Generative AI on AWS ki training | 17th जनवरी 10:30am Introductory Class | Agentic AI | AWS скачать в хорошем качестве

Generative AI on AWS ki training | 17th जनवरी 10:30am Introductory Class | Agentic AI | AWS

Generative AI on AWS - Instructor led training program Registration Link: https://forms.gle/AWewsee9vNF5gjaT7 Learning Path Structure: Stage 1 L200 - 6 Classes - 15 Hours Stage 2 L300 - 17 Classes - 42.5 Hours Each class is 2.5 hours and on weekends (SAT & SUN 10:30am to 01:00pm). Fee Structure & Registration: Stage 1 (L200): ₹10,000/- Stage 2 (L300): ₹25,000/- Combined L200 + L300: ₹30,000/- (special bundled pricing) Early Bird Offer: Registration & Payment on or before 20th January 2026 can avail a discount of 20% across all training fees Important Dates: Introductory Session: 17th January 2026 (Complimentary) Stage 1 classes starts on: 25th January 2026 Refund Policy: 100% fee refund, no questions asked, if you are not satisfied with the training L200 – Detailed Day-wise Agenda (6 Classes) Class 1: Generative AI & Agentic AI Fundamentals • Evolution from Traditional AI → ML → Generative AI • What makes AI Agentic • LLMs, embeddings, tools, memory – conceptual overview Class 2: Foundation Models & LLM Ecosystem on AWS • Overview of Foundation Models • Amazon Bedrock – purpose and positioning • Model families (text, chat, embeddings, multimodal) Class 3: Core AWS Building Blocks for GenAI Systems • Data layer: S3, RDS, DynamoDB, OpenSearch • Compute layer: Lambda, ECS, EC2 • Integration layer: API Gateway, EventBridge, Step Functions Class 4: Agentic AI – Conceptual Architecture • What is an AI Agent • Memory types: short-term vs long-term • Single-agent vs multi-agent systems Class 5: Enterprise Use Cases for Agentic AI • Enterprise copilots • Autonomous workflow orchestration Class 6: Governance, Security & Responsible AI • Data privacy & isolation in Bedrock • Guardrails and policy enforcement L300 – Detailed Day-wise Agenda (17 Classes) Class 1: Amazon Bedrock – Overview & Positioning • Amazon Bedrock service overview and value proposition • Where Bedrock fits in AWS GenAI ecosystem • Choosing the right model for use cases (cost, latency, accuracy) • Hands-on: Simple model invocation Class 2: Prompt Engineering – Fundamentals • What is prompting and why it matters • Zero-shot, one-shot, few-shot prompting • Prompt structure and best practices • Hands-on: Foundational prompt design lab Class 3: Prompt Engineering – Advanced Patterns • Chain-of-thought and reasoning prompts • ReAct and tool-aware prompting • Reducing hallucinations via prompting • Hands-on: Advanced prompt optimization lab Class 4: Embeddings & Vector Search • Chunking & indexing strategies • Vector similarity search • Hands-on: Generate embeddings using Bedrock Class 5: Retrieval-Augmented Generation (RAG) • RAG reference architectures on AWS • OpenSearch-based vector stores • Hands-on: Build a basic RAG pipeline Class 6: Advanced RAG Patterns • Hybrid search • Re-ranking strategies • Hands-on: Optimize retrieval accuracy Class 7: Agentic AI Design Patterns • Planner–Executor–Critic pattern • Tool-based agents • Stateful vs stateless agents Class 8: Amazon Bedrock Agent Core – Architecture • Agent Core concepts and lifecycle • Knowledge bases and memory handling • Agent lifecycle Class 9: Hands-on – Build Your First Agent using Agent Core • Create an agent using Bedrock Agent Core • Integrate Lambda-based tools • Create Bedrock Agent Class 10: Multi-Agent Systems Class 11: Enterprise Integration Patterns for Agentic AI • Integrating agents with enterprise systems (ERP, MES, CRM, ITSM) • Hands-on: Integrate agent with a real enterprise-style REST API Class 12: Model Adaptation Strategies (Conceptual) Class 13: Hands-on Lab – End-to-End Enterprise Agent Build Class 14 & 15: Real-life Enterprise Use Case Implementation (Extended Hands-on) • Designing an Agentic AI solution with clear business objectives • Coordinating multiple agents (planner, executor, validator) • Implementing memory management (short-term vs long-term memory) Class 16: Hackathon Kick-off – Real-world Enterprise Use Case Class 17: Hackathon Demo Day & Training Closure Terms & Conditions • While the training will be delivered broadly as per the published agenda and schedule, the timing, sequence of sessions, and session topics may be subject to change based on practical considerations. • This is a personal training program and not a registered training institute. Hence, there is no obligation or liability on the trainer to provide a completion certificate. • Participants are required to create and use their own individual AWS accounts for hands-on practice. The trainer is not liable for any AWS service usage costs incurred during the training. • The trainer is not promoting AWS services. However, since the trainer’s professional expertise is centered around AWS, the training content and examples are designed using AWS-native services for practical demonstration.