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Advanced Techniques in Securing Cloud Operations

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The Securing Cloud Operations specialization is designed to equip absolute beginners with a clear, practical, and security-first understanding of how to deploy, harden, and validate a small cloud-based web environment across AWS, Microsoft Azure, or Google Cloud. Through this program, learners will gain hands-on experience identifying common cloud misconfigurations—such as exposed virtual machines, open storage buckets, overly permissive access policies, and unmanaged credentials—and learn how these issues can rapidly escalate into real-world breaches. Following a structured, step-by-step curriculum, each module uses free-tier services, simple checklists, and guided walkthroughs to help learners build confidence while securing foundational cloud components.

Participants will learn why cloud service models (IaaS, PaaS, and SaaS) change security decisions, how the shared-responsibility model defines what the provider secures versus what the customer must secure, and which built-in, one-click protections can dramatically reduce risk. The specialization emphasizes practical controls such as identity and access management basics, secure networking defaults, storage access restrictions, logging and monitoring essentials, and baseline hardening for compute instances. Learners will also practice reviewing configurations with an audit mindset, documenting security evidence, and validating improvements through repeatable checks.

By the end of this program, learners will have tested a cloud virtual machine against the CIS Benchmark, collected and exported audit-ready evidence into a structured folder, and created a printable ten-control security checklist that can be applied to future cloud projects. This specialization prepares aspiring cloud practitioners, IT professionals, and security newcomers to secure real environments responsibly, communicate security posture clearly, and develop the habits needed to reduce cloud risk through consistent, repeatable operational practices.

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This course contains the use of artificial intelligence.AI is transforming software development, but every intelligent application introduces new security challenges. From chatbots and large language models to autonomous AI agents, organizations need professionals who understand how AI systems can be attacked—and how to defend them.Welcome to AI Security Fundamentals: Secure LLMs and AI Applications, a practical course covering AI cybersecurity, Generative AI security, LLM security, and the controls used to protect real-world AI applications. You'll move beyond theory to explore common vulnerabilities, implement defenses, and test your work through guided, hands-on labs.What You'll LearnYou'll start with AI security fundamentals, AI threat modeling, attack surfaces, and trust boundaries. Then you'll investigate the risks highlighted by the OWASP Top 10 for LLM Applications, including prompt injection, indirect prompt injection, sensitive data disclosure, data leakage, model supply chain attacks, and data poisoning.You'll also explore Retrieval-Augmented Generation (RAG) security, vector database security, access control, insecure output handling, and system prompt leakage. As AI applications become more autonomous, you'll learn to reduce AI agent security risks, excessive agency, tool-calling vulnerabilities, and unauthorized actions through least-privilege access, authorization checks, and human approval workflows.Security isn't only about finding vulnerabilities. You'll build defenses using input validation, output validation, PII redaction, authentication, API security, rate limiting, model integrity verification, and defense-in-depth architecture. You'll practice secure AI development, DevSecOps for AI, security testing, AI security monitoring, and incident response.Learn by BuildingThroughout the course, you'll work with BrightDesk, a fictional enterprise AI customer-support assistant. Step by step, you'll assess its architecture, identify threats, protect sensitive data, secure retrieval workflows, validate model artifacts, and control AI agent permissions.Hands-on exercises use accessible tools such as Python, FastAPI, Ollama, FAISS, and pytest. You'll learn how to perform controlled tests in a local environment, evaluate defenses, and document residual risks. No paid AI API subscription is required, and starter examples make the practical work approachable.You'll also become familiar with widely used guidance including NIST AI Risk Management Framework (AI RMF), MITRE ATLAS, and OWASP LLM security resources.The final capstone connects everything: you will create a security checklist, map AI application vulnerabilities, add practical safeguards, run security regression tests, and present findings to stakeholders. This mirrors how real teams collaborate across engineering, architecture, privacy, and security—not by promising perfect protection, but by continually improving measurable controls over time.Who Should Enroll?This course is designed for software developers, AI engineers, solution architects, cybersecurity analysts, security engineers, DevSecOps professionals, and technical leaders responsible for deploying AI safely. Beginners are welcome; basic Python familiarity is helpful for coding exercises but not mandatory.By the end, you'll have more than a vocabulary of AI threats. You'll have practiced applying security controls, producing an AI security risk assessment, and building a portfolio-ready secure AI application prototype. Whether you're securing your first LLM-powered chatbot or reviewing an enterprise AI architecture, you'll leave with a practical foundation for making AI applications more resilient.Enroll and start building AI systems with security in mind from day one.

