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Cloud Native Twelve-Factor and Fifteen-Factor Applications
.MP4, AVC, 1280×720, 30 fps | English, AAC, 2 Ch | 57m | 296 MB
Instructor: Frank P Moley III​

The twelve-factor and fifteen-factor methodology helps you build more effective, software-as-a-service apps. It allows for automation, continuous deployment, easy onboarding, and portability between execution environments. By leveraging these methodologies, you can also achieve straightforward deployment on numerous cloud platforms in any language, as well as high scalability without needing to change your tooling, architecture, or team.

In this course, join instructor Frank Moley as he walks through the fifteen most important factors for software developers looking to build agile, scalable, and resilient web apps. Along the way, Frank explains exactly how each factor applies to cloud-native development, sharing key pointers, pro tips, and practical strategies for making a legacy application twelve- or fifteen-factor compatible.

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Cloud Data, Platform and Applications Security
Published 08/2025
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 5h 20m | Size: 1.35 GB​

This comprehensive cloud security course provides expert training to protect every layer of the cloud environment. You will learn how to secure cloud data throughout its entire lifecycle-from creation and storage to usage, sharing, archiving, and destruction. Gain practical skills in data classification, data obfuscation, and key and certificate management to enforce strong data security policies and maintain compliance.

You will explore cloud platform and infrastructure security, including designing secure physical data centers, network architectures, virtualization, cloud compute and storage components, and management planes. Learn to identify vulnerabilities, mitigate risks, and develop effective business continuity and disaster recovery plans to ensure resilient cloud operations.

The course also covers essential cloud application security topics such as secure software development lifecycles (SDLC), threat modeling, OWASP API security, secure coding techniques, and managing third-party software risks. You will master cloud identity and access management (IAM) solutions such as federated identity, single sign-on (SSO), multi-factor authentication (MFA), cloud access security brokers (CASBs), and secrets management to safeguard access and protect sensitive resources.

About the Instructors

Michael J Shannon began his IT career when he transitioned from recording studio engineer to network technician for a major telecommunications company in the early 1990’s. He soon began to focus on security and was one of the first 10 people to attain the HIPAA Certified Security Specialist. Throughout his 30 years in IT, he has worked as an employee, contractor, and consultant for several companies including Platinum Technologies, Fujitsu, IBM, State Farm, MindSharp, Thomson, Pearson, and Skillsoft among others. Mr. Shannon has authored several books, training manuals, blog articles, and CBT modules over the years as well. He has attained the CISSP, ITIL 4 Managing Professional, CCNP Security, Palo Alto PCNSE7 and OpenFAIR certifications in the security field as well as several cloud-based certifications for AWS, Google Cloud, and Azure. His hobbies are playing guitar, songwriting, and golf. He resides with his wife in Abilene Texas.

Free Download Cloud Computing Fundamentals for Beginners (2026)
Published 4/2026
Created by Vedika Singh
MP4 | Video: h264, 1920×1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All Levels | Genre: eLearning | Language: English | Duration: 31 Lectures ( 4h 47m ) | Size: 1.35 GB

Learn Cloud Computing Fundamentals, Architecture, Networking, Virtualization & Service Models
What you’ll learn
✓ Understand the fundamentals of cloud computing and how cloud systems work
✓ Explain cloud architecture, networking, and virtualization concepts
✓ Identify different types of cloud computing and service models (IaaS, PaaS, SaaS)
✓ Understand cloud migration and its business impact
✓ Describe cloud characteristics, components, advantages, and challenges
✓ Understand cloud layers and reference models
✓ Gain knowledge of popular cloud platforms and their use cases
Requirements
● No prior knowledge of cloud computing is required
● Basic understanding of computers and the internet is helpful
● Willingness to learn cloud computing concepts from scratch
Description
Cloud Computing Fundamentals | Basics of Cloud Computing
Learn the fundamentals of cloud computing and essential cloud computing basics and build a strong understanding of how modern cloud systems work. This beginner-friendly course covers essential cloud computing basics, helping you understand how data is stored, processed, and managed in cloud environments.
What You Will Learn
• Introduction to Cloud Computing
• Characteristics, Components, Advantages, and Challenges
• Cloud Migration and Its Business Impact
• Cloud Networking and Architecture
• Cloud Layers and Reference Models
• Types of Cloud Computing
• Cloud Service Models
• Virtualization in Cloud Computing
• Overview of Popular Cloud Platforms
Course Overview
• Understand core cloud computing fundamentals
• Learn how cloud systems work in real-world environments
• Explore cloud architecture, networking, and virtualization
• Gain clarity on cloud types and service models
• Build a solid conceptual foundation for advanced cloud technologies
Why Take This Course
• Covers all core cloud computing fundamentals
• Beginner-friendly and easy to understand
• Structured and focused learning approach
• Updated for 2026
Why Learn Cloud Computing
• One of the most in-demand skills in IT
• Builds a strong foundation for cloud and DevOps careers
• Helps understand modern data storage and processing systems
• Supports long-term growth in evolving technology domains
Start your journey into cloud computing fundamentals and build a strong foundation for a career in modern IT.
Who this course is for
■ Beginners who want to learn cloud computing fundamentals from scratch
■ Students and graduates interested in starting a career in IT or cloud computing
■ IT professionals looking to understand cloud concepts, architecture, and networking
■ Developers and engineers who want a strong foundation in cloud computing and virtualization
■ Business professionals interested in cloud technology and its business impact
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https://www.udemy.com/course/easy-cloud-basics

