Developing Generative AI Applications on AWS (DGAIA)

 

Course Overview

This course is designed to introduce generative artificial intelligence (AI) to software developers interested in using large language models (LLMs) 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.

Who should attend

This course is intended for:

  • Software developers interested in using LLMs without fine-tuning

Prerequisites

We recommend that attendees of this course have:

Course Objectives

In this course, you will learn to:

  • 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 foundation models (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 an 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 LLMs, prompt templates, chains, chat models, text embeddings models, document loaders, retrievers, and Agents for Amazon Bedrock
  • Describe architecture patterns that you can implement with Amazon Bedrock for building generative AI applications
  • Apply the concepts to build and test sample use cases that use the various Amazon Bedrock models, LangChain, and the Retrieval Augmented Generation (RAG) approach

Course Content

  • Introduction to Generative AI – Art of the Possible
  • Planning a Generative AI Project
  • Getting Started with Amazon Bedrock
  • Foundations of Prompt Engineering
  • Amazon Bedrock Application Components
  • Amazon Bedrock Foundation Models
  • LangChain
  • Architecture Patterns

Prices & Delivery methods

Online training
Modality: L

Duration 2 days

Price
  • Poland: 4,000.— PLN
Dates and Booking
Enquire a date
Classroom training
Modality: C

Duration 2 days

Price
  • Poland: 4,000.— PLN
Dates and Booking
Enquire a date

Schedule

English

Time zone: Central European Time (CET)   ±1 hour

Online training Time zone: Greenwich Mean Time (GMT)
Online training Time zone: British Summer Time (BST)
Online training Time zone: British Summer Time (BST)
Online training Time zone: Greenwich Mean Time (GMT)

6 hours difference

Online training Time zone: Eastern Standard Time (EST)
Online training Time zone: Eastern Standard Time (EST)
Online training Time zone: Eastern Daylight Time (EDT)
Online training Time zone: Eastern Daylight Time (EDT)
Online training Time zone: Eastern Standard Time (EST)
Online training Time zone: Eastern Standard Time (EST)

7 hours difference

Online training Time zone: Central Daylight Time (CDT)
Online training Time zone: Central Daylight Time (CDT)
Online training Time zone: Central Daylight Time (CDT)
Online training Time zone: Central Daylight Time (CDT)

9 hours difference

Online training Time zone: Pacific Daylight Time (PDT)
Online training Time zone: Pacific Daylight Time (PDT)
Instructor-led Online Training:   This is an Instructor-Led Online course
This is a FLEX course, which is delivered both virtually and in the classroom.

Europe

Germany

 Berlin This is a FLEX course.   Time zone: Central European Time (CET) Enroll:
for online training
for classroom training
München This is a FLEX course.   Time zone: Central European Time (CET) Enroll:
for online training
for classroom training
Frankfurt This is a FLEX course.   Time zone: Central European Summer Time (CEST) Enroll:
for online training
for classroom training
Hamburg This is a FLEX course.   Time zone: Central European Summer Time (CEST) Enroll:
for online training
for classroom training
Berlin This is a FLEX course.   Time zone: Central European Summer Time (CEST) Enroll:
for online training
for classroom training
Frankfurt This is a FLEX course.   Time zone: Central European Time (CET) Enroll:
for online training
for classroom training

Switzerland

 Zürich This is a FLEX course.   Time zone: Central European Time (CET) Enroll:
for online training
for classroom training
Zürich This is a FLEX course.   Time zone: Central European Time (CET) Enroll:
for online training
for classroom training
Zürich This is a FLEX course.   Time zone: Central European Summer Time (CEST) Enroll:
for online training
for classroom training
Zürich This is a FLEX course.   Time zone: Central European Summer Time (CEST) Enroll:
for online training
for classroom training
Zürich This is a FLEX course.   Time zone: Central European Summer Time (CEST) Enroll:
for online training
for classroom training
Zürich This is a FLEX course.   Time zone: Central European Time (CET) Enroll:
for online training
for classroom training
This is a FLEX course, which is delivered both virtually and in the classroom.