{"id":238510,"date":"2026-04-08T15:04:58","date_gmt":"2026-04-08T13:04:58","guid":{"rendered":"https:\/\/www.itta.net\/?post_type=formations&#038;p=238510"},"modified":"2026-04-12T18:59:04","modified_gmt":"2026-04-12T16:59:04","slug":"developing-aws-bedrock-applications-agents","status":"publish","type":"formations","link":"https:\/\/www.itta.net\/en\/trainings\/artificial-intelligence\/ai-development-and-llm\/development-with-llms-and-agents\/developing-with-aws-bedrock-applications-and-agents\/","title":{"rendered":"Developing with AWS Bedrock : Applications and Agents"},"content":{"rendered":"\r\n<p class=\"wp-block-paragraph\">The Developing with AWS Bedrock: Applications and Agents training course covers how to build generative AI solutions within the AWS environment using Amazon Bedrock. It helps participants understand how to interact with models, build assistant-type and chat agent applications, and prepare more advanced scenarios around agent workflows and business integration.<\/p>\r\n\r\n\r\n\r\n<p><strong>An advanced training course to complement your cloud skills and cover the AWS ecosystem<\/strong><\/p>\r\n\r\n\r\n\r\n<p class=\"wp-block-paragraph\">During this training course, participants discover how to use Bedrock in an application-oriented approach, structure model calls, prepare business assistants, understand agent workflow logic and integrate these building blocks into a broader AWS environment.<\/p>\r\n","protected":false},"featured_media":0,"parent":0,"menu_order":0,"template":"","editeurs":[1453],"domaine":[4251,2982,4271,4244,2980],"class_list":["post-238510","formations","type-formations","status-publish","hentry","editeurs-aws-amazon-web-services","domaine-ai-development-and-llm","domaine-artificial-intelligence","domaine-development-with-llms-and-agents","domaine-developpement-ia-et-llm","domaine-intelligence-artificielle"],"acf":{"reference":"AI-06-05","duree_nombre":2,"duree_unite":"jour","prix_virtuel":1400,"prix_presentiel":1500,"prix_blended":"","prix_elearning":"","views":90,"niveau":["Avanc\u00e9"],"role":[],"certifiant":"","pdus":"","lieux":["Gen\u00e8ve","Lausanne"],"formats_dapprentissage":["presentiel","virtuel"],"examen_inclus":"Non certifiant","garanti":[],"financement":["Temptraining"],"description_temptraining":"","description_caf":"","description_title":"Developing with AWS Bedrock : Applications and Agents Training","objectifs":"<ul>\r\n \t<li>Understand the role of Amazon Bedrock in the AWS ecosystem<\/li>\r\n \t<li>Build generative applications and assistants based on Bedrock<\/li>\r\n \t<li>Discover agent and workflow logic in AWS<\/li>\r\n \t<li>Structure business use cases that can be deployed in a cloud environment<\/li>\r\n \t<li>Understand the relationship between Bedrock, SageMaker AI and other AWS components<\/li>\r\n \t<li>Prepare more robust applications and agents for enterprise environments<\/li>\r\n<\/ul>","connaissances":"<ul>\r\n \t<li>Solid foundations in development or cloud architecture<\/li>\r\n \t<li>Prior experience with AWS is recommended<\/li>\r\n \t<li>A general understanding of generative AI is a plus<\/li>\r\n<\/ul>","profils_participants":"<ul>\r\n \t<li>Developers<\/li>\r\n \t<li>Cloud architects<\/li>\r\n \t<li>DevOps \/ cloud engineering professionals<\/li>\r\n \t<li>Technical project managers<\/li>\r\n \t<li>Anyone with existing AWS knowledge or solid cloud foundations looking to develop generative applications with Bedrock<\/li>\r\n<\/ul>","examen":"","documentation":"<ul>\n \t<li>Support de cours num\u00e9rique inclus<\/li>\n<\/ul>","lab__exercices":"<ul>\n \t<li>This course includes exercises on structuring Bedrock API calls, building simple generative applications, analyzing agent use cases and designing application architectures in the AWS ecosystem.