AWS Role - Based

AWS-DEVGENAI : Developing Generative AI Applications on AWS

Overview

In this 2-day course an expert instructor will guide you in your developer role with Python experience through the basics, benefit, associated terminology of generative AI. You will learn the steps to planning a generative AI project, the foundations of prompt engineering, and more to develop generative AI applications with AWS services. By the end of the course, you will develop the skills needed to build applications that can generate and summarize text, answer questions, and interact with users using a chatbot interface.

AWS generative AI certification is designed to test the competency of a candidate in both theoretical knowledge and practical application of Generative AI on Amazon Bedrock. It assesses a candidate in designing, deploying, and optimisation of the Generative AI applications across multiple environments. You will get questions on AWS generative AI courses, related to actual projects. This exam focuses explicitly on mastery in applying AI models on the AWS framework for candidates desiring certification and prepares them for real-world deployments, giving them deep insight into how to use AWS Bedrock effectively.

What You'll Learn

Describe generative AI and how it aligns to machine learning
Define the importance of generative AI and explain its potential risks and benefits
Identify business value from generative AI use cases
Discuss the technical foundations and key terminology for generative AI
Explain the steps for planning a generative AI project
Identify some of the risks and mitigations when using generative AI
Understand how Amazon Bedrock works
Familiarize yourself with basic concepts of Amazon Bedrock
Recognize the benefits of Amazon Bedrock
List typical use cases for Amazon Bedrock
Describe the typical architecture associated with an Amazon Bedrock solution
Understand the cost structure of Amazon Bedrock
Implement a demonstration of Amazon Bedrock in the AWS Management Console
Define prompt engineering and apply general best practices when interacting with FMs
Identify the basic types of prompt techniques, including zero-shot and few-shot learning
Apply advanced prompt techniques when necessary for your use case
Identify which prompt-techniques are best-suited for specific models
Identify potential prompt misuses
Analyze potential bias in FM responses and design prompts that mitigate that bias
Identify the components of a generative AI application and how to customize a foundation model (FM)
Describe Amazon Bedrock foundation models, inference parameters, and key Amazon Bedrock APIs
Identify Amazon Web Services (AWS) offerings that help with monitoring, securing, and governing your Amazon Bedrock applications
Describe how to integrate LangChain with large language models (LLMs), prompt templates, chains, chat models, text embeddings models, document loaders, retrievers, and Agents for Amazon Bedrock
Describe architecture patterns that can be implemented with Amazon Bedrock for building generative AI applications
Apply the concepts to build and test sample use cases that leverage the various Amazon Bedrock models, LangChain, and the Retrieval Augmented Generation (RAG) approach

Who Should Attend

This course is intended for:

Software developers interested in leveraging large language models without fine-tuning

Prerequisites

We recommend that attendees of this course have:

AWS Technical Essentials
Intermediate-level proficiency in Python

Learning Journey

Want to boost your career in AWS? Click on the roles below to see the learning pathways, specially designed to give you the skills to succeed.

Coming Soon...

Day 1

Module 1: Introduction to Generative AI - Art of the Possible

Overview of ML
Basics of generative AI
Generative AI use cases
Generative AI in practice
Risks and benefits

Module 2: Planning a Generative AI Project

Generative AI fundamentals
Generative AI in practice
Generative AI context
Steps in planning a generative AI project
Risks and mitigation

Module 3: Getting Started with Amazon Bedrock

Introduction to Amazon Bedrock
Architecture and use cases
How to use Amazon Bedrock
Demonstration: Setting Up Bedrock Access and Using Playgrounds

Module 4: Foundations of Prompt Engineering

Basics of foundation models
Fundamentals of prompt engineering
Basic prompt techniques
Advanced prompt techniques
Demonstration: Fine-Tuning a Basic Text Prompt
Model-specific prompt techniques
Addressing prompt misuses
Mitigating bias
Demonstration: Image Bias-Mitigation

Day 2

Module 5: Amazon Bedrock Application Components

Applications and use cases
Overview of generative AI application components
Foundation models and the FM interface
Working with datasets and embeddings
Demonstration: Word Embeddings
Additional application components
RAG
Model fine-tuning
Securing generative AI applications
Generative AI application architecture

Module 6: Amazon Bedrock Foundation Models

Introduction to Amazon Bedrock foundation models
Using Amazon Bedrock FMs for inference
Amazon Bedrock methods
Data protection and auditability
Demonstration: Invoke Bedrock Model for Text Generation Using Zero-Shot Prompt

Module 7: LangChain

Optimizing LLM performance
Integrating AWS and LangChain
Using models with LangChain
Constructing prompts
Structuring documents with indexes
Storing and retrieving data with memory
Using chains to sequence components
Managing external resources with LangChain agents
Demonstration: Bedrock with LangChain Using a Prompt that Includes Context

Module 8: Architecture Patterns

Introduction to architecture patterns
Text summarization
Demonstration: Text Summarization of Small Files with Anthropic Claude
Demonstration: Abstractive Text Summarization with Amazon Titan Using LangChain
Question answering
Demonstration: Using Amazon Bedrock for Question Answering
Chatbots
Demonstration: Conversational Interface – Chatbot with AI21 LLM
Code generation
Demonstration: Using Amazon Bedrock Models for Code Generation
LangChain and agents for Amazon Bedrock
Demonstration: Integrating Amazon Bedrock Models with LangChain Agents

Frequently Asked Questions (FAQs)

Keep Exploring

Course Curriculum

Training Schedule

Exam & Certification

Frequently Asked Questions

Improve yourself and your career by taking this course.

More Courses By AWS

Browse All Courses

Ready to Take Your Business from Great to Awesome?

Level-up by partnering with Trainocate. Get in touch today.

Name

Phone

I'm inquiring for

Myself Company

Enter Your Message

By submitting this form, you consent to Trainocate processing your data to respond to your inquiry and provide you with relevant information about our training programs, including occasional emails with the latest news, exclusive events, and special offers.

You can unsubscribe from our marketing emails at any time. Our data handling practices are in accordance with our Privacy Policy.