School of AI Certified Solutions Architect (Associate)
IT & Software100% OFF

School of AI Certified Solutions Architect (Associate)

Udemy Instructor
0(2.0K students)
Self-paced
All Levels

About this course

This course involves the use of artificial intelligence(AI).The School of AI Certified Solutions Architect (Associate) course is your comprehensive pathway to mastering AWS cloud architecture, high availability, and secure, scalable design patterns. Whether you are preparing for the AWS Solutions Architect Associate certification exam or looking to elevate your career in cloud computing, this program equips you with the practical skills and theoretical foundation needed to succeed.This hands-on course takes you from the fundamentals of the AWS global infrastructure—including Regions, Availability Zones, and Edge Locations—through advanced topics like multi-region architectures, disaster recovery strategies, and cost optimization. You will gain deep knowledge of critical AWS services such as Amazon EC2, S3, EBS, EFS, RDS, Aurora, DynamoDB, VPC networking, IAM, CloudWatch, CloudFormation, Elastic Beanstalk, and ElastiCache.

Each module is carefully designed to align with the AWS Well-Architected Framework, covering the six pillars: operational excellence, security, reliability, performance efficiency, cost optimization, and sustainability.By focusing on real-world architecture scenarios, the course ensures you not only learn the theory but also how to apply it in practice. Through hands-on labs and mini-projects, you will design resilient infrastructures using Elastic Load Balancing, Auto Scaling Groups, and serverless compute with AWS Lambda. You will explore microservices architectures with ECS, EKS, and Fargate, learn how to decouple applications with SQS, SNS, and EventBridge, and secure your workloads with IAM roles and policies, AWS KMS, WAF, and Shield.The course also provides detailed coverage of monitoring and observability tools such as CloudWatch metrics, logs, alarms, and dashboards, as well as compliance services like AWS Config and CloudTrail.

By the end, you will understand how to architect solutions that are fault-tolerant, cost-efficient, and compliant with industry standards.What sets this course apart is its emphasis on exam preparation. You’ll review common exam scenarios, architecture patterns, and practice with 50 exam-style multiple-choice questions designed to simulate the real AWS Solutions Architect Associate exam. You will also complete a final capstone project, where you will design and present a full AWS solution that applies everything you’ve learned—from compute and storage to networking, security, and cost optimization.This course is ideal for IT professionals, system administrators, developers, and aspiring cloud architects who want to build a career in cloud computing and earn a globally recognized AWS certification.

By completing this program, you will gain not only a certificate from the School of AI but also the confidence to design, deploy, and manage AWS-based solutions in professional environments.With cloud computing jobs in high demand and AWS continuing to dominate the market, this certification can open doors to roles such as Cloud Solutions Architect, DevOps Engineer, or Cloud Consultant. Mastering AWS services through this course will help you future-proof your career and join the growing community of certified AWS professionals.

Skills you'll gain

IT CertificationsEnglish

Available Coupons

Course Information

Level: All Levels

Suitable for learners at this level

Duration: Self-paced

Total course content

Instructor: Udemy Instructor

Expert course creator

This course includes:

  • 📹Video lectures
  • 📄Downloadable resources
  • 📱Mobile & desktop access
  • 🎓Certificate of completion
  • ♾️Lifetime access
$0$98.99

Save $98.99 today!

Enroll Now - Free

Redirects to Udemy • Limited free enrollments

You May Also Like

Explore more courses similar to this one

School of AI Certified Cloud Practitioner (Foundational)
IT & Software
906 left

School of AI Certified Cloud Practitioner (Foundational)

Udemy Instructor

This course involves the use of artificial intelligence(AI).Are you ready to begin your journey into the world of cloud computing with AWS? The School of AI Certified Cloud Practitioner (Foundational) course is designed to give you a complete, beginner-friendly introduction to the Amazon Web Services (AWS) Cloud while preparing you for the AWS Certified Cloud Practitioner (CLF-C02) exam. Whether you are a student, IT professional, manager, or career changer, this course will provide the knowledge and confidence you need to understand the AWS Cloud ecosystem and its real-world business value.In today’s technology-driven world, organizations across every industry—from startups to enterprises—are adopting AWS cloud services to improve agility, scalability, and cost efficiency. By mastering the AWS Cloud Practitioner certification, you will gain a recognized credential that demonstrates your ability to understand cloud concepts, AWS global infrastructure, pricing, billing, and support, as well as fundamental security and compliance best practices.This course is structured to cover every domain of the exam while building practical, hands-on skills. You’ll start by exploring what cloud computing is, the benefits of AWS such as agility, elasticity, and pay-as-you-go pricing, and the fundamentals of the AWS global infrastructure including Regions, Availability Zones, and Edge Locations. From there, you will dive into compute services like Amazon EC2, AWS Lambda, Elastic Beanstalk, and Lightsail, followed by storage options such as Amazon S3, EBS, EFS, and Glacier.You will also learn the differences between relational and non-relational databases, exploring Amazon RDS, DynamoDB, Aurora, and Redshift. Networking essentials are covered in depth, including Amazon VPC, Route 53, CloudFront, and Elastic Load Balancing. In the security domain, you’ll master the AWS Shared Responsibility Model, build identities with IAM users, groups, roles, and policies, and secure data using encryption with AWS KMS and AWS Secrets Manager.Cloud economics is a critical exam area, so this course provides step-by-step guidance on using the AWS Pricing Calculator, understanding the AWS Free Tier, analyzing bills in the Billing & Cost Management Dashboard, and applying pricing models such as On-Demand, Reserved Instances, Spot, and Savings Plans. You’ll also explore the AWS Well-Architected Framework and the six pillars—Operational Excellence, Security, Reliability, Performance Efficiency, Cost Optimization, and Sustainability.To ensure you are fully prepared, the course includes hands-on labs such as creating IAM users with MFA, launching EC2 instances, hosting static websites on Amazon S3, setting up alarms in CloudWatch, and reviewing logs in CloudTrail. Each section includes exam tips, practice questions, and cheat sheets to reinforce your learning.By the end of this course, you will:Understand AWS cloud concepts and core servicesApply security and compliance best practicesEstimate and manage costs using AWS pricing toolsPrepare with confidence for the AWS Cloud Practitioner examIf your goal is to earn your AWS certification, build a solid foundation in cloud computing, and boost your career in tech, this is the course for you.