<\/li>\n<\/ul>","contenu_cours":"<strong>Module 1: Understanding Amazon Bedrock and Its Positioning<\/strong>\r\n<ul>\r\n \t<li>Introduction to Bedrock<\/li>\r\n \t<li>Positioning within the AWS ecosystem<\/li>\r\n \t<li>Difference between model platform, application and agent<\/li>\r\n \t<li>Use cases for generation, assistance and automation<\/li>\r\n<\/ul>\r\n<strong>Module 2: First Developments with Bedrock<\/strong>\r\n<ul>\r\n \t<li>Authentication and access logic<\/li>\r\n \t<li>Structure of model calls<\/li>\r\n \t<li>Managing generation parameters<\/li>\r\n \t<li>Structuring inputs and outputs<\/li>\r\n \t<li>Building a first application interaction<\/li>\r\n<\/ul>\r\n<strong>Module 3: Building Generative Applications<\/strong>\r\n<ul>\r\n \t<li>Business assistant<\/li>\r\n \t<li>Simple Q&A<\/li>\r\n \t<li>Content generation<\/li>\r\n \t<li>Analysis and summarization<\/li>\r\n \t<li>Preparing reusable application logic<\/li>\r\n<\/ul>\r\n<strong>Module 4: Understanding Agents and Workflows<\/strong>\r\n<ul>\r\n \t<li>Difference between a simple generative application and an agent<\/li>\r\n \t<li>Role of agent workflows<\/li>\r\n \t<li>Step coordination<\/li>\r\n \t<li>Connecting to data or processes<\/li>\r\n \t<li>Identifying relevant use cases<\/li>\r\n<\/ul>\r\n<strong>Module 5: Integrating Bedrock into a Broader AWS Environment<\/strong>\r\n<ul>\r\n \t<li>Integration with SageMaker AI<\/li>\r\n \t<li>Connecting to AWS services<\/li>\r\n \t<li>Preparing an enterprise architecture<\/li>\r\n \t<li>Considerations on security, costs and operations<\/li>\r\n<\/ul>\r\n<strong>Module 6: Best Practices and Caution<\/strong>\r\n<ul>\r\n \t<li>Output reliability<\/li>\r\n \t<li>Human validation<\/li>\r\n \t<li>Usage costs<\/li>\r\n \t<li>Data protection<\/li>\r\n \t<li>Choosing the right use cases and avoiding unnecessary complexity<\/li>\r\n<\/ul>","cours_recommandes":[238507,238509,238511,238506,238512],"infos_additionnelles":"<h3>AWS Bedrock, multi-model platform for enterprise AI<\/h3>\r\n<p>AWS Bedrock is a managed platform that provides access to the most performant AI models on the market through a unified API. Claude, LLaMA, Mistral, Stable Diffusion and Amazon Titan models are available without managing infrastructure, which considerably simplifies the development and deployment of AI applications.<\/p>\r\n<p>For companies already using AWS, Bedrock offers native integration with the full range of cloud services, which accelerates development and strengthens security.<\/p>\r\n\r\n<h3>The multi-model approach of Bedrock<\/h3>\r\n<p>One of the major advantages of Bedrock is the ability to compare and combine different models through a unified API. This approach allows you to choose the most suitable model for each task, reduce dependency on a single provider and benefit from each provider's advances as soon as they become available.<\/p>\r\n<p>Model Evaluation allows you to objectively compare model performance on specific test sets, facilitating decision-making on the choice of model for each use case.<\/p>\r\n\r\n<h3>Building AI agents with Bedrock<\/h3>\r\n<p>Bedrock Agents enables the creation of AI agents capable of executing complex tasks autonomously. Agents can orchestrate API calls, query databases, execute workflows and make context-based decisions. Defining actions and knowledge bases allows you to customize agent behavior.<\/p>\r\n<p>Bedrock guardrails add a security layer by setting clear boundaries on what the agent can and cannot do, an essential aspect for enterprise deployments.<\/p>\r\n\r\n<h3>RAG and Knowledge Bases on Bedrock<\/h3>\r\n<p>Bedrock Knowledge Bases simplifies RAG implementation by providing a managed indexing and semantic search service. Documents can be loaded from S3, and Bedrock automatically handles chunking, vector indexing and retrieval. This approach considerably reduces the complexity of RAG implementation.<\/p>\r\n<p>Integration with vector databases like OpenSearch and Pinecone provides additional options for use cases requiring specific performance or features.<\/p>\r\n\r\n<h3>Bedrock for enterprise applications in Switzerland<\/h3>\r\n<p>The AWS region in Zurich ensures data localization in Switzerland, a prerequisite for many companies subject to strict regulations. AWS compliance certifications cover the most demanding standards in the Swiss market.