AWS Bedrock Training Course in Gurgaon
AI is the future innovation with Agentic AI tools and frameworks (Amazon Bedrock, ChatGPT, Gen AI, Bedrock AgentCore) for intelligent automation. We are delivering this training in Gurgaon where-in core Gen AI principles using patterns like multi-agents, reflection & others will be taught using hands-on training to become a Gen AI Engineer.
- Get mastery in building Agentic AI workflows for intelligent automation & to drive key businesses powered through Agentic AI frameworks like Amazon Bedrock, AgentCore Runtime
- Experience blended learning through interactive offline and online sessions.
- Job Oriented Training Course
- Course Duration - 3 months
- Get Trained from Industry Experts
Train using realtime course materials using online portals & trainer experience to get a personalized teaching experience.
Trained through leading industry professionals to get realtime project exposure
Gain professionals insights through leading industry experts across domains
24/7 Q&A support designed to address training needs
Amazon Bedrock Training Course
Kickstart your carrer in AI with certification in Generative AI Engineer (Amazon Bedrock) course, that will help in shaping the carrer to the current industry needs that need automation using intelligent workflows like Amazon Bedrock, Microsoft AutoGen, LangGraph, Vector DB & others in every domain & sphere of the industry that will allow organizations to boost decision making & also thrive business growth with improved customer satisfaction.
- Self-paced videos & training materials with archived session recordings
- Success Aimers targets industry employers to gain visibility
- Industry-paced training with realtime scenarios using Agentic AI frameworks/tools (n8n, Microsoft AutoGen, Langchain, LangGraph, AWS Bedrock, Azure Open AI & others) for intelligent automation.
- Real-World industry scenarios with projects implementation support
- Live Virtual classes heading by top industry experts alogn with project implementation
- Q&A support sessions
- Job Interview preparation & use cases
Explain Gen AI (Bedrock) Engineer?
AI Engineers automate business processes via AI development frameworks (Agentic AI) like Amazon Bedrock, Microsoft AutoGen, Langchain, LangGraph, AWS Bedrock, Azure Open AI & others for intelligent automation that will allow organizations to boost decsion making & also thrive business growth with improved customer satisfaction. AI engineers build optimized workflows, deployment & maintain the AI development lifecycle to deliver high-précised solutions to the clients using Agentic AI frameworks/workflow builders.
Role of Gen AI (Bedrock) Engineer?
Generative AI Engineers manages the end-to-end AI development lifecycle using Agentic AI frameworks (Amazon Bedrock) and intelligent workflow strategies.
Responsibilities include:
- Agentic AI Tools Adoption & automation using patterns like RAG ,Tools ,Reflection & others
- Continuously exploring new AI based frameworks/tools to build optimized workflows
- Deploying AI model within cloud infrastructure securly & seamlessly.
- Develop & Design AI workflows that meets business needs with automation scripts
- Success Aimers helps aspiring AI professionals to build, deploy, manage these Agents effectively seamlessly & to scale as per business needs.
Who should opt for Gen AI (Amazon Bedrock) Engineer course?
Gen AI course accelerates/boost carrier in AI & technology-driven organizations
- AI & Application Engineers – Develop Agentic AI workflows to automate business processes.
- Data Engineers – Implementing Data Pipelines using AI
- AI Developers – Automated workflows using Agentic AI frameworks/tools
- AI Leaders – Leading AI Governance & initiative within enterprise.
- Cloud & Infrastructure Engineers – Deploying AI developed applications seamlessly & effectively.
Prerequisites of Gen AI (Amazon Bedrock) Engineer Course?
Prerequisites required for the Generative AI Engineer Certification Course
- Below is the prerequisite to become a successful AI Professional:
- High School Diploma or a undergraduate degree
- Python Programming language
- IT Foundational Knowledge along wit Data Science & Software Development skills
- Knowledge of Cloud Computing Platforms like AWS, AZURE & GCP will be an added advantage.
Kind of Job Placement/Offers after Gen AI (Amazon Bedrock) Engineer Certification Course?
- Job Carrer Path in Generative AI & N8N Automation
- Generative AI Engineer – Develop & Deploy AI developed solutions/applications using agentic frameworks/tools
- AI/ML Engineer – Build context-aware, Enterprise ready AI systems.