0.02.1KSelf-paced
FREE$98.99
Enroll
Ultimate EKS Bootcamp: From Zero to Production-Ready AWS K8S
IT & Software
959 left

Ultimate EKS Bootcamp: From Zero to Production-Ready AWS K8S

Udemy Instructor

Learn Amazon EKS the right way — from fundamentals to advanced autoscaling and monitoring.This course is designed for DevOps Engineers, Cloud Architects, and Kubernetes practitioners who want to confidently run production workloads on Amazon Elastic Kubernetes Service (EKS).We’ll start with a practical, lab-driven approach — no endless theory. You’ll begin by setting up your AWS and Kubernetes environment, then progress through deploying workloads, managing networking with ALB ingress, enabling persistent storage, and securing access with IAM Roles for Service Accounts (IRSA).From there, we’ll tackle scaling strategies — EKS Cluster Autoscaler, Horizontal Pod Autoscaler, Vertical Pod Autoscaler, and advanced solutions like Karpenter for just-in-time node provisioning, and KEDA for event-driven scaling.Finally, we’ll cover EKS observability with logging, metrics, and dashboards so you can keep your clusters healthy and cost-efficient.By the end of this bootcamp, you’ll have a production-ready EKS skillset — ready to build, scale, and monitor Kubernetes workloads on AWS.What You’ll LearnSet up and configure Amazon EKS clusters from scratchDeploy applications to EKS using kubectl and manifestsConfigure Ingress with AWS ALB Ingress ControllerAttach persistent EBS volumes for stateful workloadsSecure workloads using IAM Roles for Service Accounts (IRSA)Implement EKS Cluster Autoscaler for node scalingApply Horizontal Pod Autoscaler (HPA) and Vertical Pod Autoscaler (VPA) for workload scalingUse Karpenter for next-generation cluster scalingImplement KEDA for event-driven autoscaling scenariosMonitor and troubleshoot EKS clusters using Prometheus, Grafana, and CloudWatchOptimize cost and performance for Kubernetes workloads on AWS

0.01.5KSelf-paced
FREE$83.99
Enroll
Mastering LLM Evaluation: Build Reliable Scalable AI Systems
IT & Software
898 left

Mastering LLM Evaluation: Build Reliable Scalable AI Systems

Udemy Instructor

Unlock the power of LLM evaluation and build AI applications that are not only intelligent—but also reliable, efficient, and cost-effective. This comprehensive course teaches you how to evaluate large language model outputs across the entire development lifecycle—from prototype to production. Whether you're an AI engineer, product manager, or ML ops specialist, this program gives you the tools to drive real impact with LLM-driven systems.Modern LLM applications are powerful, but they're also prone to hallucinations, inconsistencies, and unexpected behavior. That’s why evaluation is not a nice-to-have—it's the backbone of any scalable AI product. In this hands-on course, you'll learn how to design, implement, and operationalize robust evaluation frameworks for LLMs. We’ll walk you through common failure modes, annotation strategies, synthetic data generation, and how to create automated evaluation pipelines. You’ll also master error analysis, observability instrumentation, and cost optimization through smart routing and monitoring.What sets this course apart is its focus on practical labs, real-world tools, and enterprise-ready templates. You won’t just learn the theory of evaluation—you’ll build test suites for RAG systems, multi-modal agents, and multi-step LLM pipelines. You’ll explore how to monitor models in production using CI/CD gates, A/B testing, and safety guardrails. You’ll also implement human-in-the-loop (HITL) evaluation and continuous feedback loops that keep your system learning and improving over time.You’ll gain skills in annotation taxonomy, inter-annotator agreement, and how to build collaborative evaluation workflows across teams. We’ll even show you how to tie evaluation metrics back to business KPIs like CSAT, conversion rates, or time-to-resolution—so you can measure not just model performance, but actual ROI.As AI becomes mission-critical in every industry, the ability to run scalable, automated, and cost-efficient LLM evaluations will be your edge. By the end of this course, you’ll be equipped to design high-quality evaluation workflows, troubleshoot LLM failures, and deploy production-grade monitoring systems that align with your company’s risk tolerance, quality thresholds, and cost constraints.This course is perfect for:AI engineers building or maintaining LLM-based systemsProduct managers responsible for AI quality and safetyMLOps and platform teams looking to scale evaluation processesData scientists focused on AI reliability and error analysisJoin now and learn how to build trustable, measurable, and scalable LLM applications—from the inside out.

0.02.7KSelf-paced
FREE$85.99
Enroll