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Free Download Clinical Research Skill-Building with AI
Published 3/2026
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 3h 49m | Size: 2.44 GB
Clinical Digital and AI Literacy, Automation, and Career Advancement.

What you’ll learn
Master AI Prompt Engineering: Write clear, structured AI prompts to automate daily clinical research tasks and save hours on routine documentation.
Implement AI-Assisted Writing: Generate GCP-aligned emails, monitoring notes, and safety narratives using GenAI tools like ChatGPT and Claude.
Apply RBQM & Data Analytics: Use AI for risk-based quality management, anomaly detection, and identifying patterns in complex clinical datasets.
Future-Proof Your Clinical Career: Build an AI-ready resume and master the digital literacy needed for high-demand roles in modern clinical operations.
Requirements
Foundational Clinical Knowledge: A basic understanding of the clinical trial lifecycle (Phase 1-4) and ICH-GCP guidelines is recommended to apply AI contextually
No Technical Coding Required: You do not need experience in Python, R, or data science; the course focuses on user-friendly AI interfaces.
Standard Computing Setup: A laptop or desktop with a reliable internet connection is essential for accessing cloud-based AI platforms
AI Tool Access: Learners should have (or be willing to create) free accounts for Generative AI tools like ChatGPT, Claude, or Google Gemini.
Critical Thinking Skills: A willingness to question and verify AI-generated outputs is vital, as human oversight remains mandatory in clinical research.
Adaptability: A growth mindset is encouraged to navigate the rapid shift from manual processes to AI-augmented workflows.
Description
Unlock the future of clinical operations with Clinical Research Skill-Building with AI: Digital Literacy, Automation, and Career Advancement. This masterclass is specifically designed to bridge the critical gap between traditional ICH-GCP guidelines and cutting-edge Generative AI technologies. Tailored for CRAs, CRCs, and Study Coordinators, the curriculum targets operational "pain points" like recruitment delays and heavy documentation burdens through high-efficiency AI integration.
Participants gain hands-on experience in Prompt Engineering for Clinical Research, learning to automate monitoring notes, safety narratives, and site correspondence without compromising compliance. The course dives deep into high-impact domains, including Risk-Based Quality Management (RBQM), automated data anomaly detection, and the evolution of AI within decentralized clinical trials. Beyond technical automation, we emphasize Executive Presence and professional communication, empowering you to lead digital transformation initiatives within your organization.
Expanded Learning Objectives
• Master AI Prompt Engineering: Develop the ability to craft structured, context-aware prompts to automate daily clinical tasks and streamline routine study documentation.
• Implement AI-Assisted Writing: Learn to generate GCP-aligned emails, monitoring logs, and complex regulatory summaries using professional GenAI tools.
• Apply RBQM & Data Analytics: Leverage AI for advanced signal detection, identifying Key Risk Indicators (KRIs), and cleaning intricate clinical datasets for improved trial integrity.
• Optimize Patient Recruitment: Utilize AI-supported screening and feasibility tools to accelerate inclusion/exclusion checks and reduce enrollment timelines.
• Integrate Digital Literacy: Gain confidence in navigating AI-supported dashboards and automation platforms essential for modern decentralized and hybrid trials.
• Future-Proof Your Career: Build an AI-ready professional portfolio and master the essential "soft skills," mindfulness, and digital literacy required for high-stakes interviews in the modern clinical landscape.
Step into the next generation of clinical research and transform your professional workflow with the power of Artificial Intelligence. Gain the competitive edge needed to lead in an AI-driven industry while maintaining the highest standards of clinical ethics and data integrity.
Who this course is for
Current Clinical Research Professionals (CRAs, CRCs, & Study Coordinators): Individuals looking to reduce their "monitoring burden" and automate repetitive documentation like safety narratives, monitoring notes, and site correspondence
Clinical Data Managers & Analytics Aspirants: Professionals aiming to transition into "Clinical Data Scientist" roles by mastering AI-powered anomaly detection, data cleaning, and predictive risk modeling.
Clinical Operations Leaders & Project Managers: Decision-makers who need to understand the ROI of AI implementation to reduce trial timelines, optimize site selection, and lead digital transformation within their organizations.
Regulatory & Medical Affairs Specialists: Writers and compliance officers who want to use GenAI to assist in drafting Clinical Study Reports (CSRs), summarizing protocols, and tracking global regulatory intelligence

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Client-side Data Persistence
Duration: 40m | .MP4 1280×720 30 fps(r) | AAC, 48000 Hz, 2ch | 118.96 MB
Genre: eLearning | Language: English​

This course will teach you how to store, retrieve, and manage data directly in the browser using Local Storage, Session Storage, and IndexedDB to create faster, more reliable, and offline-capable web apps.