Agentic AI Red Teaming: Hands-On Security Testing

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This course contains the use of artificial intelligence.AI agents do more than answer questions. They plan, call tools, store memories, coordinate with other agents, and take action. Every capability creates a new security boundary. This hands-on course, Agentic AI Red Teaming: Hands-On Security Testing, teaches you to evaluate those boundaries and uncover failures before they reach production.You'll learn agentic AI security, AI red teaming, LLM security testing, and adversarial AI evaluation through a realistic enterprise case study: BrightDesk, a fictional multi-agent customer support platform. Instead of relying on slides alone, you'll work with an isolated AI agent testing sandbox, synthetic records, mock APIs, local tools, and repeatable tests. See how an apparently harmless instruction can redirect a plan, trigger an inappropriate tool call, or contaminate later decisions.What You'll LearnMap AI agent attack surfaces across planning loops, prompts, tool execution, external data, long-term memory, and multi-agent orchestration.Test prompt injection, goal hijacking, instruction override, multi-turn attacks, and gradual goal drift without touching real customer systems.Evaluate tool-call exploitation, unsafe tool chaining, excessive permissions, weak authorization, and untrusted tool responses.Investigate memory poisoning, persistent state attacks, context manipulation, and retrieval-based threats in RAG workflows.Examine agent-to-agent communication, cross-agent manipulation, false consensus, compromised workers, and multi-agent coordination failures.Assess Model Context Protocol (MCP) security, tool metadata integrity, and unsafe integration boundaries.Design adversarial test cases, automated security regression testing, execution traces, and AI security scorecards.Measure cascading failures, propagation depth, blast radius, unsafe action rates, and the difference between single-turn failure and system-wide compromise.Apply least privilege, policy enforcement, approval gates, memory validation, monitoring, and defense-in-depth, then retest to verify improvements.Build Practical Red-Team SkillsUsing Python, Ollama, LangGraph, FastAPI, and pytest, you'll develop an agent testing environment and run controlled scenarios against BrightDesk. Explore AI threat modeling, risk prioritization, evidence collection, trace analysis, and security reporting. You'll also encounter concepts from the OWASP Top 10 for Agentic Applications, MITRE ATLAS, and AI governance, connecting technical findings to real enterprise risk decisions.You'll practice distinguishing a model's incorrect answer from an agent's unauthorized action, and you'll learn why execution logs, reproducible scenarios, and clear pass/fail criteria matter when testing complex, stateful AI workflows in enterprise environments.Your capstone is an end-to-end agentic AI penetration testing exercise in an authorized simulation. Create a threat model, execute structured adversarial evaluations, document vulnerabilities, introduce safeguards, and compare security results before and after remediation. You'll leave with reusable test templates, a security evaluation framework, and a portfolio-ready assessment report.Who Should Enroll?This course is designed for AI engineers, LLM developers, application security engineers, red teamers, penetration testers, AI architects, security researchers, and teams building autonomous AI agents or enterprise generative AI solutions. Basic Python skills and familiarity with LLMs or APIs will help; prior professional red-team experience isn't required.If you're moving from traditional cybersecurity to agentic AI risk management, or building production agents that must be trustworthy, this course gives you a structured, hands-on way to test what happens when an AI system does more than talk.