- AI Automation Engineer – Design, Developed & build automated workflows to drive key business processes/decisions
- Cloud AI Engineer / AI Cloud Architect – Deploy AI Solutions seamlessly & effectively across enterprises with AI Governance strategy
- AI Model Deployment Engineer – Automate Model Deployment & AI Lifecycle management via MLOps pipeline & Agentic AI Frameworks
| Training Options | Weekdays (Mon-Fri) | Weekends (Sat-Sun) | Fast Track |
|---|---|---|---|
| Duration of Course | 2 months | 3 months | 15 days |
| Hours / day | 1-2 hours | 2-3 hours | 5 hours |
| Mode of Training | Offline / Online | Offline / Online | Offline / Online |
Amazon Bedrock Training Course Curriculum
Start your carrer in AI with certification in Generative AI with Amazon Bedrock Certification Course, that will help in shaping the carrer to the current industry needs that need automation using intelligent workflows like n8n, Amazon Bedrock Microsoft AutoGen, LangGraph & others in every domain & sphere of the industry that will allow organizations to boost decision making & also thrive business growth with improved customer satisfaction.
Generative AI & Foundation Models Concepts
- Overview – Generative AI & Foundation Models Concepts
- What is Generative AI and Use Cases
- How Generative AI works 1 – Prompt, Completion and Inferences
- How Generative AI works – Basic Concepts and Terminology
- Service Offerings in Generative AI from AWS
Amazon Bedrock – Deep Dive
- Section Overview – Amazon Bedrock
- Amazon Bedrock – Introduction
- Bedrock – Console Walkthrough – 1
- Bedrock – Console Walkthrough – 2
- Amazon Bedrock – Architecture
- Amazon Bedrock – Inference Parameters – Temperature
- Amazon Bedrock – Inference Parameters – 2
- Bedrock – Pricing
Text Models with Amazon Bedrock
- Understanding Model Parameters
- Amazon Titan
- Llama2
- Code Along Project – Call Transcript
Getting started with AWS Bedrock
- What is AWS Bedrock
- Introduction to Foundational Models
- Foundational Model Providers
- Bedrock Playground and Pricing
- Inspecting Model Inference Configurations for LLMs and Image Generation Models
- Training Foundation Models with you Custom Data
Amazon Bedrock Agents - Setup
- Amazon Bedrock Inline Agent – Intro
- Amazon Bedrock Agent Console
- Inline Agent vs Bedrock Agent
- Inline Agent Class Walkthrough
- AWS Profile – CLI
- IAM Access Key
Retreival-Augmented Generation (RAG) Agents with Bedrock
- Introduction & Importance of RAG
- How RAG Works: Ingestion, Retrieval, Generation
- Architecture of RAG & End-to-End Workflow
- Applications & Use Cases
- Challenges in Implementing RAG
- RAG – Example with Amazon Bedrock Embeddings and LLMs
Vector Databases & Embeddings - Bedrock Knowledge Bases
- Vector Databases & Embeddings for RAG Workflows
- Bedrock Knowledge Bases Model Access
- Create a Knowledge Base
- RAG Lambda
- RAG API Gateway Integration
- Using OpenAI LLM to Generate Responses from Vector Data
- LangChain & Pinecone Integration
- LangChain Embeddings Pinecone
- Bedrock Knowledge Bases
Implementation of RAG PDF Workflow - Build RAG Workflows Deep Dive
- Building a RAG Pipeline
- Architectural Diagrams & Workflow Setup
- Embedding Models & RAG Workflow with UI (Streamlit)
MCP Server with Amazon Bedrock Agents
- Bedrock Agent with Time MCP Server
- Bedrock Agent with Perplexity MCP Server
- Cost Analysis Agent – Multi MCP Servers and Builder Tools
- Cost Analysis Agent – Evaluate Agents
Code Generation Project with Bedrock
- Setting up Code Generation Project
- Coding our Lambda Function and integrating it with AWS Bedrock
- Setting up API Gateway and our Serverless Stack
- Testing our Live Endpoint
- Creating our Boto3 Lambda Layer
- Attaching our Lambda Layer to our Function
- Testing our Bedrock Model
- Verifying Final Output of Bedrock
Bedrock AI Agents & Agentic Workflows
- Overview of Bedrock AI Agents, Characteristics & Use Cases
- Building Bedrock AI Agents: Project Setup, Agent Class & Prompts
