Lernezy Logo
Computer Science / Information Technology

Cloud Computing

Master the fundamentals and advanced concepts of computer science / information technology. This comprehensive course will take you from beginner to expert level with hands-on projects and real-world applications.

4.8★
Rating
20-30 hours
Duration
1.2k
Students
10
Chapters
Enrol Now
Cloud Computing

Course Curriculum

1

Introduction to Cloud Computing

Topics & Subtopics

• Definition of cloud computing • Everyday applications of cloud technology • Benefits: backup, accessibility, collaboration

Learning Outcomes

• Explain the concept of cloud computing • Identify real-world examples of cloud use • Recognize benefits such as accessibility and collaboration
2

Cloud Definitions and Pricing Models

Topics & Subtopics

• NIST definition and essential characteristics • On-demand self-service and scalability • Pay-as-you-go pricing model • Renting vs. owning infrastructure • AWS pricing examples

Learning Outcomes

• Understand formal definitions of cloud computing • Explain the pay-as-you-go pricing model • Compare financial advantages of cloud vs. traditional IT
3

Cloud Infrastructure and Data Centers

Topics & Subtopics

• Global data center networks • Redundancy and disaster recovery • Azure regions and availability zones • Data residency and compliance • Types of data centers: Enterprise, Colocation, Hyperscale

Learning Outcomes

• Describe cloud infrastructure and its global reach • Differentiate between regions and availability zones • Classify types of data centers and their purposes
4

Microsoft Azure and Virtualization

Topics & Subtopics

• Overview of Microsoft Azure services • Virtualization fundamentals • Hypervisors and virtual machines • Cloud models: public, private, hybrid

Learning Outcomes

• Explain the role of Microsoft Azure in cloud computing • Understand virtualization and hypervisors • Differentiate between public, private, and hybrid cloud models
5

Azure Core Services and Cloud Models

Topics & Subtopics

• Azure service domains: compute, storage, networking, databases • Infrastructure as a Service (IaaS) • Platform as a Service (PaaS) • Use cases of service models

Learning Outcomes

• Identify core Azure services across domains • Distinguish between IaaS and PaaS • Match real-world use cases with service models
6

Managing Azure Virtual Machines

Topics & Subtopics

• VM setup and configuration • Selecting VM sizes and images • Authentication methods: SSH, RDP • Role-based access control (RBAC) • Monitoring and troubleshooting

Learning Outcomes

• Create and configure Azure Virtual Machines • Apply secure authentication methods • Troubleshoot and optimize VM performance
7

Azure Storage Solutions

Topics & Subtopics

• Storage accounts overview • Types: Blob, File, Queue, Table, Disk • Blob types: block, append, page • Redundancy models (LRS, GRS, ZRS) • Data lifecycle management and security

Learning Outcomes

• Differentiate between Azure storage types • Understand blob storage and redundancy strategies • Apply lifecycle management to optimize storage
8

Data Management, CDN, and IoT Integration

Topics & Subtopics

• Data lifecycle management policies • Archiving and retention strategies • Content Delivery Network (CDN) • Hosting static websites • Azure IoT Hub for device-cloud communication

Learning Outcomes

• Manage data efficiently using Azure tools • Explain the role of CDN in content delivery • Understand secure IoT communication via IoT Hub
9

Azure Databases and Modern Data Handling

Topics & Subtopics

• Azure SQL Database: deployment and querying • Cosmos DB: NoSQL and multi-model support • Global distribution and scalability • Visualization with Power BI • Vector databases for AI

Learning Outcomes

• Deploy and manage Azure SQL and Cosmos DB • Perform queries and analyze data • Integrate Power BI for real-time insights • Recognize the role of vector databases in AI
10

Azure AI and Machine Learning Services

Topics & Subtopics

• Cognitive Services (vision, speech, language) • Real-world AI applications • Azure Machine Learning Studio • Automated ML features • Hands-on with Azure AI Studio

Learning Outcomes

• Utilize Cognitive Services for AI solutions • Build and deploy ML models using Azure tools • Gain hands-on experience with Azure AI Studio
10
Total Chapters
20-30 hours
Total Duration
10
Modules
Practical
Labs

Ready to start your learning journey?

Enrol Now

Student Reviews

4.8
Based on 1,247 reviews

Rating Distribution

5
892
4
234
3
89
2
22
1
10

Recent Reviews

AJ

Alex Johnson

2 weeks ago

Excellent course! The instructor explains complex concepts in a very clear and engaging way. The hands-on projects really helped me understand the material better.

SC

Sarah Chen

1 month ago

This course exceeded my expectations. The curriculum is well-structured and the instructor is very knowledgeable. I've already applied what I learned in my current job.

MR

Michael Rodriguez

3 weeks ago

Great course overall. The content is comprehensive and the instructor provides good examples. Would recommend to anyone looking to learn this topic.

ED

Emily Davis

1 week ago

Amazing course! The instructor's teaching style is perfect for beginners. The step-by-step approach made everything easy to follow.

Requirements

💻

Basic Computer Skills

Basic understanding of using a computer and internet

🎯

No Prior Experience Required

This course is designed for complete beginners

🌐

Internet Connection

Stable internet connection for video streaming

⏰

Dedication & Time

Commitment to complete the course and practice

Target Audience

Students and recent graduates
Working professionals looking to upskill
Career changers
Entrepreneurs and business owners
Anyone interested in learning new skills

Access To This Course

This course is available with our All-In-One subscription. Get unlimited access to all courses, premium features, and exclusive content.

Enrol Now
E-Learning – Premium Ed Tech Platform