Microsoft AZ-305: Azure Solutions Architect Practice Exams

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Preparing for the Microsoft AZ-305: Designing Microsoft Azure Infrastructure Solutions certification exam? Take your preparation to the next level with 360 scenario-based practice questions designed to strengthen your Azure architecture knowledge, sharpen your technical decision-making skills, and build confidence before exam day.This comprehensive practice exam course focuses on designing secure, scalable, reliable, and cost-effective Microsoft Azure solutions.With 360 practice questions, you will work through realistic architecture scenarios involving Azure Identity and Governance, Data Storage Solutions, Business Continuity, and Infrastructure Design.These practice exams help you evaluate competing architectural approaches, analyze technical and business requirements, and select the most appropriate Azure solutions based on Microsoft best practices.Why Choose These Microsoft AZ-305 Practice Exams?360 High-Quality Practice QuestionsStrengthen your preparation with a comprehensive collection of questions covering the essential knowledge and skills measured by the Microsoft AZ-305 certification exam.Realistic, Scenario-Based Architecture QuestionsPractice solving complex design challenges involving Azure networking, compute, storage, identity, security, governance, and disaster recovery.Aligned with Microsoft AZ-305 Exam ObjectivesFocus your preparation on the major skills measured in the Designing Microsoft Azure Infrastructure Solutions exam.Detailed Explanations for Correct and Incorrect AnswersUnderstand why the recommended architecture meets the requirements and why alternative solutions may be less appropriate.Microsoft Learn Documentation-Based LearningReinforce important concepts using official Microsoft documentation and recommended Azure architecture practices.Develop Real-World Azure Architecture SkillsGo beyond memorization by learning how to design solutions that balance performance, availability, security, scalability, and cost.What Will You Practice?The 360 practice questions cover the four major domains of the Microsoft AZ-305 certification exam.Domain 1: Design Identity, Governance, and Monitoring SolutionsLearn how to design secure and manageable Azure environments that meet organizational identity, security, compliance, and monitoring requirements.Key topics include:Design authentication and authorization solutions using Microsoft Entra ID.Design hybrid identity and identity synchronization strategies.Implement role-based access control (Azure RBAC).Design privileged access and identity governance solutions.Design Azure Policy and governance strategies.Plan management groups, subscriptions, and resource organization.Design monitoring solutions using Azure Monitor and Log Analytics.Design centralized logging, alerting, and diagnostic strategies.Evaluate security, compliance, and operational management requirements.Practice selecting identity and governance solutions that support enterprise security and operational efficiency.Domain 2: Design Data Storage SolutionsStrengthen your ability to select appropriate Azure storage and database technologies based on application requirements.Key topics include:Design relational data storage solutions using Azure SQL Database and Azure SQL Managed Instance.Evaluate Azure Cosmos DB for globally distributed and scalable applications.Design Azure Blob Storage and Azure Files solutions.Select appropriate storage redundancy and replication options.Design data protection, encryption, and access control strategies.Plan data migration and integration solutions.Evaluate database performance, availability, and scalability requirements.Design backup and recovery strategies for data platforms.Compare storage services based on cost, performance, and operational requirements.Learn how to select the most suitable Azure data services for different business and technical scenarios.Domain 3: Design Business Continuity SolutionsDevelop the skills needed to design highly available, resilient, and recoverable Azure environments.Key topics include:Design high availability and disaster recovery strategies.Evaluate Recovery Time Objective (RTO) and Recovery Point Objective (RPO) requirements.Design Azure Backup solutions.Implement disaster recovery strategies using Azure Site Recovery.Evaluate availability zones and Azure region architectures.Design geo-redundant storage and database replication.Plan business continuity for critical workloads.Design resilient application architectures.Evaluate backup retention, recovery options, and disaster recovery costs.Practice designing solutions that minimize downtime, protect critical data, and meet business continuity requirements.Domain 4: Design Infrastructure SolutionsLearn how to design scalable, secure, and high-performance Azure infrastructure architectures.Key topics include:Design Azure Virtual Machines and compute solutions.Evaluate Azure App Service, Azure Functions, and container-based hosting options.Design Azure