<\/p>\r\n<p>ITTA trains developers and cloud architects from French-speaking Switzerland on AWS Bedrock in Geneva and Lausanne, with a hands-on approach focused on building production AI applications.<\/p>\r\n\r\n\r\n<h3>AI development in Switzerland, a fast-growing market<\/h3>\r\n<p>The Swiss AI application development market is experiencing sustained growth. Technology companies, startups, financial institutions and international organizations are actively seeking developers capable of building intelligent solutions. AI development skills with Python, language model APIs and frameworks like LangChain are among the most in-demand skills on the job market in French-speaking Switzerland.<\/p>\r\n<p>The presence of AWS, Google and Azure cloud regions in Switzerland facilitates the development and deployment of AI applications that comply with local data protection requirements. Developers trained on these platforms benefit from direct access to the necessary infrastructure and active technical communities in French-speaking Switzerland. This dynamic creates a favorable ecosystem for innovation and career development in the AI field.<\/p>\r\n\r\n\r\n<p>Developers trained in AWS Bedrock master a platform that offers unique flexibility through its multi-model approach. They are able to build robust applications that benefit from the security and scalability of AWS infrastructure. This expertise is particularly valued in organizations that have already invested in the AWS ecosystem and wish to extend their capabilities with artificial intelligence.<\/p>\r\n\r\n<p><strong>What is the difference between Bedrock and SageMaker?<\/strong><\/p>\r\n<p>Bedrock provides access to pre-trained models via API without managing infrastructure. SageMaker allows you to train, customize and deploy your own models. The two services are complementary and can be combined.<\/p>\r\n\r\n<p><strong>Is Bedrock more secure than direct provider APIs?<\/strong><\/p>\r\n<p>Bedrock adds an AWS security layer with IAM access control, native encryption and the guarantee that data does not leave the AWS infrastructure. These guarantees strengthen the security posture compared to direct APIs.<\/p>\r\n\r\n<p><strong>Can models be fine-tuned on Bedrock?<\/strong><\/p>\r\n<p>Yes, Bedrock supports fine-tuning of certain models with proprietary data. The customized model remains private and benefits from the same security guarantees as base models.<\/p>\r\n\r\n<p><strong>Are Bedrock guardrails sufficient for regulated use?<\/strong><\/p>\r\n<p>Bedrock guardrails provide an effective first line of defense. For highly regulated environments, they should be complemented by application-level and organizational controls. The training covers the design of multi-layered security systems.<\/p>\r\n\r\n<p><strong>What budget should be planned for Bedrock in production?<\/strong><\/p>\r\n<p>Bedrock is billed per use based on the number of tokens processed. Rates vary by model. Provisioned Throughput offers reduced rates for high volumes. The training covers cost optimization strategies.<\/p>","inclus_dans_ce_cours_virtuel":"<ul>\n \t<li>Training provided by a domain expert<\/li>\n \t<li>Digital documentation and support materials<\/li>\n \t<li>Achievement badge<\/li>\n<\/ul>","inclus_dans_ce_cours_presentiel":"<ul>\n \t<li>Training provided by a domain expert<\/li>\n \t<li>Digital documentation and support materials<\/li>\n \t<li>Achievement badge<\/li>\n<\/ul>","inclus_dans_ce_cours_blended":"","inclus_dans_ce_cours_elearning":"","inclus_dans_ce_cours_surmesure":""},"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v27.5 (Yoast SEO v27.5) - https:\/\/yoast.com\/product\/yoast-seo-premium-wordpress\/ -->\n<title>AWS Bedrock Applications and Agents Training<\/title>\n<meta name=\"description\" content=\"AWS Bedrock training in Geneva and Lausanne. 2 days to develop generative applications and AI agents with Amazon Bedrock. Hands-on labs. 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