Cloud Wizard - Developing Generative AI Applications on AWS (AIP-C01)

Delivered by Cloud Wizard Consulting - AWS Advanced Training Partner

Cloud Wizard Consulting has been delivering AWS training for 12 years as an Advanced Training Partner on the AWS Partner Network. All instructors hold every AWS certification, bringing deep production experience to the classroom. This 2-day course equips software developers with the skills to build, deploy, and secure generative AI applications using Amazon Bedrock and LangChain.

After completing this course, participants will be able to:

• Architect production-ready GenAI solutions - Design and implement generative AI applications using RAG, embeddings, and foundation models that address real business needs such as automating customer support workflows or building internal knowledge assistants.
• Accelerate time-to-prototype - Use Amazon Bedrock APIs and LangChain integrations to rapidly build chatbots, text summarization tools, question-answering systems, and code generation assistants.
• Apply prompt engineering for reliable outputs - Master zero-shot, few-shot, and advanced prompting techniques to get consistent, high-quality results from large language models.
• Mitigate risk with responsible AI practices - Identify prompt misuse, bias, and security vulnerabilities, then apply mitigation strategies aligned with AWS best practices.
• Prepare for AWS certification - Build knowledge and hands-on skills relevant to the AWS Certified AI Practitioner (AIP-C01) exam.

Participants work through a scenario where a financial services team needs to build a RAG-powered application that ingests regulatory documents, answers compliance questions in natural language, and summarizes policy changes for analysts - demonstrating how generative AI patterns apply to real enterprise workflows.

Module 1: Introduction to Generative AI - Machine learning overview, generative AI fundamentals, business use cases, risks and benefits.

Module 2: Planning a Generative AI Project - Generative AI concepts, project planning methodology, risk assessment and mitigation.

Module 3: Getting Started with Amazon Bedrock - Amazon Bedrock overview, architecture and use cases, access and playground demonstrations.

Module 4: Foundations of Prompt Engineering - Foundation models, prompt engineering fundamentals, zero-shot and few-shot prompting, model-specific prompting, bias mitigation demonstrations.

Module 5: Amazon Bedrock Application Components - Application architecture, foundation models and embeddings, datasets, RAG, fine-tuning, and security.

Module 6: Amazon Bedrock Foundation Models - Inference, Bedrock APIs and methods, data protection and auditing, text generation demonstration.

Module 7: LangChain Integration - LangChain fundamentals, prompt templates, chains, retrievers, embeddings, memory, agents, and context-aware prompting demonstration.

Module 8: Architecture Patterns - Text summarization, question answering, conversational AI and chatbots, code generation, LangChain agents with Amazon Bedrock.

The course includes practical demonstrations and hands-on labs covering Amazon Bedrock, prompt engineering, embeddings, RAG, LangChain integration, text generation, summarization, chatbots, question answering, and code generation. Participants build working applications during the course.

Lab environments are provisioned in isolated AWS accounts dedicated to each training session. Participant information is handled in accordance with data protection best practices.

• Software developers building generative AI applications with large language models
• Professionals preparing for the AWS Certified AI Practitioner (AIF-C01) certification

• AWS Technical Essentials or equivalent AWS knowledge
• Intermediate proficiency in Python