- Handling Complex Queries & Adding Tools
- Bedrock Concepts: Data, State, Nodes, Edges
- Human-in-the-Loop (HIL) Integration with Bedrock Agents
- Building Agentic Workflows with Bedrock
Meeting Notes Summarization Project with Bedrock
- Setting up our Lambda Function with Bedrock for Content Summarization
- Finishing our Lambda Function for Meeting Summarization
- Creating new API Gateway Endpoint for this Lambda Function
- Invoking our Serverless Meeting Notes Summarization Endpoint
- Analyzing the final results
Using Diffusion Models with Bedrock for Image Creation
- Project Introduction
- Setting up API Gateway Routes (Serverless) for New Generation AI Model Invocation
- Invoking our Stable Diffusion model for Image Generation
- Analyzing our Final Output
Enterprise Use Case 1 (Hands on) : Media and Entertainment Industry
- Introduction – Use Case for Media and Entertainment Industry
- Use Case Description - Media and Entertainment Industry
Amazon Bedrock Image Models
- Stability AI Parameters
- Titan Model Image Generation
- Titan Model Image Editing
Amazon Bedrock AI Agents
- Amazon Bedrock Agent Deep Dive - Basic Workflow
- Detailed Flow of Bedrock Agent - Full Overview
- Hands-on: Build our First Amazon Bedrock Agent - Simple Agent
- Hands-on: Adding Knowledge Base and Testing It
- Hands-on: Action Groups - Adding a Lambda Function
- Amazon Bedrock Agent and Action Groups - Architectural Overview
- Amazon Bedrock Agent Architectural Overview and Animation
- Build-time vs Runtime Operations - Overview
- Amazon Bedrock Agents - Creation Process & Benefits
Serverless E-Learning App with Bedrock Knowledge Base and API GW
- Demo of what we will Build - Amazon Bedrock Knowledge Base, Lambda, API Gateway
- What is Bedrock Knowledge Base - Concept and Architecture
- Creation of Amazon Bedrock Knowledge Base
- Retrieve API and RetrieveAndGenerate API for data retrieval - Concept
- Knowledge Base and AWS Lambda Creation - Part 1
- Knowledge Base and AWS Lambda Creation - Boto3 upgrade - Part 2
- Knowledge Base and AWS Lambda Creation - Part 3
- Knowledge Base - REST API creation and Lambda Integration
Building a Retail Bank Agent using Bedrock Agents and Knowledge Bases
- Demo of what we will Build - Amazon Bedrock Agent
- Amazon Bedrock Agent Use Case - Architecture
- Retail Bank Agent - DynamoDB creation
- Retail Bank Agent - AWS Lambda Creation
- Retail Bank Agent - OpenAPI Specification document creation
- Bedrock Agent creation
- Bedrock Agent Permission to Invoke Lambda Function
- Integration - Bedrock Agent, Lambda and DynamoDB
- Bedrock Agent and KnowledgeBase integration
Building AI Responsibily
- AWS Responsible AI Guiding Principles
- Amazon Bedrock Guardrails
AWS Model Context Protocol (MCP)
- Model Context Protocol (MCP) - Basic Concepts
- Amazon Q CLI Installation (MCP Client)
- Architecture of the Coding Agent with AWS MCP CloudFormation Server
- Build Coding Agent - AWS MCP CloudFormation Server and Amazon Q-CLI (HandsOn)
The Amazon Bedrock AgentCore Runtime
- Introducing the Amazon Bedrock AgentCore Runtime
- Running our AgentCore application locally
- Deploying our Agentic AI app to the serverless cloud with AgentCore
- Running our AgentCore app using the Starter Toolkit
- Running our AgentCore app from a client script
AgentCore Built-In Tools and Importing Bedrock Agents
- Amazon Bedrock AgentCore Tools, and integrating the code interpreter
- Importing Amazon Bedrock Agents + S3 vectors into AgentCore projects
Hours of content
Live Sessions
Software Tools
After completion of this training program you will be able to launch your carrer in the world of AI being certified as Generative AI with Amazon Bedrock Certified Professional.
With Amazon Bedrock Certification in-hand you can boost your profile on Linked, Meta, Twitter & other platform to boost your visibility
- Get your certificate upon successful completion of the course.
