Overview
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AWS Core + Business Focus for Team Managers Specialization equips managers and business professionals with practical AWS knowledge across cloud fundamentals, migration, analytics, databases, AI, security, governance, automation, and cost optimization. Learners will be able to evaluate cloud initiatives, collaborate effectively with technical teams, and align AWS solutions with business goals.
It is designed for team managers, business leaders, project managers, and technology professionals who need to understand how AWS services support business transformation and digital innovation. By completing this specialization, learners will gain practical knowledge that enables them to collaborate effectively with technical teams, make informed cloud decisions, and align technology initiatives with business objectives.
By completing this specialization, you will develop skills to:
Understand cloud computing concepts and AWS core services. Evaluate cloud migration strategies and data transfer solutions. Analyze business data using AWS analytics and data processing services.
AWS Core + Business Focus for Team Managers Specialization is broadly divided into six courses. The detail of courses is provided below:
Course 1: AWS: Introduction to Cloud Computing
Course 2: AWS: Migration & Analytics
Course 3: AWS: Database & Integration
Course 4: AWS: Generative AI & Amazon Bedrock
Course 5: AWS: AI Services
Course 6: AWS: Finance & Compliance
Syllabus
- Course 1: AWS: Introduction to Cloud Computing
- Course 2: AWS: Finance & Compliance
- Course 3: AWS: Migration & Analytics
- Course 4: AWS: Database & Integration
- Course 5: AWS: AI Services
- Course 6: AWS: Generative AI & Bedrock
Courses
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This course is designed to provide a comprehensive introduction to AWS Artificial Intelligence (AI) Services, enabling learners to understand how organizations use managed AI solutions to add intelligence to applications without building machine learning models from scratch. Participants will explore AWS services that support natural language processing, speech recognition, conversational AI, computer vision, intelligent search, personalization, and document intelligence. The course begins by introducing AI services for language processing and conversational experiences. Learners will explore services that analyze text, translate languages, convert speech to text, generate natural-sounding speech, and build intelligent chatbots. The course then progresses to AI services for computer vision, intelligent search, personalization, and human-in-the-loop workflows, helping learners understand how organizations extract insights from images and documents, deliver personalized recommendations, and improve AI outcomes through human review processes. This course is structured into multiple modules, each featuring lessons and video lectures that provide both theoretical knowledge and practical demonstrations of AWS AI services. Participants will engage with approximately 2–3 hours of instructional content, ensuring both conceptual understanding and practical application. To reinforce learning, graded and ungraded assignments are included within each module to help learners apply AI concepts in real-world business scenarios. Module 1: AI Services for Language & Conversational AI Module 2: AI Services for Vision, Search & Personalization At the end of the course, learners will learn * Understand the capabilities and use cases of AWS managed AI services for language processing, speech AI, computer vision, intelligent search, and personalization. * Identify the appropriate AWS AI service for different business and technical requirements. * Explain how organizations use AWS AI services to build intelligent applications and improve customer experiences. This course is for Cloud Practitioners, Team Managers, Business Analysts, Solutions Architects, Developers, Data Professionals, AI Enthusiasts, and learners interested in understanding AWS AI services and their business applications.
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This course is designed to provide a foundational understanding of AWS database and application integration services, enabling learners to build scalable, reliable, and loosely coupled cloud architectures. Participants will explore how AWS services help applications communicate, exchange data, and integrate across distributed systems while leveraging managed database solutions to store, process, and analyze data efficiently. The course begins by introducing AWS application integration and messaging services that enable event-driven architectures, asynchronous communication, workflow orchestration, and service-to-service integration. Learners will then explore AWS database services, gaining an understanding of relational, NoSQL, in-memory, graph, and ledger databases, along with the use cases that drive database selection in modern cloud environments. This course is structured into multiple modules, each featuring lessons and video lectures that provide both conceptual understanding and practical insights into AWS integration and database services. Participants will engage with approximately 2–3 hours of instructional content, ensuring a balance of foundational knowledge and real-world application. To reinforce learning, graded and ungraded assignments are included within each module to help learners apply concepts in realistic cloud scenarios. Module 1: AWS Application Integration & Messaging Services Module 2: AWS Database Services At the end of the course, learners will learn * Understand the purpose and business value of AWS application integration and messaging services. * Identify appropriate AWS database services based on application and workload requirements. * Explain how AWS integration and database services work together to build scalable, resilient, and cloud-native solutions. This course is for Cloud Practitioners, Team Managers, Business Analysts, Solutions Architects, Developers, Database Administrators, Application Engineers, IT Professionals, and learners seeking to understand AWS integration and database technologies.