Kubernetes Service (AKS) architectures.Plan virtual networking, subnetting, and network connectivity.Design hybrid connectivity using VPN Gateway and ExpressRoute.Evaluate Azure Load Balancer, Application Gateway, and Azure Front Door.Design network security using Azure Firewall, Network Security Groups, and private endpoints.Plan application migration and modernization strategies.Design scalable infrastructure solutions.Evaluate performance, cost optimization, and operational requirements.Practice choosing Azure infrastructure services that best satisfy business needs, technical constraints, and architectural best practices.Learn from Every Practice QuestionEvery question includes detailed explanations for the correct and incorrect answer options.These explanations help you understand the reasoning behind architectural decisions rather than simply memorize answers.You will practice identifying key requirements, evaluating competing solutions, recognizing design constraints, and selecting architectures that align with Microsoft recommendations.For example, you may need to determine:Which Azure networking architecture provides secure connectivity between regions and on-premises environments.How to design a highly available application across multiple availability zones.Which Azure database service best meets scalability and consistency requirements.How to design an effective disaster recovery solution based on RTO and RPO objectives.Which identity and governance controls satisfy enterprise security requirements.How to optimize Azure infrastructure costs without compromising reliability.Which Azure compute platform is most appropriate for a specific application workload.By reviewing the explanations, you can identify knowledge gaps and improve your ability to solve complex architecture scenarios.Develop Practical Azure Solutions Architecture SkillsThe Microsoft AZ-305 exam requires more than knowing individual Azure services.You need to understand how different Azure technologies work together to deliver secure, scalable, resilient, and cost-effective enterprise solutions.These practice exams will help you:Analyze business and technical requirements.Design identity, governance, and monitoring solutions.Select appropriate data storage and database technologies.Plan business continuity and disaster recovery strategies.Design networking, compute, and application infrastructure.Evaluate architectural trade-offs involving cost, performance, security, and reliability.Apply Microsoft Azure Well-Architected Framework principles.Strengthen your ability to interpret scenario-based certification questions.A solid understanding of Azure administration, networking, compute, storage, security, and virtualization is recommended.How to Get the Most Out of These Practice ExamsComplete the practice questions under realistic exam conditions. Evaluate your current knowledge without consulting external resources.Review every answer explanation. Understand why the correct solution meets the requirements and why alternative architectures may be unsuitable.Identify your weak areas. Focus on domains where you need additional preparation.Study official Microsoft Learn documentation. Reinforce your understanding of Azure architecture concepts and recommended design practices.Retake the practice questions. Track your progress and strengthen your technical decision-making skills.Remember, success in the AZ-305 exam depends on understanding architectural trade-offs and selecting solutions that best satisfy real-world business requirements.Start Your Microsoft AZ-305 Exam Preparation Today!Designing Microsoft Azure infrastructure solutions requires a strong understanding of cloud architecture, security, governance, data platforms, business continuity, and infrastructure services.With 360 practice questions, detailed answer explanations, and realistic Azure architecture scenarios, this course provides a structured approach to strengthening your knowledge and evaluating your exam readiness.Whether you are preparing for certification or advancing your cloud architecture expertise, these practice exams will help you develop valuable technical skills and greater confidence.Enroll today and take the next step toward passing your Microsoft AZ-305 certification exam!Happy learning, and best of luck with your Microsoft AZ-305: Designing Microsoft Azure Infrastructure Solutions exam!

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Advanced Techniques in Securing Cloud Operations

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AI Security Fundamentals: Secure LLMs and AI Applications

Agentic AI Red Teaming: Hands-On Security Testing

Microsoft AZ-305: Azure Solutions Architect Practice Exams

Advanced Techniques in Securing Cloud Operations

About this course

Skills you'll gain

Available Coupons

Course Information

This course includes:

Share this course

You May Also Like

AI Security Fundamentals: Secure LLMs and AI Applications

Agentic AI Red Teaming: Hands-On Security Testing

Microsoft AZ-305: Azure Solutions Architect Practice Exams