Cloud Computing Syllabus

• Module 1: Cloud Foundations

The "Foundations" module sets the ground for your Cloud Computing journey:

Cloud Primer: This preparatory work course offers a solid start with basic Python for Cloud and Linux. It's designed to brush up on your fundamental knowledge, prepping you for advanced modules.

Introduction to Virtualization: Learn about Virtual Machines (VMs) and Containers, key components of modern cloud architectures. This section helps in understanding the abstraction of hardware resources.

Service Delivery & Deployment Models: This section gives insights into various cloud models and their applications, enabling you to choose the right strategy for specific needs.

Cloud Attributes & Services Taxonomy: This part of the module helps you understand the hierarchy and taxonomy of cloud services, offering a holistic view of cloud infrastructure.

Introduction to Infrastructure Automation: Understand the vital role of automation in cloud infrastructure, increasing efficiency and reducing human errors in cloud environments.

Key Aspects of IaaS, PaaS, and SaaS: Uncover the unique features and differences between Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS). This knowledge is crucial for making informed decisions in the cloud domain.

At the end of this module, a quiz is conducted to assess your grasp of these foundational concepts.

• Module 2: Amazon Web Services

The "Amazon Web Services" module provides a comprehensive understanding of the AWS ecosystem, one of the leading cloud service providers:

Cloud Computing on AWS: Delve into AWS's core services - Compute, Load Balancing, Autoscaling, Storage, and more. Learn about AWS Organization and Identity, Networking, and Web Application Firewall to manage cloud resources and secure your applications.

Managed Services on AWS: Explore AWS's managed services like Databases (RDS, DynamoDB), SNS, SQS, Cloudwatch, and more. Also, experience serverless computing with AWS Lambda and dive into AWS's cognitive services like Rekognition, Comprehend, and Polly.

Containers & DevOps: This section introduces Docker and AWS ECS. You'll work with the AWS deployment pipeline (AWS Code Build, Code Commit, Code Deploy, Code Pipeline) and Cloud Formation and learn about Terraform in a self-paced setting.

Enterprise Cloud Solutions: Learn to set up a cloud-based development environment and explore data architecture, data streaming, and analytics on the cloud. Get hands-on with setting up a Kinesis data stream, using Elastic Beanstalk, and working with Elasticsearch, Step Functions, and Kubernetes.

This module includes 3 quizzes, 3 projects, 10 practice quizzes, and numerous hands-on exercises for practical learning. It allows you to validate and apply your knowledge in real-world scenarios.

• Module 3: Microsoft Azure

The "Microsoft Azure" module equips learners with a thorough understanding of Azure's services and best practices:

Azure Compute Infrastructure: Understand Azure's Infrastructure Monitoring, Storage, and Virtual Machines. Learn Deployment & Configuration, Virtual Networking, and Azure Active Directory to manage and secure your infrastructure.

Azure App Solutions: Gain expertise in implementing Application Infrastructure and Container-based applications, which is crucial for modern application development.

Azure Data Implementation: Get hands-on experience with implementing NoSQL databases and Azure SQL databases, which are essential for data management in the cloud.

Azure Network & Operations: This section covers workload management, load balancing, and network security, which are essential for maintaining efficient and secure cloud operations.

Azure Security & Governance: Learn how to manage Governance Solutions and Application Security, important for maintaining compliance and security in the cloud.

Azure DevOps: This section gives you an overview of Azure DevOps, a comprehensive set of development tools, services, and features for implementing DevOps practices.

The module comprises 1 quiz, 2 projects, 7 practice quizzes, and ample hands-on practice, facilitating the application of theoretical concepts to real-world situations.

• Module 4: Capstone Project

A practical opportunity to apply your learning to industry use cases. This serves as a tangible body of work for your portfolio, showcasing your abilities to potential employers.

• Module 5: Big Data Management & Analytics (Self-Paced)

Deep dive into Big Data Management & Analytics, learning about Apache, Cassandra, and Hadoop through Amazon EMR, Spark, and Hive. This self-paced module focuses on the practice of data management and analytics in cloud environments.

• Module 6: Microservices (Self-Paced)

A comprehensive guide to Microservices, covering its expectations and characteristics, failures, load balancing, and the 12-factor app. It delves into architecture and design patterns, anti-patterns, event-driven architecture, security enforcement, and monolith migration.

• Module 7: Cloud Security & Migration (Self-Paced)

This module emphasizes the importance of security and the intricacies of migrating to the cloud, providing a practice quiz to consolidate your knowledge.

• Module 8: Google Cloud Platform (Self-Paced)

Get hands-on experience with the Google Cloud Platform. This module provides self-paced learning with practice quizzes to solidify your understanding of Google's cloud offerings.

• Module 9: Private Cloud (Self-Paced)

Learn about the configuration and management of private clouds with practical hands-on exercises to help you apply the theoretical concepts to real-world situations.