowledge bases & Lambda to extend agent reasoning.

Multi-Agent Orchestration

Chain specialist agents for retrieval, synthesis and decision tasks.

Who Should Enroll

Software engineers already shipping on AWS who need a fast ramp-up to Bedrock Agents for data-aware apps.
Product or project leads overseeing GenAI features who must evaluate cost, safety, and deployment trade-offs.
BData scientists and ML engineers seeking hands-on RAG, tool-calling, and guardrail skills without deep DevOps.

Course Curriculum

Explore a comprehensive curriculum covering Python, machine learning models, deep learning techniques, and AI applications.

1. Introduction to Agentic systems
2. Introduction to Amazon Bedrock Agents

Meet the instructor

Our instructor and mentors carry years of experience in data industry

Vikesh Pandey

Principal Gen AI | AWS |

Vikesh is an experienced Generative AI/ML professional with 15+ years of experience in machine learning, cloud and application development.He helps some of the largest global brands from the financial industry.

Get this Course Now

With this course you’ll get

40 Mins
Duration
Nikhil Pentapalli
Instructor
Intermediate
Level

Certificate of completion

Earn a professional certificate upon course completion

Globally recognized certificate
Verifiable online credential
Enhances professional credibility

certificate

Frequently Asked Questions

Looking for answers to other questions?

Agentic systems are AI setups where models operate autonomously, making decisions and executing tasks in a workflow, similar to intelligent assistants.

Amazon Bedrock is a fully managed service that enables developers to build and scale generative AI applications using foundational models from leading providers.

RAG tackles issues like misinformation and context loss by ensuring outputs are supported by up-to-date, retrieved data.

Yes, the course provides a certification upon completion.

RAG offers the advantage of grounding responses in factual data, reducing errors common in pure generative models and providing more context than retrieval-only approaches.

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