- Certificates for each course
- Gen AI
- Vector DB
- Agentic AI
- Lang Chain
- Lang Graph
- AWS Bedrock
- Auto GEN
- Model Context Protocol (MCP)
- AI Governance
- Autonomous Agents
- N8N
- Multimodal RAG's
- MLOps
45% - 100%
Designed to provide guidance on current interview practices, personality development, soft skills enhancement, and HR-related questions
Receive expert assistance from our placement team to craft your resume and optimize your Job Profile. Learn effective strategies to capture the attention of HR professionals and maximize your chances of getting shortlisted.
Engage in mock interview sessions led by our industry experts to receive continuous, detailed feedback along with a customized improvement plan. Our dedicated support will help refine your skills until your desired job in the industry.
Join interactive sessions with industry professionals to understand the key skills companies seek. Practice solving interview question worksheets designed to improve your readiness and boost your chances of success in interviews
Build meaningful relationships with key decision-makers and open doors to exciting job prospects in Product and Service based partner
Your path to job placement starts immediately after you finish the course with guaranteed interview calls
Why should you choose to pursue a Generative AI with Amazon Bedrock Certification course with Success Aimers?
Success Aimers teaching strategy follow a methodology where in we believe in realtime job scenarios that covers industry use-cases & this will help in building the carrer in the field of AI & also delivers training with help of leading industry experts that helps students to confidently answers questions confidently & excel projects as well while working in a real-world
What is the time frame to become competent as a Gen AI (Amazon Bedrock) engineer?
To become a successful Gen AI Engineer required 1-2 years of consistent learning with dedicated 3-4 hours on daily basis.
But with Success Aimers with the help of leading industry experts & specialized trainers you able to achieve that degree of mastery in 6 months or one year or so and it’s because our curriculum & labs we had formed with hands-on projects.
Will skipping a session prevent me from completing the course?
Missing a live session doesn’t impact your training because we have the live recorded session that’s students can refer later.
What industries lead in Gen AI (Amazon Bedrock) implementation?
- Manufacturing
- Financial Services
- Healthcare
- E-commerce
- Telecommunications
- BFSI (Banking, Finance & Insurance)
- Travel Industry
- Â
Does Success Aimers offer corporate training solutions?
At Success Aimers, we have tied up with 500 + Corporate Partners to support their talent development through online training. Our corporate training programme delivers training based on industry use-cases & focused on ever-evolving tech space.
How is the Success Aimers Gen AI (Amazon Bedrock) Certification Course reviewed by learners?
Our Generative AI with Amazon Bedrock Certification Course features a well-designed curriculum frameworks focused on delivering training based on industry needs & aligned on ever-changing evolving needs of today’s workforce due to AI.
Also our training curriculum has been reviewed by alumni & praises the thorough content & real along practical use-cases that we covered during the training. Our program helps working professionals to upgrade their skills & help them grow further in their roles…
Can I attend a demo session before I enroll?
Yes, we offer one-to-one discussion before the training and also schedule one demo session to have a gist of trainer teaching style & also the students have questions around training programme placements & job growth after training completion.
What batch size do you consider for the course?
On an average we keep 5-10 students in a batch to have a interactive session & this way trainer can focus on each individual instead of having a large group.
Do you offer learning content as part of the program?
Students are provided with training content wherein the trainer share the Code Snippets, PPT Materials along with recordings of all the batches
Agentic AI Frameworks and Workflow Automation Course in Gurgaon AI is the future innovation with...
Agentic AI with Lang Chain and Lang Graph Training Course in Gurgaon With high-demand of...
AI Agent and Agentic AI Workflows with N8N Course in Gurgaon Master the future of...
AI Infrastructure Scaling and Governance with MCP Certification Course in Gurgaon AI is the future...
Azure Open AI & Azure AI Foundry Training Course AI is the future innovation with...
Gen AI Course for Software Testing in Gurgaon: Automation and Quality AI is the future...
Generative AI Certification Course in Gurgaon AI is the future innovation with Agentic AI tools...
Generative AI Course for Business Leaders and Senior Management in Gurgaon Kickstart your carrer in...
Generative AI Course for Cyber Security Professionals in Gurgaon AI is the future innovation with...
Generative AI Course for Software Development and Testing in Gurgaon AI is the future innovation...
Generative AI with Vector Databases and RAG Certification Course in Gurgaon AI is the future...
Google Cloud AI Training Course in Gurgaon AI is the future innovation with Agentic AI...
OpenAI ChatGPT Training Course in Gurgaon AI is the future innovation with Agentic AI tools...