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This course is designed to provide a comprehensive understanding of AWS services used for governance, monitoring, security, compliance, automation, and cost management. Learners will explore how organizations maintain secure, compliant, and cost-efficient cloud environments while ensuring operational visibility and effective resource management. The course begins with monitoring, auditing, and governance services that help organizations track resource activity, maintain compliance, and gain operational insights. Learners will then explore AWS identity, security, and compliance services that protect cloud workloads, manage access controls, safeguard sensitive data, and support regulatory requirements. Finally, the course covers management, automation, and cost optimization services that help organizations automate infrastructure management, govern multi-account environments, and optimize cloud spending. This course is structured into multiple modules, each featuring lessons and video lectures that provide both theoretical knowledge and practical insights into AWS governance and management services. Participants will engage with approximately 2–3 hours of instructional content, ensuring both conceptual understanding and practical application. To reinforce learning, graded and ungraded assignments are included within each module to help learners apply governance, security, and cost management concepts in real-world cloud environments. Module 1: Monitoring, Auditing & Governance Services Module 2: Identity, Security & Compliance Module 3: Management, Automation & Cost Optimization At the end of the course, learners will learn * Understand how AWS services support monitoring, auditing, governance, security, compliance, and cost optimization. * Implement identity and access management best practices to secure AWS resources. * Use AWS management and cost optimization services to improve operational efficiency and cloud governance. This course is for Team Managers, Cloud Practitioners, IT Professionals, Solutions Architects, Security Engineers, Operations Engineers, Compliance Professionals, Project Managers, and learners seeking to understand AWS governance and operational best practices.
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This course is designed to provide a comprehensive introduction to Generative AI and the AWS services that enable organizations to build, customize, and deploy AI-powered applications. Learners will explore the foundational concepts of generative AI, understand how foundation models work, and discover how businesses are using these technologies to transform customer experiences, automate processes, and drive innovation. The course begins by introducing the core concepts of generative AI, including foundation models, model lifecycles, business use cases, challenges, and evaluation metrics. Learners will then explore Amazon Q and Amazon Bedrock, gaining an understanding of how AWS simplifies the development of generative AI applications through managed services and access to multiple foundation models. Finally, the course covers advanced concepts such as Retrieval-Augmented Generation (RAG), knowledge bases, AI agents, guardrails, and model evaluation, enabling learners to understand how modern AI applications are built and governed. This course is structured into multiple modules, each featuring lessons and video lectures that provide theoretical knowledge and practical demonstrations. Participants will engage with approximately 2–3 hours of instructional content, ensuring both conceptual understanding and practical application. To reinforce learning, graded and ungraded assignments are included within each module to help learners apply generative AI concepts in real-world scenarios. Module 1: Generative AI Foundations Module 2: Amazon Q & Amazon Bedrock Fundamentals Module 3: RAG, Knowledge Bases & AI Agents ## At the end of the course, learners will learn * Understand the core concepts, terminology, use cases, and business value of Generative AI and Foundation Models. * Explore Amazon Q, Amazon Bedrock, and foundation model selection strategies to build AI-powered applications on AWS. * Understand Retrieval-Augmented Generation (RAG), knowledge bases, AI agents, guardrails, and evaluation techniques for developing trustworthy generative AI solutions. This course is for Team Managers, Business Leaders, Cloud Practitioners, Solutions Architects, Developers, Data Engineers, AI Enthusiasts, Technical Consultants, and professionals interested in understanding Generative AI on AWS.