More Info:
Client-side Data Persistence

Clean and Transform Data with Polars
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz, 2 Ch
Level: Beginner | Genre: eLearning | Language: English + subtitle | Duration: 41m 15s | Size: 99 MB​

Messy, inconsistent data makes analysis unreliable and slow.

What you’ll learn
Messy, inconsistent data makes analysis unreliable and slow. In this course, Clean and Transform Data with Polars, you will learn how to prepare real-world datasets for analysis using Polars’ expression-based API.
First, you’ll explore profiling data quality issues such as nulls, duplicates, and invalid values, and determining what must be fixed before analysis. Next, you’ll discover what it takes to standardize datasets.
Finally, you’ll learn about creating transformed datasets using quick checks such as row counts and null counts, and export the final, analysis-ready data to a durable format, with Parquet as the recommended option.
By the end of this course, you will have the skills and confidence to clean, transform, validate, and export data using Polars for real-world data analysis workflows.

Free Download Claude with the Anthropic API by Anthropic
Released 4/2026
With Anthropic
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz, 2 Ch
Skill Level: Intermediate | Genre: eLearning | Language: English + subtitle | Duration: 8h 11m | Size: 1.11 GB

This comprehensive course teaches developers how to integrate Claude AI into applications using the Anthropic API.
Course details
This course covers fundamental API operations, advanced prompting techniques, tool integration, and architectural patterns for building AI-powered systems using Claude and the Anthropic API. Through hands-on exercises and practical examples, learn how to implement conversational AI, retrieval-augmented generation, and automated workflows. Plus, find out how to leverage Claude’s multimodal capabilities for processing text, images, and documents. Note: This course was created by Anthropic. We are pleased to host this content in our library. Prerequisites Proficiency in Python programming Basic knowledge of handling JSON data
Skills covered
Retrieval-Augmented Generation (RAG), Anthropic Claude, Workflow Automation, Application Programming Interfaces (API), Artificial Intelligence (AI)
Homepage
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https://www.linkedin.com/learning/claude-with-the-anthropic-api-by-anthropic

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Free Download Claude with Google Cloud Vertex AI by Anthropic
Released 4/2026
With Anthropic
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz, 2 Ch
Skill Level: Intermediate | Genre: eLearning | Language: English + subtitle | Duration: 7h 51m | Size: 1.12 GB

This comprehensive course covers working with Anthropic models using Google Cloud Vertex AI.
Course details
This course provides comprehensive technical training on integrating and deploying Claude AI models through Google Cloud Vertex AI. Developers will learn to implement Claude API capabilities, from basic request handling to advanced features including tool use, retrieval-augmented generation (RAG), and the Model Context Protocol (MCP). The curriculum covers practical implementation patterns, performance optimization techniques, and production-ready workflows for building AI-powered applications. Prerequisitesroficiency in Python programming Basic knowledge of handling JSON data A Google Cloud account with Vertex AI access Note: This course was created by Anthropic. We are pleased to host this training in our library.
Skills covered
Retrieval-Augmented Generation (RAG), Anthropic Claude, Vertex, Artificial Intelligence (AI), Model Context Protocol (MCP)
Homepage
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https://www.linkedin.com/learning/claude-with-google-cloud-vertex-ai-by-anthropic

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Free Download Claude with Amazon Bedrock by Anthropic
Released 3/2026
With Anthropic
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz, 2 Ch
Skill Level: Intermediate | Genre: eLearning | Language: English + subtitle | Duration: 7h 26m | Size: 1 GB

Discover the essential skills and core concepts of working with Anthropic models using Amazon Bedrock, the popular AWS platform for building AI agents and applications.
Course details
Building production AI applications with Claude requires more than API access-you need systems that handle retrieval, tool use, caching, and scale. Amazon Bedrock provides the managed infrastructure to build these systems in the AWS ecosystem. This course teaches you to implement Claude’s API, create production-ready applications, and apply advanced capabilities including tool use, retrieval-augmented generation (RAG), and autonomous agents.Get started with core API implementation patterns, then learn how to build RAG systems and conversational AI pipelines. Along the way, find out how to develop autonomous agents for tasks like code generation and debugging, and learn performance optimization techniques including caching and scalable architecture design.Note: This course requires basic Python programming proficiency and a basic understanding of AWS services and Amazon Bedrock.This course was created by Anthropic. We are pleased to host this training in our library.
Skills covered
Retrieval-Augmented Generation (RAG), AI Agents, Anthropic Claude, Amazon Bedrock, Artificial Intelligence (AI), Application Development
Homepage
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https://www.linkedin.com/learning/claude-with-amazon-bedrock-by-anthropic

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