Developing Generative AI Applications on AWS Training

Live Online & Classroom Enterprise Certification Training

Do you want to improve customer experiences and solve complex business problems with generative AI? Learn to build generative AI applications with Developing Generative AI Applications on AWS.

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What is Developing Generative AI Applications on AWS Certification Training about?

This course is designed to introduce generative AI to software developers interested in leveraging large language models without fine-tuning. The course provides an overview of generative AI, planning a generative AI project, getting started with Amazon Bedrock, the foundations of prompt engineering, and the architecture patterns to build generative AI applications using Amazon Bedrock and LangChain.

What are the objectives of Developing Generative AI Applications on AWS Certification Training ?

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 is Developing Generative AI Applications on AWS Certification Training for?

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

What are the prerequisites for Developing Generative AI Applications on AWS Certification Training?

We recommend that attendees of this course have:

AWS Technical Essentials
Intermediate-level proficiency in Python

Available Training Modes

Live Online Training

Classroom Training

2 Days

Course Outline Expand All

Expand All

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

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

Getting Started with Amazon Bedrock

Introduction to Amazon Bedrock

Architecture and use cases

How to use Amazon Bedrock

Demonstration: Setting Up Amazon Bedrock Access and Using Playgrounds

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

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

Model fine-tuning

Securing generative AI applications

Generative AI application architecture

Amazon Bedrock Foundation Models

Introduction to Amazon Bedrock foundation models

Using Amazon Bedrock FMs for inference

Amazon Bedrock methods

Data protection and auditability

Lab: Invoke Amazon Bedrock model for text generation using zero-shot prompt

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

Architecture Patterns

Introduction to architecture patterns

Text summarization

Lab: Using Amazon Titan Text Premier to summarize text of small files

Lab: Summarize long texts with Amazon Titan

Question answering

Lab: Using Amazon Bedrock for question answering

Chatbots

Lab: Build a chatbot

Code generation

Lab: Using Amazon Bedrock Models for Code Generation

LangChain and agents for Amazon Bedrock

Lab: Building conversational applications with the Converse API

Who is the instructor for this training?

The trainer for this Developing Generative AI Applications on AWS Training has extensive experience in this domain, including years of experience training & mentoring professionals.

Developing Generative AI Applications on AWS Certification Training - Certification & Exam

Upon successful completion of the "Developing Generative AI Applications on AWS" course, you become eligible to pursue the> AWS Certified AI Practitioner Certification.

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