Showing posts with label security. Show all posts
Showing posts with label security. Show all posts

Monday, 4 August 2025

Claude with Amazon Bedrock

 




Claude with Amazon Bedrock

Introduction

Amazon Bedrock provides a powerful platform for building and scaling generative AI applications in the cloud—without needing to manage infrastructure or fine-tune models. Through its integration with Anthropic’s Claude, Bedrock enables organizations to seamlessly access Claude’s advanced language capabilities within AWS’s secure and enterprise-ready ecosystem. This partnership allows developers to leverage Claude for chatbots, summarization, coding, and more—directly through the tools and environments they already use on AWS.


What is Amazon Bedrock?

Amazon Bedrock is a fully managed service that allows users to build and deploy generative AI applications using foundation models from leading AI providers—including Anthropic, AI21 Labs, Meta, Cohere, Stability AI, and more. It abstracts away the complexity of provisioning GPUs or hosting LLMs, letting developers focus entirely on application logic. With Claude available through Bedrock, developers can invoke Claude’s models with standard APIs, while benefiting from AWS’s native security, compliance, and scalability.

Benefits of Using Claude via Bedrock

Accessing Claude through Bedrock offers several unique advantages. First, it allows developers to integrate generative AI directly into their AWS-based applications, without having to leave the cloud environment or manage separate accounts with model providers. It also simplifies governance through AWS Identity and Access Management (IAM), provides seamless billing through existing AWS accounts, and supports enterprise-grade observability and compliance features.

How It Works

Using Claude in Bedrock involves sending prompts to the model via the Bedrock API or through the AWS SDKs. Bedrock handles all the model hosting and versioning behind the scenes. Developers can use Claude for tasks like content creation, document analysis, question answering, and software development. The model can be accessed from within AWS Lambda, SageMaker, Step Functions, or any other compute environment within the AWS ecosystem, making it highly flexible for both real-time and batch workflows.

Use Cases in AWS Workflows

Claude on Bedrock is being used across industries to automate and enhance a wide variety of tasks. In customer service, companies use Claude to power intelligent virtual agents and summarize support tickets. In finance, it assists with analyzing regulatory documents and generating reports. Developers integrate Claude into CI/CD pipelines for writing deployment scripts or reviewing code. The synergy between Claude’s language skills and AWS’s infrastructure enables highly scalable, cost-efficient AI solutions.

Security and Data Privacy

One of the most important benefits of using Claude through Bedrock is the security framework it operates within. AWS ensures that all data is encrypted in transit and at rest. Organizations can apply fine-grained access controls to who can use models and for what purpose. Importantly, Claude via Bedrock does not train on customer data, which ensures that inputs remain private and protected—critical for industries like healthcare, government, and finance.

Join Free: Claude with Amazon Bedrock

Conclusion

Claude’s integration with Amazon Bedrock makes it easier than ever to bring state-of-the-art language capabilities into enterprise environments. By combining Claude’s strength in natural language understanding and generation with AWS’s robust cloud services, businesses can build powerful, scalable, and secure AI applications without managing infrastructure. Whether you’re looking to automate workflows, enhance customer experiences, or streamline internal processes, Claude on Bedrock offers a trusted path to getting there.

Tuesday, 20 February 2024

Enterprise and Infrastructure Security

 


Build your subject-matter expertise

This course is part of the Introduction to Cyber Security Specialization

When you enroll in this course, you'll also be enrolled in this Specialization.

Learn new concepts from industry experts

Gain a foundational understanding of a subject or tool

Develop job-relevant skills with hands-on projects

Earn a shareable career certificate

Join Free: Enterprise and Infrastructure Security

There are 4 modules in this course

This course introduces a series of advanced and current topics in cyber security, many of which are especially relevant in modern enterprise and infrastructure settings. The basics of enterprise compliance frameworks are provided with introduction to NIST and PCI. Hybrid cloud architectures are shown to provide an opportunity to fix many of the security weaknesses in modern perimeter local area networks.

Emerging security issues in blockchain, blinding algorithms, Internet of Things (IoT), and critical infrastructure protection are also described for learners in the context of cyber risk. Mobile security and cloud security hyper-resilience approaches are also introduced. The course completes with some practical advice for learners on how to plan careers in cyber security.

Tuesday, 26 December 2023

Data Privacy Fundamentals

 


What you'll learn

Identify foundational understanding of digital age privacy concepts and theories

Identify privacy implications of modern digital technology

Identify the rules and frameworks for data privacy in the age of technology

Join Free:Data Privacy Fundamentals

There are 3 modules in this course

This course is designed to introduce data privacy to a wide audience and help each participant see how data privacy has evolved as a compelling concern to public and private organizations as well as individuals. In this course, you will hear from legal and technical experts and practitioners who encounter data privacy issues daily. This course will review theories of data privacy as well as data privacy in the context of social media and artificial intelligence. It will also explore data privacy issues in journalism, surveillance, new technologies like facial recognition and biometrics. Completion of the course will enable the participant to be eligible for CPE credit.


Industrial IoT Markets and Security

 


What you'll learn

What Industry 4.0 is and what factors have enabled the IIoT.

Key skills to develop to be employed in the IIoT space.

What platforms are, and also market information on Software and Services.

What the top application areas are (examples include manufacturing and oil & gas).

Join Free:Industrial IoT Markets and Security

There are 5 modules in this course

This course can also be taken for academic credit as ECEA 5385, part of CU Boulder’s Master of Science in Electrical Engineering degree.

Developing tomorrow's industrial infrastructure is a significant challenge. This course goes beyond the hype of consumer IoT to emphasize a much greater space for potential embedded system applications and growth: The Industrial Internet of Things (IIoT), also known as Industry 4.0. Cisco’s CEO stated: “IoT overall is a $19 Trillion market. IIoT is a significant subset including digital oilfield, advanced manufacturing, power grid automation, and smart cities”.

This is part 1 of the specialization. The primary objective of this specialization is to closely examine emerging markets, technology trends, applications and skills required by engineering students, or working engineers, exploring career opportunities in the IIoT space. The structure of the course is intentionally wide and shallow: We will cover many topics, but will not go extremely deep into any one topic area, thereby providing a broad overview of the immense landscape of IIoT. There is one exception: We will study security in some depth as this is the most important topic for all "Internet of Things" product development.

In this course students will learn :
  * What Industry 4.0 is and what factors have enabled the IIoT
  * Key skills to develop to be employed in the IIoT space
  * What platforms are, and also market information on Software and Services
  * What the top application areas are (examples include manufacturing and oil & gas)
  * What the top operating systems are that are used in IIoT deployments
  * About networking and wireless communication protocols used in IIoT deployments
  * About computer security; encryption techniques and secure methods for insuring data integrity and authentication

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