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This course is designed to provide a comprehensive foundation in cloud computing and Amazon Web Services (AWS), helping learners understand how organizations leverage cloud technologies to build scalable, secure, and cost-effective solutions. Participants will begin by exploring the fundamental concepts of cloud computing, including cloud service models, deployment models, and the business benefits of cloud adoption. The course progresses to AWS-specific concepts, introducing learners to AWS global infrastructure, Regions, Availability Zones, support plans, and cloud adoption strategies. Participants will also gain an understanding of AWS account management, cloud security principles, migration strategies, and the AWS services that support workload and data migration. Additionally, the course covers the AWS Well-Architected Framework, enabling learners to understand the best practices used to design secure, reliable, high-performing, cost-optimized, and sustainable cloud architectures. This course is structured into multiple modules, each featuring lessons and video lectures that provide both theoretical knowledge and practical insights into AWS cloud technologies. Participants will engage with approximately 2–3 hours of instructional content, ensuring both conceptual understanding and practical application. To reinforce learning, graded and ungraded assignments are included within each module to help learners apply cloud concepts in real-world business and technical scenarios. Module 1: Cloud Computing & AWS Foundations Module 2: AWS Account, Security & Migration Module 3: AWS Well-Architected Framework At the end of the course, learners will learn * Understand the fundamental concepts and benefits of cloud computing. * Differentiate between cloud service models including IaaS, PaaS, and SaaS. * Explain cloud deployment models such as Public, Private, Hybrid, and Multi-Cloud. * Understand AWS global infrastructure, including Regions and Availability Zones. * Learn how to create and navigate an AWS account and the AWS Management Console. * Evaluate AWS support plans and cloud adoption strategies. * Understand the AWS Shared Responsibility Model and security best practices. * Identify common cloud migration strategies using the 6 Rs framework. * Explore AWS services that support migration and hybrid cloud environments. * Understand the purpose and benefits of the AWS Well-Architected Framework. * Apply the principles of Operational Excellence, Security, Reliability, Performance Efficiency, Cost Optimization, and Sustainability. * Develop the foundational knowledge required for further AWS learning and certification preparation. This course is for Cloud Beginners, Team Managers, Business Decision Makers, Project Managers, IT Professionals, Solutions Architects, Developers, Technical Consultants, and learners preparing to begin their AWS cloud journey.
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This course is designed to provide a comprehensive introduction to AWS migration, data transfer, analytics, and data processing services. Learners will explore how organizations migrate applications, databases, and large datasets to AWS while leveraging cloud-native analytics services to gain actionable insights from their data. The course begins with AWS migration and data transfer services, covering the strategies and tools that help organizations move workloads and data securely and efficiently to the cloud. Learners will explore services that support online and offline data migration, hybrid storage integration, and migration project management. The course then progresses to AWS analytics and data processing services, introducing solutions for big data processing, real-time streaming analytics, business intelligence, and search and analytics workloads. This course is structured into multiple modules, each featuring lessons and video lectures that provide theoretical knowledge and practical insights into AWS migration and analytics solutions. Participants will engage with approximately 2–3 hours of instructional content, ensuring both conceptual understanding and practical application. To reinforce learning, graded and ungraded assignments are included within each module to help learners apply migration and analytics concepts in real-world scenarios. Module 1: AWS Migration & Data Transfer Services Module 2: AWS Analytics & Data Processing Services At the end of the course, learners will learn * Understand the business drivers and benefits of cloud migration. * Identify common migration strategies and migration planning considerations. * Describe AWS services used for workload and data migration. * Understand how AWS Migration Hub helps manage migration projects. * Explore AWS Transfer Family for secure file transfer solutions. * Understand hybrid cloud storage integration using AWS Storage Gateway. * Learn how AWS Snow Family supports large-scale data migration and edge computing use cases. * Describe the capabilities and use cases of Amazon EMR for big data processing. * Understand how Amazon Kinesis enables real-time data streaming and analytics. * Explore Amazon QuickSight for business intelligence and data visualization. * Understand the role of Amazon OpenSearch Service in search and analytics workloads. * Identify appropriate AWS services for migration, analytics, and data processing requirements. * Develop foundational knowledge of AWS data movement and analytics solutions. This course is for Cloud Practitioners, Team Managers, Business Analysts, Project Managers, Solutions Architects, Developers, Data Engineers, IT Professionals, and learners seeking to understand AWS migration and analytics services.
Taught by
Whizlabs Instructor